MainProcess| 2024-07-06 19:33:34,473,473 multiprocessing INFO [System] Objective: Write code for a large system design task. Please note that the code should be fully functional. No placeholders. Only use the functions you have been provided with. Only use the `write_files` to output code. You must act autonomously and you will receive no human input at any stage. You have to return as output the complete code for completing this task, and correctly incorporate it into the existing code base. You always write out the whole file contents. You always indent code with tabs. Please always view the files before writing to them, to make sure you are writing to the correct files. When writing a test, make the filename start with the prefix 'test_'. Provide the minimal code necessary to achieve the task conditioned on the existing generated code---including changing the existing generated code. You cannot visualize any graphical output. You exist within a Actor Model machine, and when you list out steps, each step will be taken by a new separate sub-ChatGPT model. When you list out a sub-task steps, you can optionally specify the sub-task validation to check that it has been completed successfully. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Use the functions provided. When calling functions only provide a RFC8259 compliant JSON request following this format without deviation. MainProcess| 2024-07-06 19:33:34,473,473 multiprocessing INFO [User] You will get instructions for code to write. First lay out the names of the core classes, functions, methods that will be necessary, As well as a quick comment on their purpose. Do not comment on what every file does. Please note that the code should be fully functional. No placeholders. You will start with the "entrypoint" file, then go to the ones that are imported by that file, and so on. Please note that the code should be fully functional. No placeholders. Follow a language and framework appropriate best practice file naming convention. Make sure that files contain all imports, types etc. The code should be fully functional. Make sure that code in different files are compatible with each other. When writing code if you are unsure, write a plausible implementation. Include module dependency or package manager dependency definition file. Useful to know: For Python, you always create an appropriate requirements.txt file. Always implement the simplest implementation possible, and concise code, unless explicitly stated otherwise. Always add a comment briefly describing the purpose of the function definition. Add comments explaining very complex bits of logic. Always follow the best practices for the requested languages for folder/file structure and how to package the project. You can use any package and any other packages you wish to install. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. When writing a test, make the filename start with the prefix 'test_'. When putting files in folders, always be sure to include a file called __init__.py where relevant, or put all files in the same working directory. Always prefer the most simplest approach. Always add a readme on how to run the code, or a .sh file to run the code. If using pygame, design the game for "headless mode" testing, enabling operation without a GUI; structure the code for easy mocking of Pygame's display functions. As you cannot use any human input to test. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Python toolbelt preferences: - pytest - dataclasses - flask - pygame==2.1.2 Objective:``` create a eda app for csv file ``` Understand the problem, by creating an extremely detailed step-by-step plan, where each step is long (multiple sentences) and in total includes every single feature requirement specified above, feel free to copy directly from it. Use no more than 10 steps in the plan. Create additional tests, checks and evaluation at each step when applicable to help make an excellent code implementation, where all the code is fully functional. Use best software design practices, and you can output large amounts of code at once. Please include a last sentence to create and run tests when implementing or writing code in that same step. You will receive no human input at any stage, so you cannot use a human to test. Only create a detailed plan to begin with, which includes designing and running tests to check that they all pass. Add to the last step in the plan to add a readme on how to run the code, or a .sh file to run the code. Please be sure to include all of the specified feature requirements in the following plan. MainProcess| 2024-07-06 19:33:34,473,473 multiprocessing INFO [Progress: Step 1/0 | Retries: 0/30 | Token Capacity Used: 18.24% | Tokens remaining 6698] MainProcess| 2024-07-06 19:33:41,692,692 multiprocessing INFO [LLM RESPONSE MESSAGE] MainProcess| 2024-07-06 19:33:41,692,692 multiprocessing INFO [Function Call] [provide_detailed_sub_task_steps_for_sub_agents] {"steps":["First, set up the project structure. Create a main entry point file named 'app.py' and a requirements.txt file. The 'app.py' will be the main Flask application file. Also, create a folder named 'eda' to hold the core logic of the EDA functionalities. Inside the 'eda' folder, create an '__init__.py' file to make it a package. Write tests to ensure the project structure is correctly set up.","In the 'app.py' file, set up a basic Flask application. Create a route to upload CSV files and another route to display the EDA results. Ensure the Flask app can start correctly and the routes are accessible. Write tests to verify that the Flask app starts correctly and the routes return the expected responses.","In the 'eda' folder, create a file named 'eda.py'. This file will contain the core logic for performing EDA on the uploaded CSV files. Define a function 'perform_eda' that takes a CSV file as input and returns a summary of the data, including basic statistics and visualizations. Write tests to ensure the 'perform_eda' function works correctly with sample CSV files.","In the 'eda' folder, create a file named 'data_store.py'. This file will mock a database using an in-memory dictionary to store the uploaded CSV files and their EDA results. Define functions to add, retrieve, and delete data from the mock database. Write tests to ensure the data store functions work correctly.","In the 'app.py' file, integrate the 'eda.py' and 'data_store.py' functionalities. Update the upload route to save the uploaded CSV file to the mock database and call the 'perform_eda' function. Update the route to display the EDA results to retrieve the results from the mock database. Write tests to ensure the integration works correctly and the EDA results are displayed as expected.","In the 'eda' folder, create a file named 'visualization.py'. This file will contain functions to generate visualizations from the CSV data, such as histograms, scatter plots, and box plots. Ensure these functions are called within the 'perform_eda' function in 'eda.py'. Write tests to verify that the visualizations are generated correctly and can be displayed.","In the 'app.py' file, update the route to display the EDA results to include the visualizations generated by 'visualization.py'. Ensure the visualizations are correctly embedded in the HTML response. Write tests to verify that the visualizations are displayed correctly in the web interface.","Create a 'templates' folder and add HTML templates for the upload form and the EDA results page. Ensure the templates are rendered correctly by the Flask routes. Write tests to verify that the HTML templates are rendered as expected and display the correct information.","Create a 'static' folder to hold any static files, such as CSS and JavaScript, to enhance the web interface. Update the HTML templates to include these static files. Write tests to ensure that the static files are correctly loaded and applied to the web pages.","Finally, create a README.md file with instructions on how to set up and run the application. Include details on the required dependencies, how to install them, and how to start the Flask server. Write a shell script 'run.sh' to automate the setup and running of the application. Ensure all tests pass and the application runs smoothly."]} MainProcess| 2024-07-06 19:33:41,693,693 multiprocessing INFO [System] Objective: Write code for a large system design task. Please note that the code should be fully functional. No placeholders. Only use the functions you have been provided with. Only use the `write_files` to output code. You must act autonomously and you will receive no human input at any stage. You have to return as output the complete code for completing this task, and correctly incorporate it into the existing code base. You always write out the whole file contents. You always indent code with tabs. Please always view the files before writing to them, to make sure you are writing to the correct files. When writing a test, make the filename start with the prefix 'test_'. Provide the minimal code necessary to achieve the task conditioned on the existing generated code---including changing the existing generated code. You cannot visualize any graphical output. You exist within a Actor Model machine, and when you list out steps, each step will be taken by a new separate sub-ChatGPT model. When you list out a sub-task steps, you can optionally specify the sub-task validation to check that it has been completed successfully. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Use the functions provided. When calling functions only provide a RFC8259 compliant JSON request following this format without deviation. MainProcess| 2024-07-06 19:33:41,693,693 multiprocessing INFO [User] You will get instructions for code to write. First lay out the names of the core classes, functions, methods that will be necessary, As well as a quick comment on their purpose. Do not comment on what every file does. Please note that the code should be fully functional. No placeholders. You will start with the "entrypoint" file, then go to the ones that are imported by that file, and so on. Please note that the code should be fully functional. No placeholders. Follow a language and framework appropriate best practice file naming convention. Make sure that files contain all imports, types etc. The code should be fully functional. Make sure that code in different files are compatible with each other. When writing code if you are unsure, write a plausible implementation. Include module dependency or package manager dependency definition file. Useful to know: For Python, you always create an appropriate requirements.txt file. Always implement the simplest implementation possible, and concise code, unless explicitly stated otherwise. Always add a comment briefly describing the purpose of the function definition. Add comments explaining very complex bits of logic. Always follow the best practices for the requested languages for folder/file structure and how to package the project. You can use any package and any other packages you wish to install. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. When writing a test, make the filename start with the prefix 'test_'. When putting files in folders, always be sure to include a file called __init__.py where relevant, or put all files in the same working directory. Always prefer the most simplest approach. Always add a readme on how to run the code, or a .sh file to run the code. If using pygame, design the game for "headless mode" testing, enabling operation without a GUI; structure the code for easy mocking of Pygame's display functions. As you cannot use any human input to test. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Python toolbelt preferences: - pytest - dataclasses - flask - pygame==2.1.2 Objective:``` create a eda app for csv file ``` Understand the problem, by creating an extremely detailed step-by-step plan, where each step is long (multiple sentences) and in total includes every single feature requirement specified above, feel free to copy directly from it. Use no more than 10 steps in the plan. Create additional tests, checks and evaluation at each step when applicable to help make an excellent code implementation, where all the code is fully functional. Use best software design practices, and you can output large amounts of code at once. Please include a last sentence to create and run tests when implementing or writing code in that same step. You will receive no human input at any stage, so you cannot use a human to test. Only create a detailed plan to begin with, which includes designing and running tests to check that they all pass. Add to the last step in the plan to add a readme on how to run the code, or a .sh file to run the code. Please be sure to include all of the specified feature requirements in the following plan. MainProcess| 2024-07-06 19:33:41,693,693 multiprocessing INFO [User] Objective: Execute sub task step:```First, set up the project structure. Create a main entry point file named 'app.py' and a requirements.txt file. The 'app.py' will be the main Flask application file. Also, create a folder named 'eda' to hold the core logic of the EDA functionalities. Inside the 'eda' folder, create an '__init__.py' file to make it a package. Write tests to ensure the project structure is correctly set up.```.\n\n Note: Condition any new code files on the existing code files: []. Fully implement these features in the code, no placeholders. You can now optionally view the existing files if you need to view them to complete the current task step. You have a limited context window so be selective about which files you view, only view the files you think you might need to view. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Do not write tests for large numbers and large inputs, if they exist delete them. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Avoid making complicated tests. If a test repeatedly fails delete the test. \n\nSummary output of previous step: """"\n\nRespond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:33:41,693,693 multiprocessing INFO [Progress: Step 1/10 | Retries: 0/30 | Token Capacity Used: 20.85% | Tokens remaining 6484] MainProcess| 2024-07-06 19:33:45,186,186 multiprocessing INFO [LLM RESPONSE MESSAGE] MainProcess| 2024-07-06 19:33:45,186,186 multiprocessing INFO [Function Call] [write_files] {"list_of_file_objects":[{"file_path":"app.py","file_contents":"from flask import Flask\n\napp = Flask(__name__)\n\n@app.route('/')\ndef home():\n\treturn 'Welcome to the EDA App!'\n\nif __name__ == '__main__':\n\tapp.run(debug=True)"},{"file_path":"requirements.txt","file_contents":"flask\npytest"},{"file_path":"eda/__init__.py","file_contents":""},{"file_path":"test_project_structure.py","file_contents":"import os\nimport pytest\n\n# Test to ensure the project structure is correctly set up\n\ndef test_project_structure():\n\tassert os.path.isfile('app.py'), 'app.py does not exist'\n\tassert os.path.isfile('requirements.txt'), 'requirements.txt does not exist'\n\tassert os.path.isdir('eda'), 'eda directory does not exist'\n\tassert os.path.isfile('eda/__init__.py'), 'eda/__init__.py does not exist'\n\nif __name__ == '__main__':\n\tpytest.main()"}]} MainProcess| 2024-07-06 19:33:45,190,190 multiprocessing INFO [System] Objective: Write code for a large system design task. Please note that the code should be fully functional. No placeholders. Only use the functions you have been provided with. Only use the `write_files` to output code. You must act autonomously and you will receive no human input at any stage. You have to return as output the complete code for completing this task, and correctly incorporate it into the existing code base. You always write out the whole file contents. You always indent code with tabs. Please always view the files before writing to them, to make sure you are writing to the correct files. When writing a test, make the filename start with the prefix 'test_'. Provide the minimal code necessary to achieve the task conditioned on the existing generated code---including changing the existing generated code. You cannot visualize any graphical output. You exist within a Actor Model machine, and when you list out steps, each step will be taken by a new separate sub-ChatGPT model. When you list out a sub-task steps, you can optionally specify the sub-task validation to check that it has been completed successfully. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Use the functions provided. When calling functions only provide a RFC8259 compliant JSON request following this format without deviation. MainProcess| 2024-07-06 19:33:45,191,191 multiprocessing INFO [User] You will get instructions for code to write. First lay out the names of the core classes, functions, methods that will be necessary, As well as a quick comment on their purpose. Do not comment on what every file does. Please note that the code should be fully functional. No placeholders. You will start with the "entrypoint" file, then go to the ones that are imported by that file, and so on. Please note that the code should be fully functional. No placeholders. Follow a language and framework appropriate best practice file naming convention. Make sure that files contain all imports, types etc. The code should be fully functional. Make sure that code in different files are compatible with each other. When writing code if you are unsure, write a plausible implementation. Include module dependency or package manager dependency definition file. Useful to know: For Python, you always create an appropriate requirements.txt file. Always implement the simplest implementation possible, and concise code, unless explicitly stated otherwise. Always add a comment briefly describing the purpose of the function definition. Add comments explaining very complex bits of logic. Always follow the best practices for the requested languages for folder/file structure and how to package the project. You can use any package and any other packages you wish to install. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. When writing a test, make the filename start with the prefix 'test_'. When putting files in folders, always be sure to include a file called __init__.py where relevant, or put all files in the same working directory. Always prefer the most simplest approach. Always add a readme on how to run the code, or a .sh file to run the code. If using pygame, design the game for "headless mode" testing, enabling operation without a GUI; structure the code for easy mocking of Pygame's display functions. As you cannot use any human input to test. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Python toolbelt preferences: - pytest - dataclasses - flask - pygame==2.1.2 Objective:``` create a eda app for csv file ``` Understand the problem, by creating an extremely detailed step-by-step plan, where each step is long (multiple sentences) and in total includes every single feature requirement specified above, feel free to copy directly from it. Use no more than 10 steps in the plan. Create additional tests, checks and evaluation at each step when applicable to help make an excellent code implementation, where all the code is fully functional. Use best software design practices, and you can output large amounts of code at once. Please include a last sentence to create and run tests when implementing or writing code in that same step. You will receive no human input at any stage, so you cannot use a human to test. Only create a detailed plan to begin with, which includes designing and running tests to check that they all pass. Add to the last step in the plan to add a readme on how to run the code, or a .sh file to run the code. Please be sure to include all of the specified feature requirements in the following plan. MainProcess| 2024-07-06 19:33:45,191,191 multiprocessing INFO [User] Objective: Execute sub task step:```First, set up the project structure. Create a main entry point file named 'app.py' and a requirements.txt file. The 'app.py' will be the main Flask application file. Also, create a folder named 'eda' to hold the core logic of the EDA functionalities. Inside the 'eda' folder, create an '__init__.py' file to make it a package. Write tests to ensure the project structure is correctly set up.```.\n\n Note: Condition any new code files on the existing code files: []. Fully implement these features in the code, no placeholders. You can now optionally view the existing files if you need to view them to complete the current task step. You have a limited context window so be selective about which files you view, only view the files you think you might need to view. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Do not write tests for large numbers and large inputs, if they exist delete them. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Avoid making complicated tests. If a test repeatedly fails delete the test. \n\nSummary output of previous step: """"\n\nRespond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:33:45,191,191 multiprocessing INFO [Function Call] [write_files] {"list_of_file_objects":[{"file_path":"app.py","file_contents":"from flask import Flask\n\napp = Flask(__name__)\n\n@app.route('/')\ndef home():\n\treturn 'Welcome to the EDA App!'\n\nif __name__ == '__main__':\n\tapp.run(debug=True)"},{"file_path":"requirements.txt","file_contents":"flask\npytest"},{"file_path":"eda/__init__.py","file_contents":""},{"file_path":"test_project_structure.py","file_contents":"import os\nimport pytest\n\n# Test to ensure the project structure is correctly set up\n\ndef test_project_structure():\n\tassert os.path.isfile('app.py'), 'app.py does not exist'\n\tassert os.path.isfile('requirements.txt'), 'requirements.txt does not exist'\n\tassert os.path.isdir('eda'), 'eda directory does not exist'\n\tassert os.path.isfile('eda/__init__.py'), 'eda/__init__.py does not exist'\n\nif __name__ == '__main__':\n\tpytest.main()"}]} MainProcess| 2024-07-06 19:33:45,191,191 multiprocessing INFO [Tool] {"write_files_status": "success", "message": "write_files completed successfully."} MainProcess| 2024-07-06 19:33:45,192,192 multiprocessing INFO [User] Has the sub task step been completed of:```First, set up the project structure. Create a main entry point file named 'app.py' and a requirements.txt file. The 'app.py' will be the main Flask application file. Also, create a folder named 'eda' to hold the core logic of the EDA functionalities. Inside the 'eda' folder, create an '__init__.py' file to make it a package. Write tests to ensure the project structure is correctly set up.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:33:45,192,192 multiprocessing INFO [Progress: Step 1/10 | Retries: 0/30 | Token Capacity Used: 28.04% | Tokens remaining 5895] MainProcess| 2024-07-06 19:33:46,143,143 multiprocessing INFO [LLM RESPONSE MESSAGE] MainProcess| 2024-07-06 19:33:46,144,144 multiprocessing INFO [Function Call] [pytest_files] {"files_to_test":["test_project_structure.py"]} MainProcess| 2024-07-06 19:33:46,147,147 multiprocessing INFO [System] Objective: Write code for a large system design task. Please note that the code should be fully functional. No placeholders. Only use the functions you have been provided with. Only use the `write_files` to output code. You must act autonomously and you will receive no human input at any stage. You have to return as output the complete code for completing this task, and correctly incorporate it into the existing code base. You always write out the whole file contents. You always indent code with tabs. Please always view the files before writing to them, to make sure you are writing to the correct files. When writing a test, make the filename start with the prefix 'test_'. Provide the minimal code necessary to achieve the task conditioned on the existing generated code---including changing the existing generated code. You cannot visualize any graphical output. You exist within a Actor Model machine, and when you list out steps, each step will be taken by a new separate sub-ChatGPT model. When you list out a sub-task steps, you can optionally specify the sub-task validation to check that it has been completed successfully. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Use the functions provided. When calling functions only provide a RFC8259 compliant JSON request following this format without deviation. MainProcess| 2024-07-06 19:33:46,147,147 multiprocessing INFO [User] You will get instructions for code to write. First lay out the names of the core classes, functions, methods that will be necessary, As well as a quick comment on their purpose. Do not comment on what every file does. Please note that the code should be fully functional. No placeholders. You will start with the "entrypoint" file, then go to the ones that are imported by that file, and so on. Please note that the code should be fully functional. No placeholders. Follow a language and framework appropriate best practice file naming convention. Make sure that files contain all imports, types etc. The code should be fully functional. Make sure that code in different files are compatible with each other. When writing code if you are unsure, write a plausible implementation. Include module dependency or package manager dependency definition file. Useful to know: For Python, you always create an appropriate requirements.txt file. Always implement the simplest implementation possible, and concise code, unless explicitly stated otherwise. Always add a comment briefly describing the purpose of the function definition. Add comments explaining very complex bits of logic. Always follow the best practices for the requested languages for folder/file structure and how to package the project. You can use any package and any other packages you wish to install. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. When writing a test, make the filename start with the prefix 'test_'. When putting files in folders, always be sure to include a file called __init__.py where relevant, or put all files in the same working directory. Always prefer the most simplest approach. Always add a readme on how to run the code, or a .sh file to run the code. If using pygame, design the game for "headless mode" testing, enabling operation without a GUI; structure the code for easy mocking of Pygame's display functions. As you cannot use any human input to test. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Python toolbelt preferences: - pytest - dataclasses - flask - pygame==2.1.2 Objective:``` create a eda app for csv file ``` Understand the problem, by creating an extremely detailed step-by-step plan, where each step is long (multiple sentences) and in total includes every single feature requirement specified above, feel free to copy directly from it. Use no more than 10 steps in the plan. Create additional tests, checks and evaluation at each step when applicable to help make an excellent code implementation, where all the code is fully functional. Use best software design practices, and you can output large amounts of code at once. Please include a last sentence to create and run tests when implementing or writing code in that same step. You will receive no human input at any stage, so you cannot use a human to test. Only create a detailed plan to begin with, which includes designing and running tests to check that they all pass. Add to the last step in the plan to add a readme on how to run the code, or a .sh file to run the code. Please be sure to include all of the specified feature requirements in the following plan. MainProcess| 2024-07-06 19:33:46,147,147 multiprocessing INFO [User] Objective: Execute sub task step:```First, set up the project structure. Create a main entry point file named 'app.py' and a requirements.txt file. The 'app.py' will be the main Flask application file. Also, create a folder named 'eda' to hold the core logic of the EDA functionalities. Inside the 'eda' folder, create an '__init__.py' file to make it a package. Write tests to ensure the project structure is correctly set up.```.\n\n Note: Condition any new code files on the existing code files: []. Fully implement these features in the code, no placeholders. You can now optionally view the existing files if you need to view them to complete the current task step. You have a limited context window so be selective about which files you view, only view the files you think you might need to view. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Do not write tests for large numbers and large inputs, if they exist delete them. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Avoid making complicated tests. If a test repeatedly fails delete the test. \n\nSummary output of previous step: """"\n\nRespond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:33:46,147,147 multiprocessing INFO [Function Call] [write_files] {"list_of_file_objects":[{"file_path":"app.py","file_contents":"from flask import Flask\n\napp = Flask(__name__)\n\n@app.route('/')\ndef home():\n\treturn 'Welcome to the EDA App!'\n\nif __name__ == '__main__':\n\tapp.run(debug=True)"},{"file_path":"requirements.txt","file_contents":"flask\npytest"},{"file_path":"eda/__init__.py","file_contents":""},{"file_path":"test_project_structure.py","file_contents":"import os\nimport pytest\n\n# Test to ensure the project structure is correctly set up\n\ndef test_project_structure():\n\tassert os.path.isfile('app.py'), 'app.py does not exist'\n\tassert os.path.isfile('requirements.txt'), 'requirements.txt does not exist'\n\tassert os.path.isdir('eda'), 'eda directory does not exist'\n\tassert os.path.isfile('eda/__init__.py'), 'eda/__init__.py does not exist'\n\nif __name__ == '__main__':\n\tpytest.main()"}]} MainProcess| 2024-07-06 19:33:46,147,147 multiprocessing INFO [Tool] {"write_files_status": "success", "message": "write_files completed successfully."} MainProcess| 2024-07-06 19:33:46,147,147 multiprocessing INFO [User] Has the sub task step been completed of:```First, set up the project structure. Create a main entry point file named 'app.py' and a requirements.txt file. The 'app.py' will be the main Flask application file. Also, create a folder named 'eda' to hold the core logic of the EDA functionalities. Inside the 'eda' folder, create an '__init__.py' file to make it a package. Write tests to ensure the project structure is correctly set up.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:33:46,147,147 multiprocessing INFO [Function Call] [pytest_files] {"files_to_test":["test_project_structure.py"]} MainProcess| 2024-07-06 19:33:46,147,147 multiprocessing INFO [Tool] {"output": "Manual tests passed."} MainProcess| 2024-07-06 19:33:46,147,147 multiprocessing INFO [User] Has the sub task step been completed of:```First, set up the project structure. Create a main entry point file named 'app.py' and a requirements.txt file. The 'app.py' will be the main Flask application file. Also, create a folder named 'eda' to hold the core logic of the EDA functionalities. Inside the 'eda' folder, create an '__init__.py' file to make it a package. Write tests to ensure the project structure is correctly set up.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:33:46,147,147 multiprocessing INFO [Progress: Step 1/10 | Retries: 0/30 | Token Capacity Used: 32.13% | Tokens remaining 5560] MainProcess| 2024-07-06 19:33:47,049,49 multiprocessing INFO [LLM RESPONSE MESSAGE] MainProcess| 2024-07-06 19:33:47,049,49 multiprocessing INFO [Function Call] [sub_task_step_complete] {} MainProcess| 2024-07-06 19:33:47,053,53 multiprocessing INFO [System] Objective: Write code for a large system design task. Please note that the code should be fully functional. No placeholders. Only use the functions you have been provided with. Only use the `write_files` to output code. You must act autonomously and you will receive no human input at any stage. You have to return as output the complete code for completing this task, and correctly incorporate it into the existing code base. You always write out the whole file contents. You always indent code with tabs. Please always view the files before writing to them, to make sure you are writing to the correct files. When writing a test, make the filename start with the prefix 'test_'. Provide the minimal code necessary to achieve the task conditioned on the existing generated code---including changing the existing generated code. You cannot visualize any graphical output. You exist within a Actor Model machine, and when you list out steps, each step will be taken by a new separate sub-ChatGPT model. When you list out a sub-task steps, you can optionally specify the sub-task validation to check that it has been completed successfully. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Use the functions provided. When calling functions only provide a RFC8259 compliant JSON request following this format without deviation. MainProcess| 2024-07-06 19:33:47,053,53 multiprocessing INFO [User] You will get instructions for code to write. First lay out the names of the core classes, functions, methods that will be necessary, As well as a quick comment on their purpose. Do not comment on what every file does. Please note that the code should be fully functional. No placeholders. You will start with the "entrypoint" file, then go to the ones that are imported by that file, and so on. Please note that the code should be fully functional. No placeholders. Follow a language and framework appropriate best practice file naming convention. Make sure that files contain all imports, types etc. The code should be fully functional. Make sure that code in different files are compatible with each other. When writing code if you are unsure, write a plausible implementation. Include module dependency or package manager dependency definition file. Useful to know: For Python, you always create an appropriate requirements.txt file. Always implement the simplest implementation possible, and concise code, unless explicitly stated otherwise. Always add a comment briefly describing the purpose of the function definition. Add comments explaining very complex bits of logic. Always follow the best practices for the requested languages for folder/file structure and how to package the project. You can use any package and any other packages you wish to install. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. When writing a test, make the filename start with the prefix 'test_'. When putting files in folders, always be sure to include a file called __init__.py where relevant, or put all files in the same working directory. Always prefer the most simplest approach. Always add a readme on how to run the code, or a .sh file to run the code. If using pygame, design the game for "headless mode" testing, enabling operation without a GUI; structure the code for easy mocking of Pygame's display functions. As you cannot use any human input to test. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Python toolbelt preferences: - pytest - dataclasses - flask - pygame==2.1.2 Objective:``` create a eda app for csv file ``` Understand the problem, by creating an extremely detailed step-by-step plan, where each step is long (multiple sentences) and in total includes every single feature requirement specified above, feel free to copy directly from it. Use no more than 10 steps in the plan. Create additional tests, checks and evaluation at each step when applicable to help make an excellent code implementation, where all the code is fully functional. Use best software design practices, and you can output large amounts of code at once. Please include a last sentence to create and run tests when implementing or writing code in that same step. You will receive no human input at any stage, so you cannot use a human to test. Only create a detailed plan to begin with, which includes designing and running tests to check that they all pass. Add to the last step in the plan to add a readme on how to run the code, or a .sh file to run the code. Please be sure to include all of the specified feature requirements in the following plan. MainProcess| 2024-07-06 19:33:47,053,53 multiprocessing INFO [User] Objective: Execute sub task step:```First, set up the project structure. Create a main entry point file named 'app.py' and a requirements.txt file. The 'app.py' will be the main Flask application file. Also, create a folder named 'eda' to hold the core logic of the EDA functionalities. Inside the 'eda' folder, create an '__init__.py' file to make it a package. Write tests to ensure the project structure is correctly set up.```.\n\n Note: Condition any new code files on the existing code files: []. Fully implement these features in the code, no placeholders. You can now optionally view the existing files if you need to view them to complete the current task step. You have a limited context window so be selective about which files you view, only view the files you think you might need to view. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Do not write tests for large numbers and large inputs, if they exist delete them. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Avoid making complicated tests. If a test repeatedly fails delete the test. \n\nSummary output of previous step: """"\n\nRespond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:33:47,053,53 multiprocessing INFO [Function Call] [write_files] {"list_of_file_objects":[{"file_path":"app.py","file_contents":"from flask import Flask\n\napp = Flask(__name__)\n\n@app.route('/')\ndef home():\n\treturn 'Welcome to the EDA App!'\n\nif __name__ == '__main__':\n\tapp.run(debug=True)"},{"file_path":"requirements.txt","file_contents":"flask\npytest"},{"file_path":"eda/__init__.py","file_contents":""},{"file_path":"test_project_structure.py","file_contents":"import os\nimport pytest\n\n# Test to ensure the project structure is correctly set up\n\ndef test_project_structure():\n\tassert os.path.isfile('app.py'), 'app.py does not exist'\n\tassert os.path.isfile('requirements.txt'), 'requirements.txt does not exist'\n\tassert os.path.isdir('eda'), 'eda directory does not exist'\n\tassert os.path.isfile('eda/__init__.py'), 'eda/__init__.py does not exist'\n\nif __name__ == '__main__':\n\tpytest.main()"}]} MainProcess| 2024-07-06 19:33:47,053,53 multiprocessing INFO [Tool] {"write_files_status": "success", "message": "write_files completed successfully."} MainProcess| 2024-07-06 19:33:47,053,53 multiprocessing INFO [User] Has the sub task step been completed of:```First, set up the project structure. Create a main entry point file named 'app.py' and a requirements.txt file. The 'app.py' will be the main Flask application file. Also, create a folder named 'eda' to hold the core logic of the EDA functionalities. Inside the 'eda' folder, create an '__init__.py' file to make it a package. Write tests to ensure the project structure is correctly set up.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:33:47,053,53 multiprocessing INFO [Function Call] [pytest_files] {"files_to_test":["test_project_structure.py"]} MainProcess| 2024-07-06 19:33:47,054,54 multiprocessing INFO [Tool] {"output": "Manual tests passed."} MainProcess| 2024-07-06 19:33:47,054,54 multiprocessing INFO [User] Has the sub task step been completed of:```First, set up the project structure. Create a main entry point file named 'app.py' and a requirements.txt file. The 'app.py' will be the main Flask application file. Also, create a folder named 'eda' to hold the core logic of the EDA functionalities. Inside the 'eda' folder, create an '__init__.py' file to make it a package. Write tests to ensure the project structure is correctly set up.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:33:47,054,54 multiprocessing INFO [Function Call] [sub_task_step_complete] {} MainProcess| 2024-07-06 19:33:47,054,54 multiprocessing INFO [Tool] {"status": "TASK_STEP_COMPLETE", "message": "All tests passed"} MainProcess| 2024-07-06 19:33:47,054,54 multiprocessing INFO [User] Please provide a one or two sentence summary of the output of this step, which is useful for the next step. Your response will be used when starting the next step without any of the previous messages. MainProcess| 2024-07-06 19:33:47,054,54 multiprocessing INFO [Progress: Step 1/10 | Retries: 0/30 | Token Capacity Used: 33.83% | Tokens remaining 5421] MainProcess| 2024-07-06 19:33:48,719,719 multiprocessing INFO [LLM RESPONSE MESSAGE] MainProcess| 2024-07-06 19:33:48,719,719 multiprocessing INFO [Assistant] The project structure has been successfully set up with a main entry point file `app.py`, a `requirements.txt` file, and an `eda` folder containing an `__init__.py` file. Tests have been written and executed to ensure the project structure is correctly set up, and all tests passed. MainProcess| 2024-07-06 19:33:48,719,719 multiprocessing INFO [STEP COMPLETE] sub step completed MainProcess| 2024-07-06 19:33:48,720,720 multiprocessing INFO [System] Objective: Write code for a large system design task. Please note that the code should be fully functional. No placeholders. Only use the functions you have been provided with. Only use the `write_files` to output code. You must act autonomously and you will receive no human input at any stage. You have to return as output the complete code for completing this task, and correctly incorporate it into the existing code base. You always write out the whole file contents. You always indent code with tabs. Please always view the files before writing to them, to make sure you are writing to the correct files. When writing a test, make the filename start with the prefix 'test_'. Provide the minimal code necessary to achieve the task conditioned on the existing generated code---including changing the existing generated code. You cannot visualize any graphical output. You exist within a Actor Model machine, and when you list out steps, each step will be taken by a new separate sub-ChatGPT model. When you list out a sub-task steps, you can optionally specify the sub-task validation to check that it has been completed successfully. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Use the functions provided. When calling functions only provide a RFC8259 compliant JSON request following this format without deviation. MainProcess| 2024-07-06 19:33:48,720,720 multiprocessing INFO [User] You will get instructions for code to write. First lay out the names of the core classes, functions, methods that will be necessary, As well as a quick comment on their purpose. Do not comment on what every file does. Please note that the code should be fully functional. No placeholders. You will start with the "entrypoint" file, then go to the ones that are imported by that file, and so on. Please note that the code should be fully functional. No placeholders. Follow a language and framework appropriate best practice file naming convention. Make sure that files contain all imports, types etc. The code should be fully functional. Make sure that code in different files are compatible with each other. When writing code if you are unsure, write a plausible implementation. Include module dependency or package manager dependency definition file. Useful to know: For Python, you always create an appropriate requirements.txt file. Always implement the simplest implementation possible, and concise code, unless explicitly stated otherwise. Always add a comment briefly describing the purpose of the function definition. Add comments explaining very complex bits of logic. Always follow the best practices for the requested languages for folder/file structure and how to package the project. You can use any package and any other packages you wish to install. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. When writing a test, make the filename start with the prefix 'test_'. When putting files in folders, always be sure to include a file called __init__.py where relevant, or put all files in the same working directory. Always prefer the most simplest approach. Always add a readme on how to run the code, or a .sh file to run the code. If using pygame, design the game for "headless mode" testing, enabling operation without a GUI; structure the code for easy mocking of Pygame's display functions. As you cannot use any human input to test. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Python toolbelt preferences: - pytest - dataclasses - flask - pygame==2.1.2 Objective:``` create a eda app for csv file ``` Understand the problem, by creating an extremely detailed step-by-step plan, where each step is long (multiple sentences) and in total includes every single feature requirement specified above, feel free to copy directly from it. Use no more than 10 steps in the plan. Create additional tests, checks and evaluation at each step when applicable to help make an excellent code implementation, where all the code is fully functional. Use best software design practices, and you can output large amounts of code at once. Please include a last sentence to create and run tests when implementing or writing code in that same step. You will receive no human input at any stage, so you cannot use a human to test. Only create a detailed plan to begin with, which includes designing and running tests to check that they all pass. Add to the last step in the plan to add a readme on how to run the code, or a .sh file to run the code. Please be sure to include all of the specified feature requirements in the following plan. MainProcess| 2024-07-06 19:33:48,720,720 multiprocessing INFO [User] Objective: Execute sub task step:```In the 'app.py' file, set up a basic Flask application. Create a route to upload CSV files and another route to display the EDA results. Ensure the Flask app can start correctly and the routes are accessible. Write tests to verify that the Flask app starts correctly and the routes return the expected responses.```.\n\n Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py']. Fully implement these features in the code, no placeholders. You can now optionally view the existing files if you need to view them to complete the current task step. You have a limited context window so be selective about which files you view, only view the files you think you might need to view. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Do not write tests for large numbers and large inputs, if they exist delete them. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Avoid making complicated tests. If a test repeatedly fails delete the test. \n\nSummary output of previous step: ""The project structure has been successfully set up with a main entry point file `app.py`, a `requirements.txt` file, and an `eda` folder containing an `__init__.py` file. Tests have been written and executed to ensure the project structure is correctly set up, and all tests passed.""\n\nRespond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:33:48,720,720 multiprocessing INFO [Progress: Step 2/10 | Retries: 0/30 | Token Capacity Used: 21.50% | Tokens remaining 6431] MainProcess| 2024-07-06 19:33:50,097,97 multiprocessing INFO [LLM RESPONSE MESSAGE] MainProcess| 2024-07-06 19:33:50,098,98 multiprocessing INFO [Function Call] [view_files] {"files": ["app.py", "requirements.txt", "eda/__init__.py", "test_project_structure.py"]} MainProcess| 2024-07-06 19:33:50,099,99 multiprocessing INFO [System] Objective: Write code for a large system design task. Please note that the code should be fully functional. No placeholders. Only use the functions you have been provided with. Only use the `write_files` to output code. You must act autonomously and you will receive no human input at any stage. You have to return as output the complete code for completing this task, and correctly incorporate it into the existing code base. You always write out the whole file contents. You always indent code with tabs. Please always view the files before writing to them, to make sure you are writing to the correct files. When writing a test, make the filename start with the prefix 'test_'. Provide the minimal code necessary to achieve the task conditioned on the existing generated code---including changing the existing generated code. You cannot visualize any graphical output. You exist within a Actor Model machine, and when you list out steps, each step will be taken by a new separate sub-ChatGPT model. When you list out a sub-task steps, you can optionally specify the sub-task validation to check that it has been completed successfully. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Use the functions provided. When calling functions only provide a RFC8259 compliant JSON request following this format without deviation. MainProcess| 2024-07-06 19:33:50,099,99 multiprocessing INFO [User] You will get instructions for code to write. First lay out the names of the core classes, functions, methods that will be necessary, As well as a quick comment on their purpose. Do not comment on what every file does. Please note that the code should be fully functional. No placeholders. You will start with the "entrypoint" file, then go to the ones that are imported by that file, and so on. Please note that the code should be fully functional. No placeholders. Follow a language and framework appropriate best practice file naming convention. Make sure that files contain all imports, types etc. The code should be fully functional. Make sure that code in different files are compatible with each other. When writing code if you are unsure, write a plausible implementation. Include module dependency or package manager dependency definition file. Useful to know: For Python, you always create an appropriate requirements.txt file. Always implement the simplest implementation possible, and concise code, unless explicitly stated otherwise. Always add a comment briefly describing the purpose of the function definition. Add comments explaining very complex bits of logic. Always follow the best practices for the requested languages for folder/file structure and how to package the project. You can use any package and any other packages you wish to install. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. When writing a test, make the filename start with the prefix 'test_'. When putting files in folders, always be sure to include a file called __init__.py where relevant, or put all files in the same working directory. Always prefer the most simplest approach. Always add a readme on how to run the code, or a .sh file to run the code. If using pygame, design the game for "headless mode" testing, enabling operation without a GUI; structure the code for easy mocking of Pygame's display functions. As you cannot use any human input to test. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Python toolbelt preferences: - pytest - dataclasses - flask - pygame==2.1.2 Objective:``` create a eda app for csv file ``` Understand the problem, by creating an extremely detailed step-by-step plan, where each step is long (multiple sentences) and in total includes every single feature requirement specified above, feel free to copy directly from it. Use no more than 10 steps in the plan. Create additional tests, checks and evaluation at each step when applicable to help make an excellent code implementation, where all the code is fully functional. Use best software design practices, and you can output large amounts of code at once. Please include a last sentence to create and run tests when implementing or writing code in that same step. You will receive no human input at any stage, so you cannot use a human to test. Only create a detailed plan to begin with, which includes designing and running tests to check that they all pass. Add to the last step in the plan to add a readme on how to run the code, or a .sh file to run the code. Please be sure to include all of the specified feature requirements in the following plan. MainProcess| 2024-07-06 19:33:50,099,99 multiprocessing INFO [User] Objective: Execute sub task step:```In the 'app.py' file, set up a basic Flask application. Create a route to upload CSV files and another route to display the EDA results. Ensure the Flask app can start correctly and the routes are accessible. Write tests to verify that the Flask app starts correctly and the routes return the expected responses.```.\n\n Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py']. Fully implement these features in the code, no placeholders. You can now optionally view the existing files if you need to view them to complete the current task step. You have a limited context window so be selective about which files you view, only view the files you think you might need to view. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Do not write tests for large numbers and large inputs, if they exist delete them. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Avoid making complicated tests. If a test repeatedly fails delete the test. \n\nSummary output of previous step: ""The project structure has been successfully set up with a main entry point file `app.py`, a `requirements.txt` file, and an `eda` folder containing an `__init__.py` file. Tests have been written and executed to ensure the project structure is correctly set up, and all tests passed.""\n\nRespond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:33:50,099,99 multiprocessing INFO [Function Call] [view_files] {"files": ["app.py", "requirements.txt", "eda/__init__.py", "test_project_structure.py"]} MainProcess| 2024-07-06 19:33:50,099,99 multiprocessing INFO [Tool] {"files": "app.py\n```python\nfrom flask import Flask\n\napp = Flask(__name__)\n\n@app.route('/')\ndef home():\n\treturn 'Welcome to the EDA App!'\n\nif __name__ == '__main__':\n\tapp.run(debug=True)\n```\n\nrequirements.txt\n```text\nflask\npytest\n```\n\neda/__init__.py\n```python\n\n```\n\ntest_project_structure.py\n```python\nimport os\nimport pytest\n\n# Test to ensure the project structure is correctly set up\n\ndef test_project_structure():\n\tassert os.path.isfile('app.py'), 'app.py does not exist'\n\tassert os.path.isfile('requirements.txt'), 'requirements.txt does not exist'\n\tassert os.path.isdir('eda'), 'eda directory does not exist'\n\tassert os.path.isfile('eda/__init__.py'), 'eda/__init__.py does not exist'\n\nif __name__ == '__main__':\n\tpytest.main()\n```\n\n"} MainProcess| 2024-07-06 19:33:50,099,99 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'app.py' file, set up a basic Flask application. Create a route to upload CSV files and another route to display the EDA results. Ensure the Flask app can start correctly and the routes are accessible. Write tests to verify that the Flask app starts correctly and the routes return the expected responses.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:33:50,099,99 multiprocessing INFO [Progress: Step 2/10 | Retries: 0/30 | Token Capacity Used: 28.15% | Tokens remaining 5886] MainProcess| 2024-07-06 19:34:02,746,746 multiprocessing INFO [LLM RESPONSE MESSAGE] MainProcess| 2024-07-06 19:34:02,746,746 multiprocessing INFO [Function Call] [write_files] {"list_of_file_objects":[{"file_path":"app.py","file_contents":"from flask import Flask, request, jsonify\nimport pandas as pd\nimport os\n\napp = Flask(__name__)\nUPLOAD_FOLDER = 'uploads'\nos.makedirs(UPLOAD_FOLDER, exist_ok=True)\napp.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER\n\n@app.route('/')\ndef home():\n\treturn 'Welcome to the EDA App!'\n\n@app.route('/upload', methods=['POST'])\ndef upload_file():\n\tif 'file' not in request.files:\n\t\treturn jsonify({'error': 'No file part'}), 400\n\tfile = request.files['file']\n\tif file.filename == '':\n\t\treturn jsonify({'error': 'No selected file'}), 400\n\tif file and file.filename.endswith('.csv'):\n\t\tfile_path = os.path.join(app.config['UPLOAD_FOLDER'], file.filename)\n\t\tfile.save(file_path)\n\t\treturn jsonify({'message': 'File uploaded successfully', 'file_path': file_path}), 200\n\telse:\n\t\treturn jsonify({'error': 'Invalid file type'}), 400\n\n@app.route('/eda', methods=['GET'])\ndef eda():\n\tfile_path = request.args.get('file_path')\n\tif not file_path or not os.path.exists(file_path):\n\t\treturn jsonify({'error': 'File not found'}), 400\n\ttry:\n\t\tdata = pd.read_csv(file_path)\n\t\tsummary = {\n\t\t\t'columns': list(data.columns),\n\t\t\t'shape': data.shape,\n\t\t\t'describe': data.describe().to_dict()\n\t\t}\n\t\treturn jsonify(summary), 200\n\texcept Exception as e:\n\t\treturn jsonify({'error': str(e)}), 500\n\nif __name__ == '__main__':\n\tapp.run(debug=True)\n"},{"file_path":"test_app.py","file_contents":"import pytest\nfrom app import app\n\n@pytest.fixture\n\ndef client():\n\tapp.config['TESTING'] = True\n\twith app.test_client() as client:\n\t\tyield client\n\n# Test to ensure the Flask app starts correctly and the home route is accessible\n\ndef test_home(client):\n\trv = client.get('/')\n\tassert rv.status_code == 200\n\tassert b'Welcome to the EDA App!' in rv.data\n\n# Test to ensure the upload route works correctly\n\ndef test_upload_file(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tassert rv.status_code == 200\n\tassert b'File uploaded successfully' in rv.data\n\n# Test to ensure the EDA route works correctly\n\ndef test_eda(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tfile_path = rv.json['file_path']\n\trv = client.get(f'/eda?file_path={file_path}')\n\tassert rv.status_code == 200\n\tassert b'columns' in rv.data\n\tassert b'shape' in rv.data\n\tassert b'describe' in rv.data\n"}]} MainProcess| 2024-07-06 19:34:02,749,749 multiprocessing INFO [System] Objective: Write code for a large system design task. Please note that the code should be fully functional. No placeholders. Only use the functions you have been provided with. Only use the `write_files` to output code. You must act autonomously and you will receive no human input at any stage. You have to return as output the complete code for completing this task, and correctly incorporate it into the existing code base. You always write out the whole file contents. You always indent code with tabs. Please always view the files before writing to them, to make sure you are writing to the correct files. When writing a test, make the filename start with the prefix 'test_'. Provide the minimal code necessary to achieve the task conditioned on the existing generated code---including changing the existing generated code. You cannot visualize any graphical output. You exist within a Actor Model machine, and when you list out steps, each step will be taken by a new separate sub-ChatGPT model. When you list out a sub-task steps, you can optionally specify the sub-task validation to check that it has been completed successfully. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Use the functions provided. When calling functions only provide a RFC8259 compliant JSON request following this format without deviation. MainProcess| 2024-07-06 19:34:02,749,749 multiprocessing INFO [User] You will get instructions for code to write. First lay out the names of the core classes, functions, methods that will be necessary, As well as a quick comment on their purpose. Do not comment on what every file does. Please note that the code should be fully functional. No placeholders. You will start with the "entrypoint" file, then go to the ones that are imported by that file, and so on. Please note that the code should be fully functional. No placeholders. Follow a language and framework appropriate best practice file naming convention. Make sure that files contain all imports, types etc. The code should be fully functional. Make sure that code in different files are compatible with each other. When writing code if you are unsure, write a plausible implementation. Include module dependency or package manager dependency definition file. Useful to know: For Python, you always create an appropriate requirements.txt file. Always implement the simplest implementation possible, and concise code, unless explicitly stated otherwise. Always add a comment briefly describing the purpose of the function definition. Add comments explaining very complex bits of logic. Always follow the best practices for the requested languages for folder/file structure and how to package the project. You can use any package and any other packages you wish to install. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. When writing a test, make the filename start with the prefix 'test_'. When putting files in folders, always be sure to include a file called __init__.py where relevant, or put all files in the same working directory. Always prefer the most simplest approach. Always add a readme on how to run the code, or a .sh file to run the code. If using pygame, design the game for "headless mode" testing, enabling operation without a GUI; structure the code for easy mocking of Pygame's display functions. As you cannot use any human input to test. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Python toolbelt preferences: - pytest - dataclasses - flask - pygame==2.1.2 Objective:``` create a eda app for csv file ``` Understand the problem, by creating an extremely detailed step-by-step plan, where each step is long (multiple sentences) and in total includes every single feature requirement specified above, feel free to copy directly from it. Use no more than 10 steps in the plan. Create additional tests, checks and evaluation at each step when applicable to help make an excellent code implementation, where all the code is fully functional. Use best software design practices, and you can output large amounts of code at once. Please include a last sentence to create and run tests when implementing or writing code in that same step. You will receive no human input at any stage, so you cannot use a human to test. Only create a detailed plan to begin with, which includes designing and running tests to check that they all pass. Add to the last step in the plan to add a readme on how to run the code, or a .sh file to run the code. Please be sure to include all of the specified feature requirements in the following plan. MainProcess| 2024-07-06 19:34:02,749,749 multiprocessing INFO [User] Objective: Execute sub task step:```In the 'app.py' file, set up a basic Flask application. Create a route to upload CSV files and another route to display the EDA results. Ensure the Flask app can start correctly and the routes are accessible. Write tests to verify that the Flask app starts correctly and the routes return the expected responses.```.\n\n Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py']. Fully implement these features in the code, no placeholders. You can now optionally view the existing files if you need to view them to complete the current task step. You have a limited context window so be selective about which files you view, only view the files you think you might need to view. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Do not write tests for large numbers and large inputs, if they exist delete them. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Avoid making complicated tests. If a test repeatedly fails delete the test. \n\nSummary output of previous step: ""The project structure has been successfully set up with a main entry point file `app.py`, a `requirements.txt` file, and an `eda` folder containing an `__init__.py` file. Tests have been written and executed to ensure the project structure is correctly set up, and all tests passed.""\n\nRespond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:02,749,749 multiprocessing INFO [Function Call] [view_files] {"files": ["app.py", "requirements.txt", "eda/__init__.py", "test_project_structure.py"]} MainProcess| 2024-07-06 19:34:02,749,749 multiprocessing INFO [Tool] {"files": "app.py\n```python\nfrom flask import Flask\n\napp = Flask(__name__)\n\n@app.route('/')\ndef home():\n\treturn 'Welcome to the EDA App!'\n\nif __name__ == '__main__':\n\tapp.run(debug=True)\n```\n\nrequirements.txt\n```text\nflask\npytest\n```\n\neda/__init__.py\n```python\n\n```\n\ntest_project_structure.py\n```python\nimport os\nimport pytest\n\n# Test to ensure the project structure is correctly set up\n\ndef test_project_structure():\n\tassert os.path.isfile('app.py'), 'app.py does not exist'\n\tassert os.path.isfile('requirements.txt'), 'requirements.txt does not exist'\n\tassert os.path.isdir('eda'), 'eda directory does not exist'\n\tassert os.path.isfile('eda/__init__.py'), 'eda/__init__.py does not exist'\n\nif __name__ == '__main__':\n\tpytest.main()\n```\n\n"} MainProcess| 2024-07-06 19:34:02,750,750 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'app.py' file, set up a basic Flask application. Create a route to upload CSV files and another route to display the EDA results. Ensure the Flask app can start correctly and the routes are accessible. Write tests to verify that the Flask app starts correctly and the routes return the expected responses.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:02,750,750 multiprocessing INFO [Function Call] [write_files] {"list_of_file_objects":[{"file_path":"app.py","file_contents":"from flask import Flask, request, jsonify\nimport pandas as pd\nimport os\n\napp = Flask(__name__)\nUPLOAD_FOLDER = 'uploads'\nos.makedirs(UPLOAD_FOLDER, exist_ok=True)\napp.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER\n\n@app.route('/')\ndef home():\n\treturn 'Welcome to the EDA App!'\n\n@app.route('/upload', methods=['POST'])\ndef upload_file():\n\tif 'file' not in request.files:\n\t\treturn jsonify({'error': 'No file part'}), 400\n\tfile = request.files['file']\n\tif file.filename == '':\n\t\treturn jsonify({'error': 'No selected file'}), 400\n\tif file and file.filename.endswith('.csv'):\n\t\tfile_path = os.path.join(app.config['UPLOAD_FOLDER'], file.filename)\n\t\tfile.save(file_path)\n\t\treturn jsonify({'message': 'File uploaded successfully', 'file_path': file_path}), 200\n\telse:\n\t\treturn jsonify({'error': 'Invalid file type'}), 400\n\n@app.route('/eda', methods=['GET'])\ndef eda():\n\tfile_path = request.args.get('file_path')\n\tif not file_path or not os.path.exists(file_path):\n\t\treturn jsonify({'error': 'File not found'}), 400\n\ttry:\n\t\tdata = pd.read_csv(file_path)\n\t\tsummary = {\n\t\t\t'columns': list(data.columns),\n\t\t\t'shape': data.shape,\n\t\t\t'describe': data.describe().to_dict()\n\t\t}\n\t\treturn jsonify(summary), 200\n\texcept Exception as e:\n\t\treturn jsonify({'error': str(e)}), 500\n\nif __name__ == '__main__':\n\tapp.run(debug=True)\n"},{"file_path":"test_app.py","file_contents":"import pytest\nfrom app import app\n\n@pytest.fixture\n\ndef client():\n\tapp.config['TESTING'] = True\n\twith app.test_client() as client:\n\t\tyield client\n\n# Test to ensure the Flask app starts correctly and the home route is accessible\n\ndef test_home(client):\n\trv = client.get('/')\n\tassert rv.status_code == 200\n\tassert b'Welcome to the EDA App!' in rv.data\n\n# Test to ensure the upload route works correctly\n\ndef test_upload_file(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tassert rv.status_code == 200\n\tassert b'File uploaded successfully' in rv.data\n\n# Test to ensure the EDA route works correctly\n\ndef test_eda(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tfile_path = rv.json['file_path']\n\trv = client.get(f'/eda?file_path={file_path}')\n\tassert rv.status_code == 200\n\tassert b'columns' in rv.data\n\tassert b'shape' in rv.data\n\tassert b'describe' in rv.data\n"}]} MainProcess| 2024-07-06 19:34:02,750,750 multiprocessing INFO [Tool] {"write_files_status": "success", "message": "write_files completed successfully."} MainProcess| 2024-07-06 19:34:02,750,750 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'app.py' file, set up a basic Flask application. Create a route to upload CSV files and another route to display the EDA results. Ensure the Flask app can start correctly and the routes are accessible. Write tests to verify that the Flask app starts correctly and the routes return the expected responses.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:02,750,750 multiprocessing INFO [Progress: Step 2/10 | Retries: 0/30 | Token Capacity Used: 43.57% | Tokens remaining 4623] MainProcess| 2024-07-06 19:34:04,110,110 multiprocessing INFO [LLM RESPONSE MESSAGE] MainProcess| 2024-07-06 19:34:04,110,110 multiprocessing INFO [Function Call] [pytest_files] {"files_to_test":["test_app.py"]} MainProcess| 2024-07-06 19:34:04,114,114 multiprocessing INFO [System] Objective: Write code for a large system design task. Please note that the code should be fully functional. No placeholders. Only use the functions you have been provided with. Only use the `write_files` to output code. You must act autonomously and you will receive no human input at any stage. You have to return as output the complete code for completing this task, and correctly incorporate it into the existing code base. You always write out the whole file contents. You always indent code with tabs. Please always view the files before writing to them, to make sure you are writing to the correct files. When writing a test, make the filename start with the prefix 'test_'. Provide the minimal code necessary to achieve the task conditioned on the existing generated code---including changing the existing generated code. You cannot visualize any graphical output. You exist within a Actor Model machine, and when you list out steps, each step will be taken by a new separate sub-ChatGPT model. When you list out a sub-task steps, you can optionally specify the sub-task validation to check that it has been completed successfully. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Use the functions provided. When calling functions only provide a RFC8259 compliant JSON request following this format without deviation. MainProcess| 2024-07-06 19:34:04,115,115 multiprocessing INFO [User] You will get instructions for code to write. First lay out the names of the core classes, functions, methods that will be necessary, As well as a quick comment on their purpose. Do not comment on what every file does. Please note that the code should be fully functional. No placeholders. You will start with the "entrypoint" file, then go to the ones that are imported by that file, and so on. Please note that the code should be fully functional. No placeholders. Follow a language and framework appropriate best practice file naming convention. Make sure that files contain all imports, types etc. The code should be fully functional. Make sure that code in different files are compatible with each other. When writing code if you are unsure, write a plausible implementation. Include module dependency or package manager dependency definition file. Useful to know: For Python, you always create an appropriate requirements.txt file. Always implement the simplest implementation possible, and concise code, unless explicitly stated otherwise. Always add a comment briefly describing the purpose of the function definition. Add comments explaining very complex bits of logic. Always follow the best practices for the requested languages for folder/file structure and how to package the project. You can use any package and any other packages you wish to install. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. When writing a test, make the filename start with the prefix 'test_'. When putting files in folders, always be sure to include a file called __init__.py where relevant, or put all files in the same working directory. Always prefer the most simplest approach. Always add a readme on how to run the code, or a .sh file to run the code. If using pygame, design the game for "headless mode" testing, enabling operation without a GUI; structure the code for easy mocking of Pygame's display functions. As you cannot use any human input to test. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Python toolbelt preferences: - pytest - dataclasses - flask - pygame==2.1.2 Objective:``` create a eda app for csv file ``` Understand the problem, by creating an extremely detailed step-by-step plan, where each step is long (multiple sentences) and in total includes every single feature requirement specified above, feel free to copy directly from it. Use no more than 10 steps in the plan. Create additional tests, checks and evaluation at each step when applicable to help make an excellent code implementation, where all the code is fully functional. Use best software design practices, and you can output large amounts of code at once. Please include a last sentence to create and run tests when implementing or writing code in that same step. You will receive no human input at any stage, so you cannot use a human to test. Only create a detailed plan to begin with, which includes designing and running tests to check that they all pass. Add to the last step in the plan to add a readme on how to run the code, or a .sh file to run the code. Please be sure to include all of the specified feature requirements in the following plan. MainProcess| 2024-07-06 19:34:04,115,115 multiprocessing INFO [User] Objective: Execute sub task step:```In the 'app.py' file, set up a basic Flask application. Create a route to upload CSV files and another route to display the EDA results. Ensure the Flask app can start correctly and the routes are accessible. Write tests to verify that the Flask app starts correctly and the routes return the expected responses.```.\n\n Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py']. Fully implement these features in the code, no placeholders. You can now optionally view the existing files if you need to view them to complete the current task step. You have a limited context window so be selective about which files you view, only view the files you think you might need to view. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Do not write tests for large numbers and large inputs, if they exist delete them. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Avoid making complicated tests. If a test repeatedly fails delete the test. \n\nSummary output of previous step: ""The project structure has been successfully set up with a main entry point file `app.py`, a `requirements.txt` file, and an `eda` folder containing an `__init__.py` file. Tests have been written and executed to ensure the project structure is correctly set up, and all tests passed.""\n\nRespond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:04,115,115 multiprocessing INFO [Function Call] [view_files] {"files": ["app.py", "requirements.txt", "eda/__init__.py", "test_project_structure.py"]} MainProcess| 2024-07-06 19:34:04,115,115 multiprocessing INFO [Tool] {"files": "app.py\n```python\nfrom flask import Flask\n\napp = Flask(__name__)\n\n@app.route('/')\ndef home():\n\treturn 'Welcome to the EDA App!'\n\nif __name__ == '__main__':\n\tapp.run(debug=True)\n```\n\nrequirements.txt\n```text\nflask\npytest\n```\n\neda/__init__.py\n```python\n\n```\n\ntest_project_structure.py\n```python\nimport os\nimport pytest\n\n# Test to ensure the project structure is correctly set up\n\ndef test_project_structure():\n\tassert os.path.isfile('app.py'), 'app.py does not exist'\n\tassert os.path.isfile('requirements.txt'), 'requirements.txt does not exist'\n\tassert os.path.isdir('eda'), 'eda directory does not exist'\n\tassert os.path.isfile('eda/__init__.py'), 'eda/__init__.py does not exist'\n\nif __name__ == '__main__':\n\tpytest.main()\n```\n\n"} MainProcess| 2024-07-06 19:34:04,115,115 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'app.py' file, set up a basic Flask application. Create a route to upload CSV files and another route to display the EDA results. Ensure the Flask app can start correctly and the routes are accessible. Write tests to verify that the Flask app starts correctly and the routes return the expected responses.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:04,115,115 multiprocessing INFO [Function Call] [write_files] {"list_of_file_objects":[{"file_path":"app.py","file_contents":"from flask import Flask, request, jsonify\nimport pandas as pd\nimport os\n\napp = Flask(__name__)\nUPLOAD_FOLDER = 'uploads'\nos.makedirs(UPLOAD_FOLDER, exist_ok=True)\napp.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER\n\n@app.route('/')\ndef home():\n\treturn 'Welcome to the EDA App!'\n\n@app.route('/upload', methods=['POST'])\ndef upload_file():\n\tif 'file' not in request.files:\n\t\treturn jsonify({'error': 'No file part'}), 400\n\tfile = request.files['file']\n\tif file.filename == '':\n\t\treturn jsonify({'error': 'No selected file'}), 400\n\tif file and file.filename.endswith('.csv'):\n\t\tfile_path = os.path.join(app.config['UPLOAD_FOLDER'], file.filename)\n\t\tfile.save(file_path)\n\t\treturn jsonify({'message': 'File uploaded successfully', 'file_path': file_path}), 200\n\telse:\n\t\treturn jsonify({'error': 'Invalid file type'}), 400\n\n@app.route('/eda', methods=['GET'])\ndef eda():\n\tfile_path = request.args.get('file_path')\n\tif not file_path or not os.path.exists(file_path):\n\t\treturn jsonify({'error': 'File not found'}), 400\n\ttry:\n\t\tdata = pd.read_csv(file_path)\n\t\tsummary = {\n\t\t\t'columns': list(data.columns),\n\t\t\t'shape': data.shape,\n\t\t\t'describe': data.describe().to_dict()\n\t\t}\n\t\treturn jsonify(summary), 200\n\texcept Exception as e:\n\t\treturn jsonify({'error': str(e)}), 500\n\nif __name__ == '__main__':\n\tapp.run(debug=True)\n"},{"file_path":"test_app.py","file_contents":"import pytest\nfrom app import app\n\n@pytest.fixture\n\ndef client():\n\tapp.config['TESTING'] = True\n\twith app.test_client() as client:\n\t\tyield client\n\n# Test to ensure the Flask app starts correctly and the home route is accessible\n\ndef test_home(client):\n\trv = client.get('/')\n\tassert rv.status_code == 200\n\tassert b'Welcome to the EDA App!' in rv.data\n\n# Test to ensure the upload route works correctly\n\ndef test_upload_file(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tassert rv.status_code == 200\n\tassert b'File uploaded successfully' in rv.data\n\n# Test to ensure the EDA route works correctly\n\ndef test_eda(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tfile_path = rv.json['file_path']\n\trv = client.get(f'/eda?file_path={file_path}')\n\tassert rv.status_code == 200\n\tassert b'columns' in rv.data\n\tassert b'shape' in rv.data\n\tassert b'describe' in rv.data\n"}]} MainProcess| 2024-07-06 19:34:04,115,115 multiprocessing INFO [Tool] {"write_files_status": "success", "message": "write_files completed successfully."} MainProcess| 2024-07-06 19:34:04,115,115 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'app.py' file, set up a basic Flask application. Create a route to upload CSV files and another route to display the EDA results. Ensure the Flask app can start correctly and the routes are accessible. Write tests to verify that the Flask app starts correctly and the routes return the expected responses.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:04,115,115 multiprocessing INFO [Function Call] [pytest_files] {"files_to_test":["test_app.py"]} MainProcess| 2024-07-06 19:34:04,115,115 multiprocessing INFO [Tool] {"output": "Manual tests passed."} MainProcess| 2024-07-06 19:34:04,115,115 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'app.py' file, set up a basic Flask application. Create a route to upload CSV files and another route to display the EDA results. Ensure the Flask app can start correctly and the routes are accessible. Write tests to verify that the Flask app starts correctly and the routes return the expected responses.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:04,115,115 multiprocessing INFO [Progress: Step 2/10 | Retries: 0/30 | Token Capacity Used: 47.41% | Tokens remaining 4308] MainProcess| 2024-07-06 19:34:05,336,336 multiprocessing INFO [LLM RESPONSE MESSAGE] MainProcess| 2024-07-06 19:34:05,336,336 multiprocessing INFO [Function Call] [sub_task_step_complete] {} MainProcess| 2024-07-06 19:34:05,340,340 multiprocessing INFO [System] Objective: Write code for a large system design task. Please note that the code should be fully functional. No placeholders. Only use the functions you have been provided with. Only use the `write_files` to output code. You must act autonomously and you will receive no human input at any stage. You have to return as output the complete code for completing this task, and correctly incorporate it into the existing code base. You always write out the whole file contents. You always indent code with tabs. Please always view the files before writing to them, to make sure you are writing to the correct files. When writing a test, make the filename start with the prefix 'test_'. Provide the minimal code necessary to achieve the task conditioned on the existing generated code---including changing the existing generated code. You cannot visualize any graphical output. You exist within a Actor Model machine, and when you list out steps, each step will be taken by a new separate sub-ChatGPT model. When you list out a sub-task steps, you can optionally specify the sub-task validation to check that it has been completed successfully. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Use the functions provided. When calling functions only provide a RFC8259 compliant JSON request following this format without deviation. MainProcess| 2024-07-06 19:34:05,340,340 multiprocessing INFO [User] You will get instructions for code to write. First lay out the names of the core classes, functions, methods that will be necessary, As well as a quick comment on their purpose. Do not comment on what every file does. Please note that the code should be fully functional. No placeholders. You will start with the "entrypoint" file, then go to the ones that are imported by that file, and so on. Please note that the code should be fully functional. No placeholders. Follow a language and framework appropriate best practice file naming convention. Make sure that files contain all imports, types etc. The code should be fully functional. Make sure that code in different files are compatible with each other. When writing code if you are unsure, write a plausible implementation. Include module dependency or package manager dependency definition file. Useful to know: For Python, you always create an appropriate requirements.txt file. Always implement the simplest implementation possible, and concise code, unless explicitly stated otherwise. Always add a comment briefly describing the purpose of the function definition. Add comments explaining very complex bits of logic. Always follow the best practices for the requested languages for folder/file structure and how to package the project. You can use any package and any other packages you wish to install. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. When writing a test, make the filename start with the prefix 'test_'. When putting files in folders, always be sure to include a file called __init__.py where relevant, or put all files in the same working directory. Always prefer the most simplest approach. Always add a readme on how to run the code, or a .sh file to run the code. If using pygame, design the game for "headless mode" testing, enabling operation without a GUI; structure the code for easy mocking of Pygame's display functions. As you cannot use any human input to test. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Python toolbelt preferences: - pytest - dataclasses - flask - pygame==2.1.2 Objective:``` create a eda app for csv file ``` Understand the problem, by creating an extremely detailed step-by-step plan, where each step is long (multiple sentences) and in total includes every single feature requirement specified above, feel free to copy directly from it. Use no more than 10 steps in the plan. Create additional tests, checks and evaluation at each step when applicable to help make an excellent code implementation, where all the code is fully functional. Use best software design practices, and you can output large amounts of code at once. Please include a last sentence to create and run tests when implementing or writing code in that same step. You will receive no human input at any stage, so you cannot use a human to test. Only create a detailed plan to begin with, which includes designing and running tests to check that they all pass. Add to the last step in the plan to add a readme on how to run the code, or a .sh file to run the code. Please be sure to include all of the specified feature requirements in the following plan. MainProcess| 2024-07-06 19:34:05,340,340 multiprocessing INFO [User] Objective: Execute sub task step:```In the 'app.py' file, set up a basic Flask application. Create a route to upload CSV files and another route to display the EDA results. Ensure the Flask app can start correctly and the routes are accessible. Write tests to verify that the Flask app starts correctly and the routes return the expected responses.```.\n\n Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py']. Fully implement these features in the code, no placeholders. You can now optionally view the existing files if you need to view them to complete the current task step. You have a limited context window so be selective about which files you view, only view the files you think you might need to view. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Do not write tests for large numbers and large inputs, if they exist delete them. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Avoid making complicated tests. If a test repeatedly fails delete the test. \n\nSummary output of previous step: ""The project structure has been successfully set up with a main entry point file `app.py`, a `requirements.txt` file, and an `eda` folder containing an `__init__.py` file. Tests have been written and executed to ensure the project structure is correctly set up, and all tests passed.""\n\nRespond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:05,341,341 multiprocessing INFO [Function Call] [view_files] {"files": ["app.py", "requirements.txt", "eda/__init__.py", "test_project_structure.py"]} MainProcess| 2024-07-06 19:34:05,341,341 multiprocessing INFO [Tool] {"files": "app.py\n```python\nfrom flask import Flask\n\napp = Flask(__name__)\n\n@app.route('/')\ndef home():\n\treturn 'Welcome to the EDA App!'\n\nif __name__ == '__main__':\n\tapp.run(debug=True)\n```\n\nrequirements.txt\n```text\nflask\npytest\n```\n\neda/__init__.py\n```python\n\n```\n\ntest_project_structure.py\n```python\nimport os\nimport pytest\n\n# Test to ensure the project structure is correctly set up\n\ndef test_project_structure():\n\tassert os.path.isfile('app.py'), 'app.py does not exist'\n\tassert os.path.isfile('requirements.txt'), 'requirements.txt does not exist'\n\tassert os.path.isdir('eda'), 'eda directory does not exist'\n\tassert os.path.isfile('eda/__init__.py'), 'eda/__init__.py does not exist'\n\nif __name__ == '__main__':\n\tpytest.main()\n```\n\n"} MainProcess| 2024-07-06 19:34:05,341,341 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'app.py' file, set up a basic Flask application. Create a route to upload CSV files and another route to display the EDA results. Ensure the Flask app can start correctly and the routes are accessible. Write tests to verify that the Flask app starts correctly and the routes return the expected responses.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:05,341,341 multiprocessing INFO [Function Call] [write_files] {"list_of_file_objects":[{"file_path":"app.py","file_contents":"from flask import Flask, request, jsonify\nimport pandas as pd\nimport os\n\napp = Flask(__name__)\nUPLOAD_FOLDER = 'uploads'\nos.makedirs(UPLOAD_FOLDER, exist_ok=True)\napp.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER\n\n@app.route('/')\ndef home():\n\treturn 'Welcome to the EDA App!'\n\n@app.route('/upload', methods=['POST'])\ndef upload_file():\n\tif 'file' not in request.files:\n\t\treturn jsonify({'error': 'No file part'}), 400\n\tfile = request.files['file']\n\tif file.filename == '':\n\t\treturn jsonify({'error': 'No selected file'}), 400\n\tif file and file.filename.endswith('.csv'):\n\t\tfile_path = os.path.join(app.config['UPLOAD_FOLDER'], file.filename)\n\t\tfile.save(file_path)\n\t\treturn jsonify({'message': 'File uploaded successfully', 'file_path': file_path}), 200\n\telse:\n\t\treturn jsonify({'error': 'Invalid file type'}), 400\n\n@app.route('/eda', methods=['GET'])\ndef eda():\n\tfile_path = request.args.get('file_path')\n\tif not file_path or not os.path.exists(file_path):\n\t\treturn jsonify({'error': 'File not found'}), 400\n\ttry:\n\t\tdata = pd.read_csv(file_path)\n\t\tsummary = {\n\t\t\t'columns': list(data.columns),\n\t\t\t'shape': data.shape,\n\t\t\t'describe': data.describe().to_dict()\n\t\t}\n\t\treturn jsonify(summary), 200\n\texcept Exception as e:\n\t\treturn jsonify({'error': str(e)}), 500\n\nif __name__ == '__main__':\n\tapp.run(debug=True)\n"},{"file_path":"test_app.py","file_contents":"import pytest\nfrom app import app\n\n@pytest.fixture\n\ndef client():\n\tapp.config['TESTING'] = True\n\twith app.test_client() as client:\n\t\tyield client\n\n# Test to ensure the Flask app starts correctly and the home route is accessible\n\ndef test_home(client):\n\trv = client.get('/')\n\tassert rv.status_code == 200\n\tassert b'Welcome to the EDA App!' in rv.data\n\n# Test to ensure the upload route works correctly\n\ndef test_upload_file(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tassert rv.status_code == 200\n\tassert b'File uploaded successfully' in rv.data\n\n# Test to ensure the EDA route works correctly\n\ndef test_eda(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tfile_path = rv.json['file_path']\n\trv = client.get(f'/eda?file_path={file_path}')\n\tassert rv.status_code == 200\n\tassert b'columns' in rv.data\n\tassert b'shape' in rv.data\n\tassert b'describe' in rv.data\n"}]} MainProcess| 2024-07-06 19:34:05,341,341 multiprocessing INFO [Tool] {"write_files_status": "success", "message": "write_files completed successfully."} MainProcess| 2024-07-06 19:34:05,341,341 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'app.py' file, set up a basic Flask application. Create a route to upload CSV files and another route to display the EDA results. Ensure the Flask app can start correctly and the routes are accessible. Write tests to verify that the Flask app starts correctly and the routes return the expected responses.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:05,341,341 multiprocessing INFO [Function Call] [pytest_files] {"files_to_test":["test_app.py"]} MainProcess| 2024-07-06 19:34:05,341,341 multiprocessing INFO [Tool] {"output": "Manual tests passed."} MainProcess| 2024-07-06 19:34:05,341,341 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'app.py' file, set up a basic Flask application. Create a route to upload CSV files and another route to display the EDA results. Ensure the Flask app can start correctly and the routes are accessible. Write tests to verify that the Flask app starts correctly and the routes return the expected responses.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:05,341,341 multiprocessing INFO [Function Call] [sub_task_step_complete] {} MainProcess| 2024-07-06 19:34:05,342,342 multiprocessing INFO [Tool] {"status": "TASK_STEP_COMPLETE", "message": "All tests passed"} MainProcess| 2024-07-06 19:34:05,342,342 multiprocessing INFO [User] Please provide a one or two sentence summary of the output of this step, which is useful for the next step. Your response will be used when starting the next step without any of the previous messages. MainProcess| 2024-07-06 19:34:05,342,342 multiprocessing INFO [Progress: Step 2/10 | Retries: 0/30 | Token Capacity Used: 49.11% | Tokens remaining 4169] MainProcess| 2024-07-06 19:34:06,960,960 multiprocessing INFO [LLM RESPONSE MESSAGE] MainProcess| 2024-07-06 19:34:06,960,960 multiprocessing INFO [Assistant] The Flask application has been set up with routes to upload CSV files and display EDA results. Tests have been written and executed to verify that the Flask app starts correctly and the routes return the expected responses, and all tests passed successfully. MainProcess| 2024-07-06 19:34:06,960,960 multiprocessing INFO [STEP COMPLETE] sub step completed MainProcess| 2024-07-06 19:34:06,961,961 multiprocessing INFO [System] Objective: Write code for a large system design task. Please note that the code should be fully functional. No placeholders. Only use the functions you have been provided with. Only use the `write_files` to output code. You must act autonomously and you will receive no human input at any stage. You have to return as output the complete code for completing this task, and correctly incorporate it into the existing code base. You always write out the whole file contents. You always indent code with tabs. Please always view the files before writing to them, to make sure you are writing to the correct files. When writing a test, make the filename start with the prefix 'test_'. Provide the minimal code necessary to achieve the task conditioned on the existing generated code---including changing the existing generated code. You cannot visualize any graphical output. You exist within a Actor Model machine, and when you list out steps, each step will be taken by a new separate sub-ChatGPT model. When you list out a sub-task steps, you can optionally specify the sub-task validation to check that it has been completed successfully. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Use the functions provided. When calling functions only provide a RFC8259 compliant JSON request following this format without deviation. MainProcess| 2024-07-06 19:34:06,961,961 multiprocessing INFO [User] You will get instructions for code to write. First lay out the names of the core classes, functions, methods that will be necessary, As well as a quick comment on their purpose. Do not comment on what every file does. Please note that the code should be fully functional. No placeholders. You will start with the "entrypoint" file, then go to the ones that are imported by that file, and so on. Please note that the code should be fully functional. No placeholders. Follow a language and framework appropriate best practice file naming convention. Make sure that files contain all imports, types etc. The code should be fully functional. Make sure that code in different files are compatible with each other. When writing code if you are unsure, write a plausible implementation. Include module dependency or package manager dependency definition file. Useful to know: For Python, you always create an appropriate requirements.txt file. Always implement the simplest implementation possible, and concise code, unless explicitly stated otherwise. Always add a comment briefly describing the purpose of the function definition. Add comments explaining very complex bits of logic. Always follow the best practices for the requested languages for folder/file structure and how to package the project. You can use any package and any other packages you wish to install. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. When writing a test, make the filename start with the prefix 'test_'. When putting files in folders, always be sure to include a file called __init__.py where relevant, or put all files in the same working directory. Always prefer the most simplest approach. Always add a readme on how to run the code, or a .sh file to run the code. If using pygame, design the game for "headless mode" testing, enabling operation without a GUI; structure the code for easy mocking of Pygame's display functions. As you cannot use any human input to test. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Python toolbelt preferences: - pytest - dataclasses - flask - pygame==2.1.2 Objective:``` create a eda app for csv file ``` Understand the problem, by creating an extremely detailed step-by-step plan, where each step is long (multiple sentences) and in total includes every single feature requirement specified above, feel free to copy directly from it. Use no more than 10 steps in the plan. Create additional tests, checks and evaluation at each step when applicable to help make an excellent code implementation, where all the code is fully functional. Use best software design practices, and you can output large amounts of code at once. Please include a last sentence to create and run tests when implementing or writing code in that same step. You will receive no human input at any stage, so you cannot use a human to test. Only create a detailed plan to begin with, which includes designing and running tests to check that they all pass. Add to the last step in the plan to add a readme on how to run the code, or a .sh file to run the code. Please be sure to include all of the specified feature requirements in the following plan. MainProcess| 2024-07-06 19:34:06,961,961 multiprocessing INFO [User] Objective: Execute sub task step:```In the 'eda' folder, create a file named 'eda.py'. This file will contain the core logic for performing EDA on the uploaded CSV files. Define a function 'perform_eda' that takes a CSV file as input and returns a summary of the data, including basic statistics and visualizations. Write tests to ensure the 'perform_eda' function works correctly with sample CSV files.```.\n\n Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py']. Fully implement these features in the code, no placeholders. You can now optionally view the existing files if you need to view them to complete the current task step. You have a limited context window so be selective about which files you view, only view the files you think you might need to view. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Do not write tests for large numbers and large inputs, if they exist delete them. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Avoid making complicated tests. If a test repeatedly fails delete the test. \n\nSummary output of previous step: ""The Flask application has been set up with routes to upload CSV files and display EDA results. Tests have been written and executed to verify that the Flask app starts correctly and the routes return the expected responses, and all tests passed successfully.""\n\nRespond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:06,961,961 multiprocessing INFO [Progress: Step 3/10 | Retries: 0/30 | Token Capacity Used: 21.58% | Tokens remaining 6424] MainProcess| 2024-07-06 19:34:08,257,257 multiprocessing INFO [LLM RESPONSE MESSAGE] MainProcess| 2024-07-06 19:34:08,258,258 multiprocessing INFO [Function Call] [view_files] {"files":["app.py","requirements.txt","eda/__init__.py","test_project_structure.py","test_app.py"]} MainProcess| 2024-07-06 19:34:08,261,261 multiprocessing INFO [System] Objective: Write code for a large system design task. Please note that the code should be fully functional. No placeholders. Only use the functions you have been provided with. Only use the `write_files` to output code. You must act autonomously and you will receive no human input at any stage. You have to return as output the complete code for completing this task, and correctly incorporate it into the existing code base. You always write out the whole file contents. You always indent code with tabs. Please always view the files before writing to them, to make sure you are writing to the correct files. When writing a test, make the filename start with the prefix 'test_'. Provide the minimal code necessary to achieve the task conditioned on the existing generated code---including changing the existing generated code. You cannot visualize any graphical output. You exist within a Actor Model machine, and when you list out steps, each step will be taken by a new separate sub-ChatGPT model. When you list out a sub-task steps, you can optionally specify the sub-task validation to check that it has been completed successfully. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Use the functions provided. When calling functions only provide a RFC8259 compliant JSON request following this format without deviation. MainProcess| 2024-07-06 19:34:08,261,261 multiprocessing INFO [User] You will get instructions for code to write. First lay out the names of the core classes, functions, methods that will be necessary, As well as a quick comment on their purpose. Do not comment on what every file does. Please note that the code should be fully functional. No placeholders. You will start with the "entrypoint" file, then go to the ones that are imported by that file, and so on. Please note that the code should be fully functional. No placeholders. Follow a language and framework appropriate best practice file naming convention. Make sure that files contain all imports, types etc. The code should be fully functional. Make sure that code in different files are compatible with each other. When writing code if you are unsure, write a plausible implementation. Include module dependency or package manager dependency definition file. Useful to know: For Python, you always create an appropriate requirements.txt file. Always implement the simplest implementation possible, and concise code, unless explicitly stated otherwise. Always add a comment briefly describing the purpose of the function definition. Add comments explaining very complex bits of logic. Always follow the best practices for the requested languages for folder/file structure and how to package the project. You can use any package and any other packages you wish to install. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. When writing a test, make the filename start with the prefix 'test_'. When putting files in folders, always be sure to include a file called __init__.py where relevant, or put all files in the same working directory. Always prefer the most simplest approach. Always add a readme on how to run the code, or a .sh file to run the code. If using pygame, design the game for "headless mode" testing, enabling operation without a GUI; structure the code for easy mocking of Pygame's display functions. As you cannot use any human input to test. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Python toolbelt preferences: - pytest - dataclasses - flask - pygame==2.1.2 Objective:``` create a eda app for csv file ``` Understand the problem, by creating an extremely detailed step-by-step plan, where each step is long (multiple sentences) and in total includes every single feature requirement specified above, feel free to copy directly from it. Use no more than 10 steps in the plan. Create additional tests, checks and evaluation at each step when applicable to help make an excellent code implementation, where all the code is fully functional. Use best software design practices, and you can output large amounts of code at once. Please include a last sentence to create and run tests when implementing or writing code in that same step. You will receive no human input at any stage, so you cannot use a human to test. Only create a detailed plan to begin with, which includes designing and running tests to check that they all pass. Add to the last step in the plan to add a readme on how to run the code, or a .sh file to run the code. Please be sure to include all of the specified feature requirements in the following plan. MainProcess| 2024-07-06 19:34:08,261,261 multiprocessing INFO [User] Objective: Execute sub task step:```In the 'eda' folder, create a file named 'eda.py'. This file will contain the core logic for performing EDA on the uploaded CSV files. Define a function 'perform_eda' that takes a CSV file as input and returns a summary of the data, including basic statistics and visualizations. Write tests to ensure the 'perform_eda' function works correctly with sample CSV files.```.\n\n Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py']. Fully implement these features in the code, no placeholders. You can now optionally view the existing files if you need to view them to complete the current task step. You have a limited context window so be selective about which files you view, only view the files you think you might need to view. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Do not write tests for large numbers and large inputs, if they exist delete them. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Avoid making complicated tests. If a test repeatedly fails delete the test. \n\nSummary output of previous step: ""The Flask application has been set up with routes to upload CSV files and display EDA results. Tests have been written and executed to verify that the Flask app starts correctly and the routes return the expected responses, and all tests passed successfully.""\n\nRespond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:08,261,261 multiprocessing INFO [Function Call] [view_files] {"files":["app.py","requirements.txt","eda/__init__.py","test_project_structure.py","test_app.py"]} MainProcess| 2024-07-06 19:34:08,261,261 multiprocessing INFO [Tool] {"files": "app.py\n```python\nfrom flask import Flask, request, jsonify\nimport pandas as pd\nimport os\n\napp = Flask(__name__)\nUPLOAD_FOLDER = 'uploads'\nos.makedirs(UPLOAD_FOLDER, exist_ok=True)\napp.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER\n\n@app.route('/')\ndef home():\n\treturn 'Welcome to the EDA App!'\n\n@app.route('/upload', methods=['POST'])\ndef upload_file():\n\tif 'file' not in request.files:\n\t\treturn jsonify({'error': 'No file part'}), 400\n\tfile = request.files['file']\n\tif file.filename == '':\n\t\treturn jsonify({'error': 'No selected file'}), 400\n\tif file and file.filename.endswith('.csv'):\n\t\tfile_path = os.path.join(app.config['UPLOAD_FOLDER'], file.filename)\n\t\tfile.save(file_path)\n\t\treturn jsonify({'message': 'File uploaded successfully', 'file_path': file_path}), 200\n\telse:\n\t\treturn jsonify({'error': 'Invalid file type'}), 400\n\n@app.route('/eda', methods=['GET'])\ndef eda():\n\tfile_path = request.args.get('file_path')\n\tif not file_path or not os.path.exists(file_path):\n\t\treturn jsonify({'error': 'File not found'}), 400\n\ttry:\n\t\tdata = pd.read_csv(file_path)\n\t\tsummary = {\n\t\t\t'columns': list(data.columns),\n\t\t\t'shape': data.shape,\n\t\t\t'describe': data.describe().to_dict()\n\t\t}\n\t\treturn jsonify(summary), 200\n\texcept Exception as e:\n\t\treturn jsonify({'error': str(e)}), 500\n\nif __name__ == '__main__':\n\tapp.run(debug=True)\n\n```\n\nrequirements.txt\n```text\nflask\npytest\n```\n\neda/__init__.py\n```python\n\n```\n\ntest_project_structure.py\n```python\nimport os\nimport pytest\n\n# Test to ensure the project structure is correctly set up\n\ndef test_project_structure():\n\tassert os.path.isfile('app.py'), 'app.py does not exist'\n\tassert os.path.isfile('requirements.txt'), 'requirements.txt does not exist'\n\tassert os.path.isdir('eda'), 'eda directory does not exist'\n\tassert os.path.isfile('eda/__init__.py'), 'eda/__init__.py does not exist'\n\nif __name__ == '__main__':\n\tpytest.main()\n```\n\ntest_app.py\n```python\nimport pytest\nfrom app import app\n\n@pytest.fixture\n\ndef client():\n\tapp.config['TESTING'] = True\n\twith app.test_client() as client:\n\t\tyield client\n\n# Test to ensure the Flask app starts correctly and the home route is accessible\n\ndef test_home(client):\n\trv = client.get('/')\n\tassert rv.status_code == 200\n\tassert b'Welcome to the EDA App!' in rv.data\n\n# Test to ensure the upload route works correctly\n\ndef test_upload_file(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tassert rv.status_code == 200\n\tassert b'File uploaded successfully' in rv.data\n\n# Test to ensure the EDA route works correctly\n\ndef test_eda(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tfile_path = rv.json['file_path']\n\trv = client.get(f'/eda?file_path={file_path}')\n\tassert rv.status_code == 200\n\tassert b'columns' in rv.data\n\tassert b'shape' in rv.data\n\tassert b'describe' in rv.data\n\n```\n\n"} MainProcess| 2024-07-06 19:34:08,261,261 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'eda' folder, create a file named 'eda.py'. This file will contain the core logic for performing EDA on the uploaded CSV files. Define a function 'perform_eda' that takes a CSV file as input and returns a summary of the data, including basic statistics and visualizations. Write tests to ensure the 'perform_eda' function works correctly with sample CSV files.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:08,261,261 multiprocessing INFO [Progress: Step 3/10 | Retries: 0/30 | Token Capacity Used: 37.32% | Tokens remaining 5135] MainProcess| 2024-07-06 19:34:14,370,370 multiprocessing INFO [LLM RESPONSE MESSAGE] MainProcess| 2024-07-06 19:34:14,370,370 multiprocessing INFO [Function Call] [write_files] {"list_of_file_objects":[{"file_path":"eda/eda.py","file_contents":"import pandas as pd\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nfrom io import BytesIO\nimport base64\n\n# Function to perform EDA on a CSV file\ndef perform_eda(file_path):\n\tdata = pd.read_csv(file_path)\n\tsummary = {\n\t\t'columns': list(data.columns),\n\t\t'shape': data.shape,\n\t\t'describe': data.describe().to_dict(),\n\t\t'null_values': data.isnull().sum().to_dict(),\n\t\t'head': data.head().to_dict()\n\t}\n\n\t# Generate visualizations\n\tvisualizations = {}\n\n\t# Correlation heatmap\n\tplt.figure(figsize=(10, 8))\n\tsns.heatmap(data.corr(), annot=True, cmap='coolwarm')\n\tbuf = BytesIO()\n\tplt.savefig(buf, format='png')\n\tbuf.seek(0)\n\timage_base64 = base64.b64encode(buf.read()).decode('utf-8')\n\tvisualizations['correlation_heatmap'] = image_base64\n\tbuf.close()\n\tplt.close()\n\n\t# Pairplot\n\tplt.figure(figsize=(10, 8))\n\tsns.pairplot(data)\n\tbuf = BytesIO()\n\tplt.savefig(buf, format='png')\n\tbuf.seek(0)\n\timage_base64 = base64.b64encode(buf.read()).decode('utf-8')\n\tvisualizations['pairplot'] = image_base64\n\tbuf.close()\n\tplt.close()\n\n\tsummary['visualizations'] = visualizations\n\n\treturn summary\n\n# Test the perform_eda function\nif __name__ == \"__main__\":\n\t# Sample CSV data\n\tcsv_data = \"\"\"col1,col2,col3\\n1,2,3\\n4,5,6\\n7,8,9\\n10,11,12\\n\"\"\"\n\tfile_path = 'sample.csv'\n\twith open(file_path, 'w') as f:\n\t\tf.write(csv_data)\n\n\tsummary = perform_eda(file_path)\n\tprint(summary)\n"}]} MainProcess| 2024-07-06 19:34:14,374,374 multiprocessing INFO [System] Objective: Write code for a large system design task. Please note that the code should be fully functional. No placeholders. Only use the functions you have been provided with. Only use the `write_files` to output code. You must act autonomously and you will receive no human input at any stage. You have to return as output the complete code for completing this task, and correctly incorporate it into the existing code base. You always write out the whole file contents. You always indent code with tabs. Please always view the files before writing to them, to make sure you are writing to the correct files. When writing a test, make the filename start with the prefix 'test_'. Provide the minimal code necessary to achieve the task conditioned on the existing generated code---including changing the existing generated code. You cannot visualize any graphical output. You exist within a Actor Model machine, and when you list out steps, each step will be taken by a new separate sub-ChatGPT model. When you list out a sub-task steps, you can optionally specify the sub-task validation to check that it has been completed successfully. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Use the functions provided. When calling functions only provide a RFC8259 compliant JSON request following this format without deviation. MainProcess| 2024-07-06 19:34:14,374,374 multiprocessing INFO [User] You will get instructions for code to write. First lay out the names of the core classes, functions, methods that will be necessary, As well as a quick comment on their purpose. Do not comment on what every file does. Please note that the code should be fully functional. No placeholders. You will start with the "entrypoint" file, then go to the ones that are imported by that file, and so on. Please note that the code should be fully functional. No placeholders. Follow a language and framework appropriate best practice file naming convention. Make sure that files contain all imports, types etc. The code should be fully functional. Make sure that code in different files are compatible with each other. When writing code if you are unsure, write a plausible implementation. Include module dependency or package manager dependency definition file. Useful to know: For Python, you always create an appropriate requirements.txt file. Always implement the simplest implementation possible, and concise code, unless explicitly stated otherwise. Always add a comment briefly describing the purpose of the function definition. Add comments explaining very complex bits of logic. Always follow the best practices for the requested languages for folder/file structure and how to package the project. You can use any package and any other packages you wish to install. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. When writing a test, make the filename start with the prefix 'test_'. When putting files in folders, always be sure to include a file called __init__.py where relevant, or put all files in the same working directory. Always prefer the most simplest approach. Always add a readme on how to run the code, or a .sh file to run the code. If using pygame, design the game for "headless mode" testing, enabling operation without a GUI; structure the code for easy mocking of Pygame's display functions. As you cannot use any human input to test. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Python toolbelt preferences: - pytest - dataclasses - flask - pygame==2.1.2 Objective:``` create a eda app for csv file ``` Understand the problem, by creating an extremely detailed step-by-step plan, where each step is long (multiple sentences) and in total includes every single feature requirement specified above, feel free to copy directly from it. Use no more than 10 steps in the plan. Create additional tests, checks and evaluation at each step when applicable to help make an excellent code implementation, where all the code is fully functional. Use best software design practices, and you can output large amounts of code at once. Please include a last sentence to create and run tests when implementing or writing code in that same step. You will receive no human input at any stage, so you cannot use a human to test. Only create a detailed plan to begin with, which includes designing and running tests to check that they all pass. Add to the last step in the plan to add a readme on how to run the code, or a .sh file to run the code. Please be sure to include all of the specified feature requirements in the following plan. MainProcess| 2024-07-06 19:34:14,374,374 multiprocessing INFO [User] Objective: Execute sub task step:```In the 'eda' folder, create a file named 'eda.py'. This file will contain the core logic for performing EDA on the uploaded CSV files. Define a function 'perform_eda' that takes a CSV file as input and returns a summary of the data, including basic statistics and visualizations. Write tests to ensure the 'perform_eda' function works correctly with sample CSV files.```.\n\n Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py']. Fully implement these features in the code, no placeholders. You can now optionally view the existing files if you need to view them to complete the current task step. You have a limited context window so be selective about which files you view, only view the files you think you might need to view. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Do not write tests for large numbers and large inputs, if they exist delete them. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Avoid making complicated tests. If a test repeatedly fails delete the test. \n\nSummary output of previous step: ""The Flask application has been set up with routes to upload CSV files and display EDA results. Tests have been written and executed to verify that the Flask app starts correctly and the routes return the expected responses, and all tests passed successfully.""\n\nRespond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:14,374,374 multiprocessing INFO [Function Call] [view_files] {"files":["app.py","requirements.txt","eda/__init__.py","test_project_structure.py","test_app.py"]} MainProcess| 2024-07-06 19:34:14,374,374 multiprocessing INFO [Tool] {"files": "app.py\n```python\nfrom flask import Flask, request, jsonify\nimport pandas as pd\nimport os\n\napp = Flask(__name__)\nUPLOAD_FOLDER = 'uploads'\nos.makedirs(UPLOAD_FOLDER, exist_ok=True)\napp.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER\n\n@app.route('/')\ndef home():\n\treturn 'Welcome to the EDA App!'\n\n@app.route('/upload', methods=['POST'])\ndef upload_file():\n\tif 'file' not in request.files:\n\t\treturn jsonify({'error': 'No file part'}), 400\n\tfile = request.files['file']\n\tif file.filename == '':\n\t\treturn jsonify({'error': 'No selected file'}), 400\n\tif file and file.filename.endswith('.csv'):\n\t\tfile_path = os.path.join(app.config['UPLOAD_FOLDER'], file.filename)\n\t\tfile.save(file_path)\n\t\treturn jsonify({'message': 'File uploaded successfully', 'file_path': file_path}), 200\n\telse:\n\t\treturn jsonify({'error': 'Invalid file type'}), 400\n\n@app.route('/eda', methods=['GET'])\ndef eda():\n\tfile_path = request.args.get('file_path')\n\tif not file_path or not os.path.exists(file_path):\n\t\treturn jsonify({'error': 'File not found'}), 400\n\ttry:\n\t\tdata = pd.read_csv(file_path)\n\t\tsummary = {\n\t\t\t'columns': list(data.columns),\n\t\t\t'shape': data.shape,\n\t\t\t'describe': data.describe().to_dict()\n\t\t}\n\t\treturn jsonify(summary), 200\n\texcept Exception as e:\n\t\treturn jsonify({'error': str(e)}), 500\n\nif __name__ == '__main__':\n\tapp.run(debug=True)\n\n```\n\nrequirements.txt\n```text\nflask\npytest\n```\n\neda/__init__.py\n```python\n\n```\n\ntest_project_structure.py\n```python\nimport os\nimport pytest\n\n# Test to ensure the project structure is correctly set up\n\ndef test_project_structure():\n\tassert os.path.isfile('app.py'), 'app.py does not exist'\n\tassert os.path.isfile('requirements.txt'), 'requirements.txt does not exist'\n\tassert os.path.isdir('eda'), 'eda directory does not exist'\n\tassert os.path.isfile('eda/__init__.py'), 'eda/__init__.py does not exist'\n\nif __name__ == '__main__':\n\tpytest.main()\n```\n\ntest_app.py\n```python\nimport pytest\nfrom app import app\n\n@pytest.fixture\n\ndef client():\n\tapp.config['TESTING'] = True\n\twith app.test_client() as client:\n\t\tyield client\n\n# Test to ensure the Flask app starts correctly and the home route is accessible\n\ndef test_home(client):\n\trv = client.get('/')\n\tassert rv.status_code == 200\n\tassert b'Welcome to the EDA App!' in rv.data\n\n# Test to ensure the upload route works correctly\n\ndef test_upload_file(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tassert rv.status_code == 200\n\tassert b'File uploaded successfully' in rv.data\n\n# Test to ensure the EDA route works correctly\n\ndef test_eda(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tfile_path = rv.json['file_path']\n\trv = client.get(f'/eda?file_path={file_path}')\n\tassert rv.status_code == 200\n\tassert b'columns' in rv.data\n\tassert b'shape' in rv.data\n\tassert b'describe' in rv.data\n\n```\n\n"} MainProcess| 2024-07-06 19:34:14,375,375 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'eda' folder, create a file named 'eda.py'. This file will contain the core logic for performing EDA on the uploaded CSV files. Define a function 'perform_eda' that takes a CSV file as input and returns a summary of the data, including basic statistics and visualizations. Write tests to ensure the 'perform_eda' function works correctly with sample CSV files.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:14,375,375 multiprocessing INFO [Function Call] [write_files] {"list_of_file_objects":[{"file_path":"eda/eda.py","file_contents":"import pandas as pd\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nfrom io import BytesIO\nimport base64\n\n# Function to perform EDA on a CSV file\ndef perform_eda(file_path):\n\tdata = pd.read_csv(file_path)\n\tsummary = {\n\t\t'columns': list(data.columns),\n\t\t'shape': data.shape,\n\t\t'describe': data.describe().to_dict(),\n\t\t'null_values': data.isnull().sum().to_dict(),\n\t\t'head': data.head().to_dict()\n\t}\n\n\t# Generate visualizations\n\tvisualizations = {}\n\n\t# Correlation heatmap\n\tplt.figure(figsize=(10, 8))\n\tsns.heatmap(data.corr(), annot=True, cmap='coolwarm')\n\tbuf = BytesIO()\n\tplt.savefig(buf, format='png')\n\tbuf.seek(0)\n\timage_base64 = base64.b64encode(buf.read()).decode('utf-8')\n\tvisualizations['correlation_heatmap'] = image_base64\n\tbuf.close()\n\tplt.close()\n\n\t# Pairplot\n\tplt.figure(figsize=(10, 8))\n\tsns.pairplot(data)\n\tbuf = BytesIO()\n\tplt.savefig(buf, format='png')\n\tbuf.seek(0)\n\timage_base64 = base64.b64encode(buf.read()).decode('utf-8')\n\tvisualizations['pairplot'] = image_base64\n\tbuf.close()\n\tplt.close()\n\n\tsummary['visualizations'] = visualizations\n\n\treturn summary\n\n# Test the perform_eda function\nif __name__ == \"__main__\":\n\t# Sample CSV data\n\tcsv_data = \"\"\"col1,col2,col3\\n1,2,3\\n4,5,6\\n7,8,9\\n10,11,12\\n\"\"\"\n\tfile_path = 'sample.csv'\n\twith open(file_path, 'w') as f:\n\t\tf.write(csv_data)\n\n\tsummary = perform_eda(file_path)\n\tprint(summary)\n"}]} MainProcess| 2024-07-06 19:34:14,375,375 multiprocessing INFO [Tool] {"write_files_status": "success", "message": "write_files completed successfully."} MainProcess| 2024-07-06 19:34:14,375,375 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'eda' folder, create a file named 'eda.py'. This file will contain the core logic for performing EDA on the uploaded CSV files. Define a function 'perform_eda' that takes a CSV file as input and returns a summary of the data, including basic statistics and visualizations. Write tests to ensure the 'perform_eda' function works correctly with sample CSV files.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:14,375,375 multiprocessing INFO [Progress: Step 3/10 | Retries: 0/30 | Token Capacity Used: 48.73% | Tokens remaining 4200] MainProcess| 2024-07-06 19:34:17,788,788 multiprocessing INFO [LLM RESPONSE MESSAGE] MainProcess| 2024-07-06 19:34:17,788,788 multiprocessing INFO [Function Call] [write_files] {"list_of_file_objects":[{"file_path":"test_eda.py","file_contents":"import pytest\nfrom eda.eda import perform_eda\nimport os\nimport pandas as pd\n\n# Test the perform_eda function with a sample CSV file\ndef test_perform_eda():\n\t# Sample CSV data\n\tcsv_data = \"\"\"col1,col2,col3\\n1,2,3\\n4,5,6\\n7,8,9\\n10,11,12\\n\"\"\"\n\tfile_path = 'test_sample.csv'\n\twith open(file_path, 'w') as f:\n\t\tf.write(csv_data)\n\n\tsummary = perform_eda(file_path)\n\n\tassert 'columns' in summary\n\tassert 'shape' in summary\n\tassert 'describe' in summary\n\tassert 'null_values' in summary\n\tassert 'head' in summary\n\tassert 'visualizations' in summary\n\tassert 'correlation_heatmap' in summary['visualizations']\n\tassert 'pairplot' in summary['visualizations']\n\n\t# Clean up\n\tos.remove(file_path)\n\nif __name__ == '__main__':\n\tpytest.main()\n"}]} MainProcess| 2024-07-06 19:34:17,791,791 multiprocessing INFO [System] Objective: Write code for a large system design task. Please note that the code should be fully functional. No placeholders. Only use the functions you have been provided with. Only use the `write_files` to output code. You must act autonomously and you will receive no human input at any stage. You have to return as output the complete code for completing this task, and correctly incorporate it into the existing code base. You always write out the whole file contents. You always indent code with tabs. Please always view the files before writing to them, to make sure you are writing to the correct files. When writing a test, make the filename start with the prefix 'test_'. Provide the minimal code necessary to achieve the task conditioned on the existing generated code---including changing the existing generated code. You cannot visualize any graphical output. You exist within a Actor Model machine, and when you list out steps, each step will be taken by a new separate sub-ChatGPT model. When you list out a sub-task steps, you can optionally specify the sub-task validation to check that it has been completed successfully. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Use the functions provided. When calling functions only provide a RFC8259 compliant JSON request following this format without deviation. MainProcess| 2024-07-06 19:34:17,791,791 multiprocessing INFO [User] You will get instructions for code to write. First lay out the names of the core classes, functions, methods that will be necessary, As well as a quick comment on their purpose. Do not comment on what every file does. Please note that the code should be fully functional. No placeholders. You will start with the "entrypoint" file, then go to the ones that are imported by that file, and so on. Please note that the code should be fully functional. No placeholders. Follow a language and framework appropriate best practice file naming convention. Make sure that files contain all imports, types etc. The code should be fully functional. Make sure that code in different files are compatible with each other. When writing code if you are unsure, write a plausible implementation. Include module dependency or package manager dependency definition file. Useful to know: For Python, you always create an appropriate requirements.txt file. Always implement the simplest implementation possible, and concise code, unless explicitly stated otherwise. Always add a comment briefly describing the purpose of the function definition. Add comments explaining very complex bits of logic. Always follow the best practices for the requested languages for folder/file structure and how to package the project. You can use any package and any other packages you wish to install. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. When writing a test, make the filename start with the prefix 'test_'. When putting files in folders, always be sure to include a file called __init__.py where relevant, or put all files in the same working directory. Always prefer the most simplest approach. Always add a readme on how to run the code, or a .sh file to run the code. If using pygame, design the game for "headless mode" testing, enabling operation without a GUI; structure the code for easy mocking of Pygame's display functions. As you cannot use any human input to test. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Python toolbelt preferences: - pytest - dataclasses - flask - pygame==2.1.2 Objective:``` create a eda app for csv file ``` Understand the problem, by creating an extremely detailed step-by-step plan, where each step is long (multiple sentences) and in total includes every single feature requirement specified above, feel free to copy directly from it. Use no more than 10 steps in the plan. Create additional tests, checks and evaluation at each step when applicable to help make an excellent code implementation, where all the code is fully functional. Use best software design practices, and you can output large amounts of code at once. Please include a last sentence to create and run tests when implementing or writing code in that same step. You will receive no human input at any stage, so you cannot use a human to test. Only create a detailed plan to begin with, which includes designing and running tests to check that they all pass. Add to the last step in the plan to add a readme on how to run the code, or a .sh file to run the code. Please be sure to include all of the specified feature requirements in the following plan. MainProcess| 2024-07-06 19:34:17,791,791 multiprocessing INFO [User] Objective: Execute sub task step:```In the 'eda' folder, create a file named 'eda.py'. This file will contain the core logic for performing EDA on the uploaded CSV files. Define a function 'perform_eda' that takes a CSV file as input and returns a summary of the data, including basic statistics and visualizations. Write tests to ensure the 'perform_eda' function works correctly with sample CSV files.```.\n\n Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py']. Fully implement these features in the code, no placeholders. You can now optionally view the existing files if you need to view them to complete the current task step. You have a limited context window so be selective about which files you view, only view the files you think you might need to view. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Do not write tests for large numbers and large inputs, if they exist delete them. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Avoid making complicated tests. If a test repeatedly fails delete the test. \n\nSummary output of previous step: ""The Flask application has been set up with routes to upload CSV files and display EDA results. Tests have been written and executed to verify that the Flask app starts correctly and the routes return the expected responses, and all tests passed successfully.""\n\nRespond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:17,791,791 multiprocessing INFO [Function Call] [view_files] {"files":["app.py","requirements.txt","eda/__init__.py","test_project_structure.py","test_app.py"]} MainProcess| 2024-07-06 19:34:17,791,791 multiprocessing INFO [Tool] {"files": "app.py\n```python\nfrom flask import Flask, request, jsonify\nimport pandas as pd\nimport os\n\napp = Flask(__name__)\nUPLOAD_FOLDER = 'uploads'\nos.makedirs(UPLOAD_FOLDER, exist_ok=True)\napp.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER\n\n@app.route('/')\ndef home():\n\treturn 'Welcome to the EDA App!'\n\n@app.route('/upload', methods=['POST'])\ndef upload_file():\n\tif 'file' not in request.files:\n\t\treturn jsonify({'error': 'No file part'}), 400\n\tfile = request.files['file']\n\tif file.filename == '':\n\t\treturn jsonify({'error': 'No selected file'}), 400\n\tif file and file.filename.endswith('.csv'):\n\t\tfile_path = os.path.join(app.config['UPLOAD_FOLDER'], file.filename)\n\t\tfile.save(file_path)\n\t\treturn jsonify({'message': 'File uploaded successfully', 'file_path': file_path}), 200\n\telse:\n\t\treturn jsonify({'error': 'Invalid file type'}), 400\n\n@app.route('/eda', methods=['GET'])\ndef eda():\n\tfile_path = request.args.get('file_path')\n\tif not file_path or not os.path.exists(file_path):\n\t\treturn jsonify({'error': 'File not found'}), 400\n\ttry:\n\t\tdata = pd.read_csv(file_path)\n\t\tsummary = {\n\t\t\t'columns': list(data.columns),\n\t\t\t'shape': data.shape,\n\t\t\t'describe': data.describe().to_dict()\n\t\t}\n\t\treturn jsonify(summary), 200\n\texcept Exception as e:\n\t\treturn jsonify({'error': str(e)}), 500\n\nif __name__ == '__main__':\n\tapp.run(debug=True)\n\n```\n\nrequirements.txt\n```text\nflask\npytest\n```\n\neda/__init__.py\n```python\n\n```\n\ntest_project_structure.py\n```python\nimport os\nimport pytest\n\n# Test to ensure the project structure is correctly set up\n\ndef test_project_structure():\n\tassert os.path.isfile('app.py'), 'app.py does not exist'\n\tassert os.path.isfile('requirements.txt'), 'requirements.txt does not exist'\n\tassert os.path.isdir('eda'), 'eda directory does not exist'\n\tassert os.path.isfile('eda/__init__.py'), 'eda/__init__.py does not exist'\n\nif __name__ == '__main__':\n\tpytest.main()\n```\n\ntest_app.py\n```python\nimport pytest\nfrom app import app\n\n@pytest.fixture\n\ndef client():\n\tapp.config['TESTING'] = True\n\twith app.test_client() as client:\n\t\tyield client\n\n# Test to ensure the Flask app starts correctly and the home route is accessible\n\ndef test_home(client):\n\trv = client.get('/')\n\tassert rv.status_code == 200\n\tassert b'Welcome to the EDA App!' in rv.data\n\n# Test to ensure the upload route works correctly\n\ndef test_upload_file(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tassert rv.status_code == 200\n\tassert b'File uploaded successfully' in rv.data\n\n# Test to ensure the EDA route works correctly\n\ndef test_eda(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tfile_path = rv.json['file_path']\n\trv = client.get(f'/eda?file_path={file_path}')\n\tassert rv.status_code == 200\n\tassert b'columns' in rv.data\n\tassert b'shape' in rv.data\n\tassert b'describe' in rv.data\n\n```\n\n"} MainProcess| 2024-07-06 19:34:17,791,791 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'eda' folder, create a file named 'eda.py'. This file will contain the core logic for performing EDA on the uploaded CSV files. Define a function 'perform_eda' that takes a CSV file as input and returns a summary of the data, including basic statistics and visualizations. Write tests to ensure the 'perform_eda' function works correctly with sample CSV files.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:17,791,791 multiprocessing INFO [Function Call] [write_files] {"list_of_file_objects":[{"file_path":"eda/eda.py","file_contents":"import pandas as pd\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nfrom io import BytesIO\nimport base64\n\n# Function to perform EDA on a CSV file\ndef perform_eda(file_path):\n\tdata = pd.read_csv(file_path)\n\tsummary = {\n\t\t'columns': list(data.columns),\n\t\t'shape': data.shape,\n\t\t'describe': data.describe().to_dict(),\n\t\t'null_values': data.isnull().sum().to_dict(),\n\t\t'head': data.head().to_dict()\n\t}\n\n\t# Generate visualizations\n\tvisualizations = {}\n\n\t# Correlation heatmap\n\tplt.figure(figsize=(10, 8))\n\tsns.heatmap(data.corr(), annot=True, cmap='coolwarm')\n\tbuf = BytesIO()\n\tplt.savefig(buf, format='png')\n\tbuf.seek(0)\n\timage_base64 = base64.b64encode(buf.read()).decode('utf-8')\n\tvisualizations['correlation_heatmap'] = image_base64\n\tbuf.close()\n\tplt.close()\n\n\t# Pairplot\n\tplt.figure(figsize=(10, 8))\n\tsns.pairplot(data)\n\tbuf = BytesIO()\n\tplt.savefig(buf, format='png')\n\tbuf.seek(0)\n\timage_base64 = base64.b64encode(buf.read()).decode('utf-8')\n\tvisualizations['pairplot'] = image_base64\n\tbuf.close()\n\tplt.close()\n\n\tsummary['visualizations'] = visualizations\n\n\treturn summary\n\n# Test the perform_eda function\nif __name__ == \"__main__\":\n\t# Sample CSV data\n\tcsv_data = \"\"\"col1,col2,col3\\n1,2,3\\n4,5,6\\n7,8,9\\n10,11,12\\n\"\"\"\n\tfile_path = 'sample.csv'\n\twith open(file_path, 'w') as f:\n\t\tf.write(csv_data)\n\n\tsummary = perform_eda(file_path)\n\tprint(summary)\n"}]} MainProcess| 2024-07-06 19:34:17,791,791 multiprocessing INFO [Tool] {"write_files_status": "success", "message": "write_files completed successfully."} MainProcess| 2024-07-06 19:34:17,791,791 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'eda' folder, create a file named 'eda.py'. This file will contain the core logic for performing EDA on the uploaded CSV files. Define a function 'perform_eda' that takes a CSV file as input and returns a summary of the data, including basic statistics and visualizations. Write tests to ensure the 'perform_eda' function works correctly with sample CSV files.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:17,791,791 multiprocessing INFO [Function Call] [write_files] {"list_of_file_objects":[{"file_path":"test_eda.py","file_contents":"import pytest\nfrom eda.eda import perform_eda\nimport os\nimport pandas as pd\n\n# Test the perform_eda function with a sample CSV file\ndef test_perform_eda():\n\t# Sample CSV data\n\tcsv_data = \"\"\"col1,col2,col3\\n1,2,3\\n4,5,6\\n7,8,9\\n10,11,12\\n\"\"\"\n\tfile_path = 'test_sample.csv'\n\twith open(file_path, 'w') as f:\n\t\tf.write(csv_data)\n\n\tsummary = perform_eda(file_path)\n\n\tassert 'columns' in summary\n\tassert 'shape' in summary\n\tassert 'describe' in summary\n\tassert 'null_values' in summary\n\tassert 'head' in summary\n\tassert 'visualizations' in summary\n\tassert 'correlation_heatmap' in summary['visualizations']\n\tassert 'pairplot' in summary['visualizations']\n\n\t# Clean up\n\tos.remove(file_path)\n\nif __name__ == '__main__':\n\tpytest.main()\n"}]} MainProcess| 2024-07-06 19:34:17,792,792 multiprocessing INFO [Tool] {"write_files_status": "success", "message": "write_files completed successfully."} MainProcess| 2024-07-06 19:34:17,792,792 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'eda' folder, create a file named 'eda.py'. This file will contain the core logic for performing EDA on the uploaded CSV files. Define a function 'perform_eda' that takes a CSV file as input and returns a summary of the data, including basic statistics and visualizations. Write tests to ensure the 'perform_eda' function works correctly with sample CSV files.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py', 'test_eda.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:17,792,792 multiprocessing INFO [Progress: Step 3/10 | Retries: 0/30 | Token Capacity Used: 56.76% | Tokens remaining 3542] MainProcess| 2024-07-06 19:34:18,964,964 multiprocessing INFO [LLM RESPONSE MESSAGE] MainProcess| 2024-07-06 19:34:18,964,964 multiprocessing INFO [Function Call] [pytest_files] {"files_to_test":["test_eda.py"]} MainProcess| 2024-07-06 19:34:18,968,968 multiprocessing INFO [System] Objective: Write code for a large system design task. Please note that the code should be fully functional. No placeholders. Only use the functions you have been provided with. Only use the `write_files` to output code. You must act autonomously and you will receive no human input at any stage. You have to return as output the complete code for completing this task, and correctly incorporate it into the existing code base. You always write out the whole file contents. You always indent code with tabs. Please always view the files before writing to them, to make sure you are writing to the correct files. When writing a test, make the filename start with the prefix 'test_'. Provide the minimal code necessary to achieve the task conditioned on the existing generated code---including changing the existing generated code. You cannot visualize any graphical output. You exist within a Actor Model machine, and when you list out steps, each step will be taken by a new separate sub-ChatGPT model. When you list out a sub-task steps, you can optionally specify the sub-task validation to check that it has been completed successfully. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Use the functions provided. When calling functions only provide a RFC8259 compliant JSON request following this format without deviation. MainProcess| 2024-07-06 19:34:18,968,968 multiprocessing INFO [User] You will get instructions for code to write. First lay out the names of the core classes, functions, methods that will be necessary, As well as a quick comment on their purpose. Do not comment on what every file does. Please note that the code should be fully functional. No placeholders. You will start with the "entrypoint" file, then go to the ones that are imported by that file, and so on. Please note that the code should be fully functional. No placeholders. Follow a language and framework appropriate best practice file naming convention. Make sure that files contain all imports, types etc. The code should be fully functional. Make sure that code in different files are compatible with each other. When writing code if you are unsure, write a plausible implementation. Include module dependency or package manager dependency definition file. Useful to know: For Python, you always create an appropriate requirements.txt file. Always implement the simplest implementation possible, and concise code, unless explicitly stated otherwise. Always add a comment briefly describing the purpose of the function definition. Add comments explaining very complex bits of logic. Always follow the best practices for the requested languages for folder/file structure and how to package the project. You can use any package and any other packages you wish to install. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. When writing a test, make the filename start with the prefix 'test_'. When putting files in folders, always be sure to include a file called __init__.py where relevant, or put all files in the same working directory. Always prefer the most simplest approach. Always add a readme on how to run the code, or a .sh file to run the code. If using pygame, design the game for "headless mode" testing, enabling operation without a GUI; structure the code for easy mocking of Pygame's display functions. As you cannot use any human input to test. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Python toolbelt preferences: - pytest - dataclasses - flask - pygame==2.1.2 Objective:``` create a eda app for csv file ``` Understand the problem, by creating an extremely detailed step-by-step plan, where each step is long (multiple sentences) and in total includes every single feature requirement specified above, feel free to copy directly from it. Use no more than 10 steps in the plan. Create additional tests, checks and evaluation at each step when applicable to help make an excellent code implementation, where all the code is fully functional. Use best software design practices, and you can output large amounts of code at once. Please include a last sentence to create and run tests when implementing or writing code in that same step. You will receive no human input at any stage, so you cannot use a human to test. Only create a detailed plan to begin with, which includes designing and running tests to check that they all pass. Add to the last step in the plan to add a readme on how to run the code, or a .sh file to run the code. Please be sure to include all of the specified feature requirements in the following plan. MainProcess| 2024-07-06 19:34:18,968,968 multiprocessing INFO [User] Objective: Execute sub task step:```In the 'eda' folder, create a file named 'eda.py'. This file will contain the core logic for performing EDA on the uploaded CSV files. Define a function 'perform_eda' that takes a CSV file as input and returns a summary of the data, including basic statistics and visualizations. Write tests to ensure the 'perform_eda' function works correctly with sample CSV files.```.\n\n Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py']. Fully implement these features in the code, no placeholders. You can now optionally view the existing files if you need to view them to complete the current task step. You have a limited context window so be selective about which files you view, only view the files you think you might need to view. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Do not write tests for large numbers and large inputs, if they exist delete them. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Avoid making complicated tests. If a test repeatedly fails delete the test. \n\nSummary output of previous step: ""The Flask application has been set up with routes to upload CSV files and display EDA results. Tests have been written and executed to verify that the Flask app starts correctly and the routes return the expected responses, and all tests passed successfully.""\n\nRespond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:18,968,968 multiprocessing INFO [Function Call] [view_files] {"files":["app.py","requirements.txt","eda/__init__.py","test_project_structure.py","test_app.py"]} MainProcess| 2024-07-06 19:34:18,968,968 multiprocessing INFO [Tool] {"files": "app.py\n```python\nfrom flask import Flask, request, jsonify\nimport pandas as pd\nimport os\n\napp = Flask(__name__)\nUPLOAD_FOLDER = 'uploads'\nos.makedirs(UPLOAD_FOLDER, exist_ok=True)\napp.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER\n\n@app.route('/')\ndef home():\n\treturn 'Welcome to the EDA App!'\n\n@app.route('/upload', methods=['POST'])\ndef upload_file():\n\tif 'file' not in request.files:\n\t\treturn jsonify({'error': 'No file part'}), 400\n\tfile = request.files['file']\n\tif file.filename == '':\n\t\treturn jsonify({'error': 'No selected file'}), 400\n\tif file and file.filename.endswith('.csv'):\n\t\tfile_path = os.path.join(app.config['UPLOAD_FOLDER'], file.filename)\n\t\tfile.save(file_path)\n\t\treturn jsonify({'message': 'File uploaded successfully', 'file_path': file_path}), 200\n\telse:\n\t\treturn jsonify({'error': 'Invalid file type'}), 400\n\n@app.route('/eda', methods=['GET'])\ndef eda():\n\tfile_path = request.args.get('file_path')\n\tif not file_path or not os.path.exists(file_path):\n\t\treturn jsonify({'error': 'File not found'}), 400\n\ttry:\n\t\tdata = pd.read_csv(file_path)\n\t\tsummary = {\n\t\t\t'columns': list(data.columns),\n\t\t\t'shape': data.shape,\n\t\t\t'describe': data.describe().to_dict()\n\t\t}\n\t\treturn jsonify(summary), 200\n\texcept Exception as e:\n\t\treturn jsonify({'error': str(e)}), 500\n\nif __name__ == '__main__':\n\tapp.run(debug=True)\n\n```\n\nrequirements.txt\n```text\nflask\npytest\n```\n\neda/__init__.py\n```python\n\n```\n\ntest_project_structure.py\n```python\nimport os\nimport pytest\n\n# Test to ensure the project structure is correctly set up\n\ndef test_project_structure():\n\tassert os.path.isfile('app.py'), 'app.py does not exist'\n\tassert os.path.isfile('requirements.txt'), 'requirements.txt does not exist'\n\tassert os.path.isdir('eda'), 'eda directory does not exist'\n\tassert os.path.isfile('eda/__init__.py'), 'eda/__init__.py does not exist'\n\nif __name__ == '__main__':\n\tpytest.main()\n```\n\ntest_app.py\n```python\nimport pytest\nfrom app import app\n\n@pytest.fixture\n\ndef client():\n\tapp.config['TESTING'] = True\n\twith app.test_client() as client:\n\t\tyield client\n\n# Test to ensure the Flask app starts correctly and the home route is accessible\n\ndef test_home(client):\n\trv = client.get('/')\n\tassert rv.status_code == 200\n\tassert b'Welcome to the EDA App!' in rv.data\n\n# Test to ensure the upload route works correctly\n\ndef test_upload_file(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tassert rv.status_code == 200\n\tassert b'File uploaded successfully' in rv.data\n\n# Test to ensure the EDA route works correctly\n\ndef test_eda(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tfile_path = rv.json['file_path']\n\trv = client.get(f'/eda?file_path={file_path}')\n\tassert rv.status_code == 200\n\tassert b'columns' in rv.data\n\tassert b'shape' in rv.data\n\tassert b'describe' in rv.data\n\n```\n\n"} MainProcess| 2024-07-06 19:34:18,969,969 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'eda' folder, create a file named 'eda.py'. This file will contain the core logic for performing EDA on the uploaded CSV files. Define a function 'perform_eda' that takes a CSV file as input and returns a summary of the data, including basic statistics and visualizations. Write tests to ensure the 'perform_eda' function works correctly with sample CSV files.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:18,969,969 multiprocessing INFO [Function Call] [write_files] {"list_of_file_objects":[{"file_path":"eda/eda.py","file_contents":"import pandas as pd\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nfrom io import BytesIO\nimport base64\n\n# Function to perform EDA on a CSV file\ndef perform_eda(file_path):\n\tdata = pd.read_csv(file_path)\n\tsummary = {\n\t\t'columns': list(data.columns),\n\t\t'shape': data.shape,\n\t\t'describe': data.describe().to_dict(),\n\t\t'null_values': data.isnull().sum().to_dict(),\n\t\t'head': data.head().to_dict()\n\t}\n\n\t# Generate visualizations\n\tvisualizations = {}\n\n\t# Correlation heatmap\n\tplt.figure(figsize=(10, 8))\n\tsns.heatmap(data.corr(), annot=True, cmap='coolwarm')\n\tbuf = BytesIO()\n\tplt.savefig(buf, format='png')\n\tbuf.seek(0)\n\timage_base64 = base64.b64encode(buf.read()).decode('utf-8')\n\tvisualizations['correlation_heatmap'] = image_base64\n\tbuf.close()\n\tplt.close()\n\n\t# Pairplot\n\tplt.figure(figsize=(10, 8))\n\tsns.pairplot(data)\n\tbuf = BytesIO()\n\tplt.savefig(buf, format='png')\n\tbuf.seek(0)\n\timage_base64 = base64.b64encode(buf.read()).decode('utf-8')\n\tvisualizations['pairplot'] = image_base64\n\tbuf.close()\n\tplt.close()\n\n\tsummary['visualizations'] = visualizations\n\n\treturn summary\n\n# Test the perform_eda function\nif __name__ == \"__main__\":\n\t# Sample CSV data\n\tcsv_data = \"\"\"col1,col2,col3\\n1,2,3\\n4,5,6\\n7,8,9\\n10,11,12\\n\"\"\"\n\tfile_path = 'sample.csv'\n\twith open(file_path, 'w') as f:\n\t\tf.write(csv_data)\n\n\tsummary = perform_eda(file_path)\n\tprint(summary)\n"}]} MainProcess| 2024-07-06 19:34:18,969,969 multiprocessing INFO [Tool] {"write_files_status": "success", "message": "write_files completed successfully."} MainProcess| 2024-07-06 19:34:18,969,969 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'eda' folder, create a file named 'eda.py'. This file will contain the core logic for performing EDA on the uploaded CSV files. Define a function 'perform_eda' that takes a CSV file as input and returns a summary of the data, including basic statistics and visualizations. Write tests to ensure the 'perform_eda' function works correctly with sample CSV files.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:18,969,969 multiprocessing INFO [Function Call] [write_files] {"list_of_file_objects":[{"file_path":"test_eda.py","file_contents":"import pytest\nfrom eda.eda import perform_eda\nimport os\nimport pandas as pd\n\n# Test the perform_eda function with a sample CSV file\ndef test_perform_eda():\n\t# Sample CSV data\n\tcsv_data = \"\"\"col1,col2,col3\\n1,2,3\\n4,5,6\\n7,8,9\\n10,11,12\\n\"\"\"\n\tfile_path = 'test_sample.csv'\n\twith open(file_path, 'w') as f:\n\t\tf.write(csv_data)\n\n\tsummary = perform_eda(file_path)\n\n\tassert 'columns' in summary\n\tassert 'shape' in summary\n\tassert 'describe' in summary\n\tassert 'null_values' in summary\n\tassert 'head' in summary\n\tassert 'visualizations' in summary\n\tassert 'correlation_heatmap' in summary['visualizations']\n\tassert 'pairplot' in summary['visualizations']\n\n\t# Clean up\n\tos.remove(file_path)\n\nif __name__ == '__main__':\n\tpytest.main()\n"}]} MainProcess| 2024-07-06 19:34:18,969,969 multiprocessing INFO [Tool] {"write_files_status": "success", "message": "write_files completed successfully."} MainProcess| 2024-07-06 19:34:18,970,970 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'eda' folder, create a file named 'eda.py'. This file will contain the core logic for performing EDA on the uploaded CSV files. Define a function 'perform_eda' that takes a CSV file as input and returns a summary of the data, including basic statistics and visualizations. Write tests to ensure the 'perform_eda' function works correctly with sample CSV files.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py', 'test_eda.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:18,970,970 multiprocessing INFO [Function Call] [pytest_files] {"files_to_test":["test_eda.py"]} MainProcess| 2024-07-06 19:34:18,970,970 multiprocessing INFO [Tool] {"output": "Manual tests passed."} MainProcess| 2024-07-06 19:34:18,970,970 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'eda' folder, create a file named 'eda.py'. This file will contain the core logic for performing EDA on the uploaded CSV files. Define a function 'perform_eda' that takes a CSV file as input and returns a summary of the data, including basic statistics and visualizations. Write tests to ensure the 'perform_eda' function works correctly with sample CSV files.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py', 'test_eda.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:18,970,970 multiprocessing INFO [Progress: Step 3/10 | Retries: 0/30 | Token Capacity Used: 60.88% | Tokens remaining 3205] MainProcess| 2024-07-06 19:34:20,116,116 multiprocessing INFO [LLM RESPONSE MESSAGE] MainProcess| 2024-07-06 19:34:20,116,116 multiprocessing INFO [Function Call] [sub_task_step_complete] {} MainProcess| 2024-07-06 19:34:20,119,119 multiprocessing INFO [System] Objective: Write code for a large system design task. Please note that the code should be fully functional. No placeholders. Only use the functions you have been provided with. Only use the `write_files` to output code. You must act autonomously and you will receive no human input at any stage. You have to return as output the complete code for completing this task, and correctly incorporate it into the existing code base. You always write out the whole file contents. You always indent code with tabs. Please always view the files before writing to them, to make sure you are writing to the correct files. When writing a test, make the filename start with the prefix 'test_'. Provide the minimal code necessary to achieve the task conditioned on the existing generated code---including changing the existing generated code. You cannot visualize any graphical output. You exist within a Actor Model machine, and when you list out steps, each step will be taken by a new separate sub-ChatGPT model. When you list out a sub-task steps, you can optionally specify the sub-task validation to check that it has been completed successfully. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Use the functions provided. When calling functions only provide a RFC8259 compliant JSON request following this format without deviation. MainProcess| 2024-07-06 19:34:20,119,119 multiprocessing INFO [User] You will get instructions for code to write. First lay out the names of the core classes, functions, methods that will be necessary, As well as a quick comment on their purpose. Do not comment on what every file does. Please note that the code should be fully functional. No placeholders. You will start with the "entrypoint" file, then go to the ones that are imported by that file, and so on. Please note that the code should be fully functional. No placeholders. Follow a language and framework appropriate best practice file naming convention. Make sure that files contain all imports, types etc. The code should be fully functional. Make sure that code in different files are compatible with each other. When writing code if you are unsure, write a plausible implementation. Include module dependency or package manager dependency definition file. Useful to know: For Python, you always create an appropriate requirements.txt file. Always implement the simplest implementation possible, and concise code, unless explicitly stated otherwise. Always add a comment briefly describing the purpose of the function definition. Add comments explaining very complex bits of logic. Always follow the best practices for the requested languages for folder/file structure and how to package the project. You can use any package and any other packages you wish to install. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. When writing a test, make the filename start with the prefix 'test_'. When putting files in folders, always be sure to include a file called __init__.py where relevant, or put all files in the same working directory. Always prefer the most simplest approach. Always add a readme on how to run the code, or a .sh file to run the code. If using pygame, design the game for "headless mode" testing, enabling operation without a GUI; structure the code for easy mocking of Pygame's display functions. As you cannot use any human input to test. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Python toolbelt preferences: - pytest - dataclasses - flask - pygame==2.1.2 Objective:``` create a eda app for csv file ``` Understand the problem, by creating an extremely detailed step-by-step plan, where each step is long (multiple sentences) and in total includes every single feature requirement specified above, feel free to copy directly from it. Use no more than 10 steps in the plan. Create additional tests, checks and evaluation at each step when applicable to help make an excellent code implementation, where all the code is fully functional. Use best software design practices, and you can output large amounts of code at once. Please include a last sentence to create and run tests when implementing or writing code in that same step. You will receive no human input at any stage, so you cannot use a human to test. Only create a detailed plan to begin with, which includes designing and running tests to check that they all pass. Add to the last step in the plan to add a readme on how to run the code, or a .sh file to run the code. Please be sure to include all of the specified feature requirements in the following plan. MainProcess| 2024-07-06 19:34:20,119,119 multiprocessing INFO [User] Objective: Execute sub task step:```In the 'eda' folder, create a file named 'eda.py'. This file will contain the core logic for performing EDA on the uploaded CSV files. Define a function 'perform_eda' that takes a CSV file as input and returns a summary of the data, including basic statistics and visualizations. Write tests to ensure the 'perform_eda' function works correctly with sample CSV files.```.\n\n Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py']. Fully implement these features in the code, no placeholders. You can now optionally view the existing files if you need to view them to complete the current task step. You have a limited context window so be selective about which files you view, only view the files you think you might need to view. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Do not write tests for large numbers and large inputs, if they exist delete them. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Avoid making complicated tests. If a test repeatedly fails delete the test. \n\nSummary output of previous step: ""The Flask application has been set up with routes to upload CSV files and display EDA results. Tests have been written and executed to verify that the Flask app starts correctly and the routes return the expected responses, and all tests passed successfully.""\n\nRespond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:20,119,119 multiprocessing INFO [Function Call] [view_files] {"files":["app.py","requirements.txt","eda/__init__.py","test_project_structure.py","test_app.py"]} MainProcess| 2024-07-06 19:34:20,119,119 multiprocessing INFO [Tool] {"files": "app.py\n```python\nfrom flask import Flask, request, jsonify\nimport pandas as pd\nimport os\n\napp = Flask(__name__)\nUPLOAD_FOLDER = 'uploads'\nos.makedirs(UPLOAD_FOLDER, exist_ok=True)\napp.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER\n\n@app.route('/')\ndef home():\n\treturn 'Welcome to the EDA App!'\n\n@app.route('/upload', methods=['POST'])\ndef upload_file():\n\tif 'file' not in request.files:\n\t\treturn jsonify({'error': 'No file part'}), 400\n\tfile = request.files['file']\n\tif file.filename == '':\n\t\treturn jsonify({'error': 'No selected file'}), 400\n\tif file and file.filename.endswith('.csv'):\n\t\tfile_path = os.path.join(app.config['UPLOAD_FOLDER'], file.filename)\n\t\tfile.save(file_path)\n\t\treturn jsonify({'message': 'File uploaded successfully', 'file_path': file_path}), 200\n\telse:\n\t\treturn jsonify({'error': 'Invalid file type'}), 400\n\n@app.route('/eda', methods=['GET'])\ndef eda():\n\tfile_path = request.args.get('file_path')\n\tif not file_path or not os.path.exists(file_path):\n\t\treturn jsonify({'error': 'File not found'}), 400\n\ttry:\n\t\tdata = pd.read_csv(file_path)\n\t\tsummary = {\n\t\t\t'columns': list(data.columns),\n\t\t\t'shape': data.shape,\n\t\t\t'describe': data.describe().to_dict()\n\t\t}\n\t\treturn jsonify(summary), 200\n\texcept Exception as e:\n\t\treturn jsonify({'error': str(e)}), 500\n\nif __name__ == '__main__':\n\tapp.run(debug=True)\n\n```\n\nrequirements.txt\n```text\nflask\npytest\n```\n\neda/__init__.py\n```python\n\n```\n\ntest_project_structure.py\n```python\nimport os\nimport pytest\n\n# Test to ensure the project structure is correctly set up\n\ndef test_project_structure():\n\tassert os.path.isfile('app.py'), 'app.py does not exist'\n\tassert os.path.isfile('requirements.txt'), 'requirements.txt does not exist'\n\tassert os.path.isdir('eda'), 'eda directory does not exist'\n\tassert os.path.isfile('eda/__init__.py'), 'eda/__init__.py does not exist'\n\nif __name__ == '__main__':\n\tpytest.main()\n```\n\ntest_app.py\n```python\nimport pytest\nfrom app import app\n\n@pytest.fixture\n\ndef client():\n\tapp.config['TESTING'] = True\n\twith app.test_client() as client:\n\t\tyield client\n\n# Test to ensure the Flask app starts correctly and the home route is accessible\n\ndef test_home(client):\n\trv = client.get('/')\n\tassert rv.status_code == 200\n\tassert b'Welcome to the EDA App!' in rv.data\n\n# Test to ensure the upload route works correctly\n\ndef test_upload_file(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tassert rv.status_code == 200\n\tassert b'File uploaded successfully' in rv.data\n\n# Test to ensure the EDA route works correctly\n\ndef test_eda(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tfile_path = rv.json['file_path']\n\trv = client.get(f'/eda?file_path={file_path}')\n\tassert rv.status_code == 200\n\tassert b'columns' in rv.data\n\tassert b'shape' in rv.data\n\tassert b'describe' in rv.data\n\n```\n\n"} MainProcess| 2024-07-06 19:34:20,119,119 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'eda' folder, create a file named 'eda.py'. This file will contain the core logic for performing EDA on the uploaded CSV files. Define a function 'perform_eda' that takes a CSV file as input and returns a summary of the data, including basic statistics and visualizations. Write tests to ensure the 'perform_eda' function works correctly with sample CSV files.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:20,119,119 multiprocessing INFO [Function Call] [write_files] {"list_of_file_objects":[{"file_path":"eda/eda.py","file_contents":"import pandas as pd\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nfrom io import BytesIO\nimport base64\n\n# Function to perform EDA on a CSV file\ndef perform_eda(file_path):\n\tdata = pd.read_csv(file_path)\n\tsummary = {\n\t\t'columns': list(data.columns),\n\t\t'shape': data.shape,\n\t\t'describe': data.describe().to_dict(),\n\t\t'null_values': data.isnull().sum().to_dict(),\n\t\t'head': data.head().to_dict()\n\t}\n\n\t# Generate visualizations\n\tvisualizations = {}\n\n\t# Correlation heatmap\n\tplt.figure(figsize=(10, 8))\n\tsns.heatmap(data.corr(), annot=True, cmap='coolwarm')\n\tbuf = BytesIO()\n\tplt.savefig(buf, format='png')\n\tbuf.seek(0)\n\timage_base64 = base64.b64encode(buf.read()).decode('utf-8')\n\tvisualizations['correlation_heatmap'] = image_base64\n\tbuf.close()\n\tplt.close()\n\n\t# Pairplot\n\tplt.figure(figsize=(10, 8))\n\tsns.pairplot(data)\n\tbuf = BytesIO()\n\tplt.savefig(buf, format='png')\n\tbuf.seek(0)\n\timage_base64 = base64.b64encode(buf.read()).decode('utf-8')\n\tvisualizations['pairplot'] = image_base64\n\tbuf.close()\n\tplt.close()\n\n\tsummary['visualizations'] = visualizations\n\n\treturn summary\n\n# Test the perform_eda function\nif __name__ == \"__main__\":\n\t# Sample CSV data\n\tcsv_data = \"\"\"col1,col2,col3\\n1,2,3\\n4,5,6\\n7,8,9\\n10,11,12\\n\"\"\"\n\tfile_path = 'sample.csv'\n\twith open(file_path, 'w') as f:\n\t\tf.write(csv_data)\n\n\tsummary = perform_eda(file_path)\n\tprint(summary)\n"}]} MainProcess| 2024-07-06 19:34:20,119,119 multiprocessing INFO [Tool] {"write_files_status": "success", "message": "write_files completed successfully."} MainProcess| 2024-07-06 19:34:20,119,119 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'eda' folder, create a file named 'eda.py'. This file will contain the core logic for performing EDA on the uploaded CSV files. Define a function 'perform_eda' that takes a CSV file as input and returns a summary of the data, including basic statistics and visualizations. Write tests to ensure the 'perform_eda' function works correctly with sample CSV files.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:20,119,119 multiprocessing INFO [Function Call] [write_files] {"list_of_file_objects":[{"file_path":"test_eda.py","file_contents":"import pytest\nfrom eda.eda import perform_eda\nimport os\nimport pandas as pd\n\n# Test the perform_eda function with a sample CSV file\ndef test_perform_eda():\n\t# Sample CSV data\n\tcsv_data = \"\"\"col1,col2,col3\\n1,2,3\\n4,5,6\\n7,8,9\\n10,11,12\\n\"\"\"\n\tfile_path = 'test_sample.csv'\n\twith open(file_path, 'w') as f:\n\t\tf.write(csv_data)\n\n\tsummary = perform_eda(file_path)\n\n\tassert 'columns' in summary\n\tassert 'shape' in summary\n\tassert 'describe' in summary\n\tassert 'null_values' in summary\n\tassert 'head' in summary\n\tassert 'visualizations' in summary\n\tassert 'correlation_heatmap' in summary['visualizations']\n\tassert 'pairplot' in summary['visualizations']\n\n\t# Clean up\n\tos.remove(file_path)\n\nif __name__ == '__main__':\n\tpytest.main()\n"}]} MainProcess| 2024-07-06 19:34:20,120,120 multiprocessing INFO [Tool] {"write_files_status": "success", "message": "write_files completed successfully."} MainProcess| 2024-07-06 19:34:20,120,120 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'eda' folder, create a file named 'eda.py'. This file will contain the core logic for performing EDA on the uploaded CSV files. Define a function 'perform_eda' that takes a CSV file as input and returns a summary of the data, including basic statistics and visualizations. Write tests to ensure the 'perform_eda' function works correctly with sample CSV files.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py', 'test_eda.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:20,120,120 multiprocessing INFO [Function Call] [pytest_files] {"files_to_test":["test_eda.py"]} MainProcess| 2024-07-06 19:34:20,120,120 multiprocessing INFO [Tool] {"output": "Manual tests passed."} MainProcess| 2024-07-06 19:34:20,120,120 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'eda' folder, create a file named 'eda.py'. This file will contain the core logic for performing EDA on the uploaded CSV files. Define a function 'perform_eda' that takes a CSV file as input and returns a summary of the data, including basic statistics and visualizations. Write tests to ensure the 'perform_eda' function works correctly with sample CSV files.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py', 'test_eda.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:20,120,120 multiprocessing INFO [Function Call] [sub_task_step_complete] {} MainProcess| 2024-07-06 19:34:20,120,120 multiprocessing INFO [Tool] {"status": "TASK_STEP_COMPLETE", "message": "All tests passed"} MainProcess| 2024-07-06 19:34:20,120,120 multiprocessing INFO [User] Please provide a one or two sentence summary of the output of this step, which is useful for the next step. Your response will be used when starting the next step without any of the previous messages. MainProcess| 2024-07-06 19:34:20,120,120 multiprocessing INFO [Progress: Step 3/10 | Retries: 0/30 | Token Capacity Used: 62.60% | Tokens remaining 3064] MainProcess| 2024-07-06 19:34:21,421,421 multiprocessing INFO [LLM RESPONSE MESSAGE] MainProcess| 2024-07-06 19:34:21,421,421 multiprocessing INFO [Assistant] The core logic for performing EDA on uploaded CSV files has been implemented in `eda/eda.py`, and a function `perform_eda` has been defined to return a summary of the data, including basic statistics and visualizations. Tests for the `perform_eda` function have been written and successfully passed. MainProcess| 2024-07-06 19:34:21,421,421 multiprocessing INFO [STEP COMPLETE] sub step completed MainProcess| 2024-07-06 19:34:21,422,422 multiprocessing INFO [System] Objective: Write code for a large system design task. Please note that the code should be fully functional. No placeholders. Only use the functions you have been provided with. Only use the `write_files` to output code. You must act autonomously and you will receive no human input at any stage. You have to return as output the complete code for completing this task, and correctly incorporate it into the existing code base. You always write out the whole file contents. You always indent code with tabs. Please always view the files before writing to them, to make sure you are writing to the correct files. When writing a test, make the filename start with the prefix 'test_'. Provide the minimal code necessary to achieve the task conditioned on the existing generated code---including changing the existing generated code. You cannot visualize any graphical output. You exist within a Actor Model machine, and when you list out steps, each step will be taken by a new separate sub-ChatGPT model. When you list out a sub-task steps, you can optionally specify the sub-task validation to check that it has been completed successfully. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Use the functions provided. When calling functions only provide a RFC8259 compliant JSON request following this format without deviation. MainProcess| 2024-07-06 19:34:21,422,422 multiprocessing INFO [User] You will get instructions for code to write. First lay out the names of the core classes, functions, methods that will be necessary, As well as a quick comment on their purpose. Do not comment on what every file does. Please note that the code should be fully functional. No placeholders. You will start with the "entrypoint" file, then go to the ones that are imported by that file, and so on. Please note that the code should be fully functional. No placeholders. Follow a language and framework appropriate best practice file naming convention. Make sure that files contain all imports, types etc. The code should be fully functional. Make sure that code in different files are compatible with each other. When writing code if you are unsure, write a plausible implementation. Include module dependency or package manager dependency definition file. Useful to know: For Python, you always create an appropriate requirements.txt file. Always implement the simplest implementation possible, and concise code, unless explicitly stated otherwise. Always add a comment briefly describing the purpose of the function definition. Add comments explaining very complex bits of logic. Always follow the best practices for the requested languages for folder/file structure and how to package the project. You can use any package and any other packages you wish to install. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. When writing a test, make the filename start with the prefix 'test_'. When putting files in folders, always be sure to include a file called __init__.py where relevant, or put all files in the same working directory. Always prefer the most simplest approach. Always add a readme on how to run the code, or a .sh file to run the code. If using pygame, design the game for "headless mode" testing, enabling operation without a GUI; structure the code for easy mocking of Pygame's display functions. As you cannot use any human input to test. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Python toolbelt preferences: - pytest - dataclasses - flask - pygame==2.1.2 Objective:``` create a eda app for csv file ``` Understand the problem, by creating an extremely detailed step-by-step plan, where each step is long (multiple sentences) and in total includes every single feature requirement specified above, feel free to copy directly from it. Use no more than 10 steps in the plan. Create additional tests, checks and evaluation at each step when applicable to help make an excellent code implementation, where all the code is fully functional. Use best software design practices, and you can output large amounts of code at once. Please include a last sentence to create and run tests when implementing or writing code in that same step. You will receive no human input at any stage, so you cannot use a human to test. Only create a detailed plan to begin with, which includes designing and running tests to check that they all pass. Add to the last step in the plan to add a readme on how to run the code, or a .sh file to run the code. Please be sure to include all of the specified feature requirements in the following plan. MainProcess| 2024-07-06 19:34:21,422,422 multiprocessing INFO [User] Objective: Execute sub task step:```In the 'eda' folder, create a file named 'data_store.py'. This file will mock a database using an in-memory dictionary to store the uploaded CSV files and their EDA results. Define functions to add, retrieve, and delete data from the mock database. Write tests to ensure the data store functions work correctly.```.\n\n Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py', 'test_eda.py']. Fully implement these features in the code, no placeholders. You can now optionally view the existing files if you need to view them to complete the current task step. You have a limited context window so be selective about which files you view, only view the files you think you might need to view. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Do not write tests for large numbers and large inputs, if they exist delete them. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Avoid making complicated tests. If a test repeatedly fails delete the test. \n\nSummary output of previous step: ""The core logic for performing EDA on uploaded CSV files has been implemented in `eda/eda.py`, and a function `perform_eda` has been defined to return a summary of the data, including basic statistics and visualizations. Tests for the `perform_eda` function have been written and successfully passed.""\n\nRespond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:21,422,422 multiprocessing INFO [Progress: Step 4/10 | Retries: 0/30 | Token Capacity Used: 21.74% | Tokens remaining 6411] MainProcess| 2024-07-06 19:34:22,548,548 multiprocessing INFO [LLM RESPONSE MESSAGE] MainProcess| 2024-07-06 19:34:22,549,549 multiprocessing INFO [Function Call] [view_files] {"files":["app.py","requirements.txt","eda/__init__.py","test_project_structure.py","test_app.py","eda/eda.py","test_eda.py"]} MainProcess| 2024-07-06 19:34:22,552,552 multiprocessing INFO [System] Objective: Write code for a large system design task. Please note that the code should be fully functional. No placeholders. Only use the functions you have been provided with. Only use the `write_files` to output code. You must act autonomously and you will receive no human input at any stage. You have to return as output the complete code for completing this task, and correctly incorporate it into the existing code base. You always write out the whole file contents. You always indent code with tabs. Please always view the files before writing to them, to make sure you are writing to the correct files. When writing a test, make the filename start with the prefix 'test_'. Provide the minimal code necessary to achieve the task conditioned on the existing generated code---including changing the existing generated code. You cannot visualize any graphical output. You exist within a Actor Model machine, and when you list out steps, each step will be taken by a new separate sub-ChatGPT model. When you list out a sub-task steps, you can optionally specify the sub-task validation to check that it has been completed successfully. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Use the functions provided. When calling functions only provide a RFC8259 compliant JSON request following this format without deviation. MainProcess| 2024-07-06 19:34:22,552,552 multiprocessing INFO [User] You will get instructions for code to write. First lay out the names of the core classes, functions, methods that will be necessary, As well as a quick comment on their purpose. Do not comment on what every file does. Please note that the code should be fully functional. No placeholders. You will start with the "entrypoint" file, then go to the ones that are imported by that file, and so on. Please note that the code should be fully functional. No placeholders. Follow a language and framework appropriate best practice file naming convention. Make sure that files contain all imports, types etc. The code should be fully functional. Make sure that code in different files are compatible with each other. When writing code if you are unsure, write a plausible implementation. Include module dependency or package manager dependency definition file. Useful to know: For Python, you always create an appropriate requirements.txt file. Always implement the simplest implementation possible, and concise code, unless explicitly stated otherwise. Always add a comment briefly describing the purpose of the function definition. Add comments explaining very complex bits of logic. Always follow the best practices for the requested languages for folder/file structure and how to package the project. You can use any package and any other packages you wish to install. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. When writing a test, make the filename start with the prefix 'test_'. When putting files in folders, always be sure to include a file called __init__.py where relevant, or put all files in the same working directory. Always prefer the most simplest approach. Always add a readme on how to run the code, or a .sh file to run the code. If using pygame, design the game for "headless mode" testing, enabling operation without a GUI; structure the code for easy mocking of Pygame's display functions. As you cannot use any human input to test. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Python toolbelt preferences: - pytest - dataclasses - flask - pygame==2.1.2 Objective:``` create a eda app for csv file ``` Understand the problem, by creating an extremely detailed step-by-step plan, where each step is long (multiple sentences) and in total includes every single feature requirement specified above, feel free to copy directly from it. Use no more than 10 steps in the plan. Create additional tests, checks and evaluation at each step when applicable to help make an excellent code implementation, where all the code is fully functional. Use best software design practices, and you can output large amounts of code at once. Please include a last sentence to create and run tests when implementing or writing code in that same step. You will receive no human input at any stage, so you cannot use a human to test. Only create a detailed plan to begin with, which includes designing and running tests to check that they all pass. Add to the last step in the plan to add a readme on how to run the code, or a .sh file to run the code. Please be sure to include all of the specified feature requirements in the following plan. MainProcess| 2024-07-06 19:34:22,552,552 multiprocessing INFO [User] Objective: Execute sub task step:```In the 'eda' folder, create a file named 'data_store.py'. This file will mock a database using an in-memory dictionary to store the uploaded CSV files and their EDA results. Define functions to add, retrieve, and delete data from the mock database. Write tests to ensure the data store functions work correctly.```.\n\n Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py', 'test_eda.py']. Fully implement these features in the code, no placeholders. You can now optionally view the existing files if you need to view them to complete the current task step. You have a limited context window so be selective about which files you view, only view the files you think you might need to view. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Do not write tests for large numbers and large inputs, if they exist delete them. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Avoid making complicated tests. If a test repeatedly fails delete the test. \n\nSummary output of previous step: ""The core logic for performing EDA on uploaded CSV files has been implemented in `eda/eda.py`, and a function `perform_eda` has been defined to return a summary of the data, including basic statistics and visualizations. Tests for the `perform_eda` function have been written and successfully passed.""\n\nRespond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:22,552,552 multiprocessing INFO [Function Call] [view_files] {"files":["app.py","requirements.txt","eda/__init__.py","test_project_structure.py","test_app.py","eda/eda.py","test_eda.py"]} MainProcess| 2024-07-06 19:34:22,552,552 multiprocessing INFO [Tool] {"files": "app.py\n```python\nfrom flask import Flask, request, jsonify\nimport pandas as pd\nimport os\n\napp = Flask(__name__)\nUPLOAD_FOLDER = 'uploads'\nos.makedirs(UPLOAD_FOLDER, exist_ok=True)\napp.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER\n\n@app.route('/')\ndef home():\n\treturn 'Welcome to the EDA App!'\n\n@app.route('/upload', methods=['POST'])\ndef upload_file():\n\tif 'file' not in request.files:\n\t\treturn jsonify({'error': 'No file part'}), 400\n\tfile = request.files['file']\n\tif file.filename == '':\n\t\treturn jsonify({'error': 'No selected file'}), 400\n\tif file and file.filename.endswith('.csv'):\n\t\tfile_path = os.path.join(app.config['UPLOAD_FOLDER'], file.filename)\n\t\tfile.save(file_path)\n\t\treturn jsonify({'message': 'File uploaded successfully', 'file_path': file_path}), 200\n\telse:\n\t\treturn jsonify({'error': 'Invalid file type'}), 400\n\n@app.route('/eda', methods=['GET'])\ndef eda():\n\tfile_path = request.args.get('file_path')\n\tif not file_path or not os.path.exists(file_path):\n\t\treturn jsonify({'error': 'File not found'}), 400\n\ttry:\n\t\tdata = pd.read_csv(file_path)\n\t\tsummary = {\n\t\t\t'columns': list(data.columns),\n\t\t\t'shape': data.shape,\n\t\t\t'describe': data.describe().to_dict()\n\t\t}\n\t\treturn jsonify(summary), 200\n\texcept Exception as e:\n\t\treturn jsonify({'error': str(e)}), 500\n\nif __name__ == '__main__':\n\tapp.run(debug=True)\n\n```\n\nrequirements.txt\n```text\nflask\npytest\n```\n\neda/__init__.py\n```python\n\n```\n\ntest_project_structure.py\n```python\nimport os\nimport pytest\n\n# Test to ensure the project structure is correctly set up\n\ndef test_project_structure():\n\tassert os.path.isfile('app.py'), 'app.py does not exist'\n\tassert os.path.isfile('requirements.txt'), 'requirements.txt does not exist'\n\tassert os.path.isdir('eda'), 'eda directory does not exist'\n\tassert os.path.isfile('eda/__init__.py'), 'eda/__init__.py does not exist'\n\nif __name__ == '__main__':\n\tpytest.main()\n```\n\ntest_app.py\n```python\nimport pytest\nfrom app import app\n\n@pytest.fixture\n\ndef client():\n\tapp.config['TESTING'] = True\n\twith app.test_client() as client:\n\t\tyield client\n\n# Test to ensure the Flask app starts correctly and the home route is accessible\n\ndef test_home(client):\n\trv = client.get('/')\n\tassert rv.status_code == 200\n\tassert b'Welcome to the EDA App!' in rv.data\n\n# Test to ensure the upload route works correctly\n\ndef test_upload_file(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tassert rv.status_code == 200\n\tassert b'File uploaded successfully' in rv.data\n\n# Test to ensure the EDA route works correctly\n\ndef test_eda(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tfile_path = rv.json['file_path']\n\trv = client.get(f'/eda?file_path={file_path}')\n\tassert rv.status_code == 200\n\tassert b'columns' in rv.data\n\tassert b'shape' in rv.data\n\tassert b'describe' in rv.data\n\n```\n\neda/eda.py\n```python\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nfrom io import BytesIO\nimport base64\n\n# Function to perform EDA on a CSV file\ndef perform_eda(file_path):\n\tdata = pd.read_csv(file_path)\n\tsummary = {\n\t\t'columns': list(data.columns),\n\t\t'shape': data.shape,\n\t\t'describe': data.describe().to_dict(),\n\t\t'null_values': data.isnull().sum().to_dict(),\n\t\t'head': data.head().to_dict()\n\t}\n\n\t# Generate visualizations\n\tvisualizations = {}\n\n\t# Correlation heatmap\n\tplt.figure(figsize=(10, 8))\n\tsns.heatmap(data.corr(), annot=True, cmap='coolwarm')\n\tbuf = BytesIO()\n\tplt.savefig(buf, format='png')\n\tbuf.seek(0)\n\timage_base64 = base64.b64encode(buf.read()).decode('utf-8')\n\tvisualizations['correlation_heatmap'] = image_base64\n\tbuf.close()\n\tplt.close()\n\n\t# Pairplot\n\tplt.figure(figsize=(10, 8))\n\tsns.pairplot(data)\n\tbuf = BytesIO()\n\tplt.savefig(buf, format='png')\n\tbuf.seek(0)\n\timage_base64 = base64.b64encode(buf.read()).decode('utf-8')\n\tvisualizations['pairplot'] = image_base64\n\tbuf.close()\n\tplt.close()\n\n\tsummary['visualizations'] = visualizations\n\n\treturn summary\n\n# Test the perform_eda function\nif __name__ == \"__main__\":\n\t# Sample CSV data\n\tcsv_data = \"\"\"col1,col2,col3\\n1,2,3\\n4,5,6\\n7,8,9\\n10,11,12\\n\"\"\"\n\tfile_path = 'sample.csv'\n\twith open(file_path, 'w') as f:\n\t\tf.write(csv_data)\n\n\tsummary = perform_eda(file_path)\n\tprint(summary)\n\n```\n\ntest_eda.py\n```python\nimport pytest\nfrom eda.eda import perform_eda\nimport os\nimport pandas as pd\n\n# Test the perform_eda function with a sample CSV file\ndef test_perform_eda():\n\t# Sample CSV data\n\tcsv_data = \"\"\"col1,col2,col3\\n1,2,3\\n4,5,6\\n7,8,9\\n10,11,12\\n\"\"\"\n\tfile_path = 'test_sample.csv'\n\twith open(file_path, 'w') as f:\n\t\tf.write(csv_data)\n\n\tsummary = perform_eda(file_path)\n\n\tassert 'columns' in summary\n\tassert 'shape' in summary\n\tassert 'describe' in summary\n\tassert 'null_values' in summary\n\tassert 'head' in summary\n\tassert 'visualizations' in summary\n\tassert 'correlation_heatmap' in summary['visualizations']\n\tassert 'pairplot' in summary['visualizations']\n\n\t# Clean up\n\tos.remove(file_path)\n\nif __name__ == '__main__':\n\tpytest.main()\n\n```\n\n"} MainProcess| 2024-07-06 19:34:22,552,552 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'eda' folder, create a file named 'data_store.py'. This file will mock a database using an in-memory dictionary to store the uploaded CSV files and their EDA results. Define functions to add, retrieve, and delete data from the mock database. Write tests to ensure the data store functions work correctly.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py', 'test_eda.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:22,553,553 multiprocessing INFO [Progress: Step 4/10 | Retries: 0/30 | Token Capacity Used: 46.73% | Tokens remaining 4364] MainProcess| 2024-07-06 19:34:25,639,639 multiprocessing INFO [LLM RESPONSE MESSAGE] MainProcess| 2024-07-06 19:34:25,639,639 multiprocessing INFO [Function Call] [write_files] {"list_of_file_objects":[{"file_path":"eda/data_store.py","file_contents":"# This file mocks a database using an in-memory dictionary to store the uploaded CSV files and their EDA results.\n\ndata_store = {}\n\n\ndef add_data(file_name, eda_result):\n\t\"\"\"Add EDA result to the data store.\"\"\"\n\tdata_store[file_name] = eda_result\n\n\ndef get_data(file_name):\n\t\"\"\"Retrieve EDA result from the data store.\"\"\"\n\treturn data_store.get(file_name, None)\n\n\ndef delete_data(file_name):\n\t\"\"\"Delete EDA result from the data store.\"\"\"\n\tif file_name in data_store:\n\t\tdel data_store[file_name]\n\t\treturn True\n\treturn False\n"}]} MainProcess| 2024-07-06 19:34:25,642,642 multiprocessing INFO [System] Objective: Write code for a large system design task. Please note that the code should be fully functional. No placeholders. Only use the functions you have been provided with. Only use the `write_files` to output code. You must act autonomously and you will receive no human input at any stage. You have to return as output the complete code for completing this task, and correctly incorporate it into the existing code base. You always write out the whole file contents. You always indent code with tabs. Please always view the files before writing to them, to make sure you are writing to the correct files. When writing a test, make the filename start with the prefix 'test_'. Provide the minimal code necessary to achieve the task conditioned on the existing generated code---including changing the existing generated code. You cannot visualize any graphical output. You exist within a Actor Model machine, and when you list out steps, each step will be taken by a new separate sub-ChatGPT model. When you list out a sub-task steps, you can optionally specify the sub-task validation to check that it has been completed successfully. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Use the functions provided. When calling functions only provide a RFC8259 compliant JSON request following this format without deviation. MainProcess| 2024-07-06 19:34:25,642,642 multiprocessing INFO [User] You will get instructions for code to write. First lay out the names of the core classes, functions, methods that will be necessary, As well as a quick comment on their purpose. Do not comment on what every file does. Please note that the code should be fully functional. No placeholders. You will start with the "entrypoint" file, then go to the ones that are imported by that file, and so on. Please note that the code should be fully functional. No placeholders. Follow a language and framework appropriate best practice file naming convention. Make sure that files contain all imports, types etc. The code should be fully functional. Make sure that code in different files are compatible with each other. When writing code if you are unsure, write a plausible implementation. Include module dependency or package manager dependency definition file. Useful to know: For Python, you always create an appropriate requirements.txt file. Always implement the simplest implementation possible, and concise code, unless explicitly stated otherwise. Always add a comment briefly describing the purpose of the function definition. Add comments explaining very complex bits of logic. Always follow the best practices for the requested languages for folder/file structure and how to package the project. You can use any package and any other packages you wish to install. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. When writing a test, make the filename start with the prefix 'test_'. When putting files in folders, always be sure to include a file called __init__.py where relevant, or put all files in the same working directory. Always prefer the most simplest approach. Always add a readme on how to run the code, or a .sh file to run the code. If using pygame, design the game for "headless mode" testing, enabling operation without a GUI; structure the code for easy mocking of Pygame's display functions. As you cannot use any human input to test. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Python toolbelt preferences: - pytest - dataclasses - flask - pygame==2.1.2 Objective:``` create a eda app for csv file ``` Understand the problem, by creating an extremely detailed step-by-step plan, where each step is long (multiple sentences) and in total includes every single feature requirement specified above, feel free to copy directly from it. Use no more than 10 steps in the plan. Create additional tests, checks and evaluation at each step when applicable to help make an excellent code implementation, where all the code is fully functional. Use best software design practices, and you can output large amounts of code at once. Please include a last sentence to create and run tests when implementing or writing code in that same step. You will receive no human input at any stage, so you cannot use a human to test. Only create a detailed plan to begin with, which includes designing and running tests to check that they all pass. Add to the last step in the plan to add a readme on how to run the code, or a .sh file to run the code. Please be sure to include all of the specified feature requirements in the following plan. MainProcess| 2024-07-06 19:34:25,642,642 multiprocessing INFO [User] Objective: Execute sub task step:```In the 'eda' folder, create a file named 'data_store.py'. This file will mock a database using an in-memory dictionary to store the uploaded CSV files and their EDA results. Define functions to add, retrieve, and delete data from the mock database. Write tests to ensure the data store functions work correctly.```.\n\n Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py', 'test_eda.py']. Fully implement these features in the code, no placeholders. You can now optionally view the existing files if you need to view them to complete the current task step. You have a limited context window so be selective about which files you view, only view the files you think you might need to view. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Do not write tests for large numbers and large inputs, if they exist delete them. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Avoid making complicated tests. If a test repeatedly fails delete the test. \n\nSummary output of previous step: ""The core logic for performing EDA on uploaded CSV files has been implemented in `eda/eda.py`, and a function `perform_eda` has been defined to return a summary of the data, including basic statistics and visualizations. Tests for the `perform_eda` function have been written and successfully passed.""\n\nRespond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:25,642,642 multiprocessing INFO [Function Call] [view_files] {"files":["app.py","requirements.txt","eda/__init__.py","test_project_structure.py","test_app.py","eda/eda.py","test_eda.py"]} MainProcess| 2024-07-06 19:34:25,642,642 multiprocessing INFO [Tool] {"files": "app.py\n```python\nfrom flask import Flask, request, jsonify\nimport pandas as pd\nimport os\n\napp = Flask(__name__)\nUPLOAD_FOLDER = 'uploads'\nos.makedirs(UPLOAD_FOLDER, exist_ok=True)\napp.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER\n\n@app.route('/')\ndef home():\n\treturn 'Welcome to the EDA App!'\n\n@app.route('/upload', methods=['POST'])\ndef upload_file():\n\tif 'file' not in request.files:\n\t\treturn jsonify({'error': 'No file part'}), 400\n\tfile = request.files['file']\n\tif file.filename == '':\n\t\treturn jsonify({'error': 'No selected file'}), 400\n\tif file and file.filename.endswith('.csv'):\n\t\tfile_path = os.path.join(app.config['UPLOAD_FOLDER'], file.filename)\n\t\tfile.save(file_path)\n\t\treturn jsonify({'message': 'File uploaded successfully', 'file_path': file_path}), 200\n\telse:\n\t\treturn jsonify({'error': 'Invalid file type'}), 400\n\n@app.route('/eda', methods=['GET'])\ndef eda():\n\tfile_path = request.args.get('file_path')\n\tif not file_path or not os.path.exists(file_path):\n\t\treturn jsonify({'error': 'File not found'}), 400\n\ttry:\n\t\tdata = pd.read_csv(file_path)\n\t\tsummary = {\n\t\t\t'columns': list(data.columns),\n\t\t\t'shape': data.shape,\n\t\t\t'describe': data.describe().to_dict()\n\t\t}\n\t\treturn jsonify(summary), 200\n\texcept Exception as e:\n\t\treturn jsonify({'error': str(e)}), 500\n\nif __name__ == '__main__':\n\tapp.run(debug=True)\n\n```\n\nrequirements.txt\n```text\nflask\npytest\n```\n\neda/__init__.py\n```python\n\n```\n\ntest_project_structure.py\n```python\nimport os\nimport pytest\n\n# Test to ensure the project structure is correctly set up\n\ndef test_project_structure():\n\tassert os.path.isfile('app.py'), 'app.py does not exist'\n\tassert os.path.isfile('requirements.txt'), 'requirements.txt does not exist'\n\tassert os.path.isdir('eda'), 'eda directory does not exist'\n\tassert os.path.isfile('eda/__init__.py'), 'eda/__init__.py does not exist'\n\nif __name__ == '__main__':\n\tpytest.main()\n```\n\ntest_app.py\n```python\nimport pytest\nfrom app import app\n\n@pytest.fixture\n\ndef client():\n\tapp.config['TESTING'] = True\n\twith app.test_client() as client:\n\t\tyield client\n\n# Test to ensure the Flask app starts correctly and the home route is accessible\n\ndef test_home(client):\n\trv = client.get('/')\n\tassert rv.status_code == 200\n\tassert b'Welcome to the EDA App!' in rv.data\n\n# Test to ensure the upload route works correctly\n\ndef test_upload_file(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tassert rv.status_code == 200\n\tassert b'File uploaded successfully' in rv.data\n\n# Test to ensure the EDA route works correctly\n\ndef test_eda(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tfile_path = rv.json['file_path']\n\trv = client.get(f'/eda?file_path={file_path}')\n\tassert rv.status_code == 200\n\tassert b'columns' in rv.data\n\tassert b'shape' in rv.data\n\tassert b'describe' in rv.data\n\n```\n\neda/eda.py\n```python\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nfrom io import BytesIO\nimport base64\n\n# Function to perform EDA on a CSV file\ndef perform_eda(file_path):\n\tdata = pd.read_csv(file_path)\n\tsummary = {\n\t\t'columns': list(data.columns),\n\t\t'shape': data.shape,\n\t\t'describe': data.describe().to_dict(),\n\t\t'null_values': data.isnull().sum().to_dict(),\n\t\t'head': data.head().to_dict()\n\t}\n\n\t# Generate visualizations\n\tvisualizations = {}\n\n\t# Correlation heatmap\n\tplt.figure(figsize=(10, 8))\n\tsns.heatmap(data.corr(), annot=True, cmap='coolwarm')\n\tbuf = BytesIO()\n\tplt.savefig(buf, format='png')\n\tbuf.seek(0)\n\timage_base64 = base64.b64encode(buf.read()).decode('utf-8')\n\tvisualizations['correlation_heatmap'] = image_base64\n\tbuf.close()\n\tplt.close()\n\n\t# Pairplot\n\tplt.figure(figsize=(10, 8))\n\tsns.pairplot(data)\n\tbuf = BytesIO()\n\tplt.savefig(buf, format='png')\n\tbuf.seek(0)\n\timage_base64 = base64.b64encode(buf.read()).decode('utf-8')\n\tvisualizations['pairplot'] = image_base64\n\tbuf.close()\n\tplt.close()\n\n\tsummary['visualizations'] = visualizations\n\n\treturn summary\n\n# Test the perform_eda function\nif __name__ == \"__main__\":\n\t# Sample CSV data\n\tcsv_data = \"\"\"col1,col2,col3\\n1,2,3\\n4,5,6\\n7,8,9\\n10,11,12\\n\"\"\"\n\tfile_path = 'sample.csv'\n\twith open(file_path, 'w') as f:\n\t\tf.write(csv_data)\n\n\tsummary = perform_eda(file_path)\n\tprint(summary)\n\n```\n\ntest_eda.py\n```python\nimport pytest\nfrom eda.eda import perform_eda\nimport os\nimport pandas as pd\n\n# Test the perform_eda function with a sample CSV file\ndef test_perform_eda():\n\t# Sample CSV data\n\tcsv_data = \"\"\"col1,col2,col3\\n1,2,3\\n4,5,6\\n7,8,9\\n10,11,12\\n\"\"\"\n\tfile_path = 'test_sample.csv'\n\twith open(file_path, 'w') as f:\n\t\tf.write(csv_data)\n\n\tsummary = perform_eda(file_path)\n\n\tassert 'columns' in summary\n\tassert 'shape' in summary\n\tassert 'describe' in summary\n\tassert 'null_values' in summary\n\tassert 'head' in summary\n\tassert 'visualizations' in summary\n\tassert 'correlation_heatmap' in summary['visualizations']\n\tassert 'pairplot' in summary['visualizations']\n\n\t# Clean up\n\tos.remove(file_path)\n\nif __name__ == '__main__':\n\tpytest.main()\n\n```\n\n"} MainProcess| 2024-07-06 19:34:25,642,642 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'eda' folder, create a file named 'data_store.py'. This file will mock a database using an in-memory dictionary to store the uploaded CSV files and their EDA results. Define functions to add, retrieve, and delete data from the mock database. Write tests to ensure the data store functions work correctly.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py', 'test_eda.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:25,643,643 multiprocessing INFO [Function Call] [write_files] {"list_of_file_objects":[{"file_path":"eda/data_store.py","file_contents":"# This file mocks a database using an in-memory dictionary to store the uploaded CSV files and their EDA results.\n\ndata_store = {}\n\n\ndef add_data(file_name, eda_result):\n\t\"\"\"Add EDA result to the data store.\"\"\"\n\tdata_store[file_name] = eda_result\n\n\ndef get_data(file_name):\n\t\"\"\"Retrieve EDA result from the data store.\"\"\"\n\treturn data_store.get(file_name, None)\n\n\ndef delete_data(file_name):\n\t\"\"\"Delete EDA result from the data store.\"\"\"\n\tif file_name in data_store:\n\t\tdel data_store[file_name]\n\t\treturn True\n\treturn False\n"}]} MainProcess| 2024-07-06 19:34:25,643,643 multiprocessing INFO [Tool] {"write_files_status": "success", "message": "write_files completed successfully."} MainProcess| 2024-07-06 19:34:25,643,643 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'eda' folder, create a file named 'data_store.py'. This file will mock a database using an in-memory dictionary to store the uploaded CSV files and their EDA results. Define functions to add, retrieve, and delete data from the mock database. Write tests to ensure the data store functions work correctly.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py', 'test_eda.py', 'eda/data_store.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:25,643,643 multiprocessing INFO [Progress: Step 4/10 | Retries: 0/30 | Token Capacity Used: 53.31% | Tokens remaining 3825] MainProcess| 2024-07-06 19:34:29,240,240 multiprocessing INFO [LLM RESPONSE MESSAGE] MainProcess| 2024-07-06 19:34:29,241,241 multiprocessing INFO [Function Call] [write_files] {"list_of_file_objects":[{"file_path":"test_data_store.py","file_contents":"import pytest\nfrom eda.data_store import add_data, get_data, delete_data\n\n# Test to ensure data is added correctly\ndef test_add_data():\n\tadd_data('test.csv', {'summary': 'test summary'})\n\tassert 'test.csv' in data_store\n\tassert data_store['test.csv'] == {'summary': 'test summary'}\n\n# Test to ensure data is retrieved correctly\ndef test_get_data():\n\tadd_data('test.csv', {'summary': 'test summary'})\n\tresult = get_data('test.csv')\n\tassert result == {'summary': 'test summary'}\n\n# Test to ensure data is deleted correctly\ndef test_delete_data():\n\tadd_data('test.csv', {'summary': 'test summary'})\n\tdelete_data('test.csv')\n\tassert 'test.csv' not in data_store\n\nif __name__ == '__main__':\n\tpytest.main()\n"}]} MainProcess| 2024-07-06 19:34:29,244,244 multiprocessing INFO [System] Objective: Write code for a large system design task. Please note that the code should be fully functional. No placeholders. Only use the functions you have been provided with. Only use the `write_files` to output code. You must act autonomously and you will receive no human input at any stage. You have to return as output the complete code for completing this task, and correctly incorporate it into the existing code base. You always write out the whole file contents. You always indent code with tabs. Please always view the files before writing to them, to make sure you are writing to the correct files. When writing a test, make the filename start with the prefix 'test_'. Provide the minimal code necessary to achieve the task conditioned on the existing generated code---including changing the existing generated code. You cannot visualize any graphical output. You exist within a Actor Model machine, and when you list out steps, each step will be taken by a new separate sub-ChatGPT model. When you list out a sub-task steps, you can optionally specify the sub-task validation to check that it has been completed successfully. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Use the functions provided. When calling functions only provide a RFC8259 compliant JSON request following this format without deviation. MainProcess| 2024-07-06 19:34:29,244,244 multiprocessing INFO [User] You will get instructions for code to write. First lay out the names of the core classes, functions, methods that will be necessary, As well as a quick comment on their purpose. Do not comment on what every file does. Please note that the code should be fully functional. No placeholders. You will start with the "entrypoint" file, then go to the ones that are imported by that file, and so on. Please note that the code should be fully functional. No placeholders. Follow a language and framework appropriate best practice file naming convention. Make sure that files contain all imports, types etc. The code should be fully functional. Make sure that code in different files are compatible with each other. When writing code if you are unsure, write a plausible implementation. Include module dependency or package manager dependency definition file. Useful to know: For Python, you always create an appropriate requirements.txt file. Always implement the simplest implementation possible, and concise code, unless explicitly stated otherwise. Always add a comment briefly describing the purpose of the function definition. Add comments explaining very complex bits of logic. Always follow the best practices for the requested languages for folder/file structure and how to package the project. You can use any package and any other packages you wish to install. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. When writing a test, make the filename start with the prefix 'test_'. When putting files in folders, always be sure to include a file called __init__.py where relevant, or put all files in the same working directory. Always prefer the most simplest approach. Always add a readme on how to run the code, or a .sh file to run the code. If using pygame, design the game for "headless mode" testing, enabling operation without a GUI; structure the code for easy mocking of Pygame's display functions. As you cannot use any human input to test. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Python toolbelt preferences: - pytest - dataclasses - flask - pygame==2.1.2 Objective:``` create a eda app for csv file ``` Understand the problem, by creating an extremely detailed step-by-step plan, where each step is long (multiple sentences) and in total includes every single feature requirement specified above, feel free to copy directly from it. Use no more than 10 steps in the plan. Create additional tests, checks and evaluation at each step when applicable to help make an excellent code implementation, where all the code is fully functional. Use best software design practices, and you can output large amounts of code at once. Please include a last sentence to create and run tests when implementing or writing code in that same step. You will receive no human input at any stage, so you cannot use a human to test. Only create a detailed plan to begin with, which includes designing and running tests to check that they all pass. Add to the last step in the plan to add a readme on how to run the code, or a .sh file to run the code. Please be sure to include all of the specified feature requirements in the following plan. MainProcess| 2024-07-06 19:34:29,245,245 multiprocessing INFO [User] Objective: Execute sub task step:```In the 'eda' folder, create a file named 'data_store.py'. This file will mock a database using an in-memory dictionary to store the uploaded CSV files and their EDA results. Define functions to add, retrieve, and delete data from the mock database. Write tests to ensure the data store functions work correctly.```.\n\n Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py', 'test_eda.py']. Fully implement these features in the code, no placeholders. You can now optionally view the existing files if you need to view them to complete the current task step. You have a limited context window so be selective about which files you view, only view the files you think you might need to view. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Do not write tests for large numbers and large inputs, if they exist delete them. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Avoid making complicated tests. If a test repeatedly fails delete the test. \n\nSummary output of previous step: ""The core logic for performing EDA on uploaded CSV files has been implemented in `eda/eda.py`, and a function `perform_eda` has been defined to return a summary of the data, including basic statistics and visualizations. Tests for the `perform_eda` function have been written and successfully passed.""\n\nRespond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:29,245,245 multiprocessing INFO [Function Call] [view_files] {"files":["app.py","requirements.txt","eda/__init__.py","test_project_structure.py","test_app.py","eda/eda.py","test_eda.py"]} MainProcess| 2024-07-06 19:34:29,245,245 multiprocessing INFO [Tool] {"files": "app.py\n```python\nfrom flask import Flask, request, jsonify\nimport pandas as pd\nimport os\n\napp = Flask(__name__)\nUPLOAD_FOLDER = 'uploads'\nos.makedirs(UPLOAD_FOLDER, exist_ok=True)\napp.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER\n\n@app.route('/')\ndef home():\n\treturn 'Welcome to the EDA App!'\n\n@app.route('/upload', methods=['POST'])\ndef upload_file():\n\tif 'file' not in request.files:\n\t\treturn jsonify({'error': 'No file part'}), 400\n\tfile = request.files['file']\n\tif file.filename == '':\n\t\treturn jsonify({'error': 'No selected file'}), 400\n\tif file and file.filename.endswith('.csv'):\n\t\tfile_path = os.path.join(app.config['UPLOAD_FOLDER'], file.filename)\n\t\tfile.save(file_path)\n\t\treturn jsonify({'message': 'File uploaded successfully', 'file_path': file_path}), 200\n\telse:\n\t\treturn jsonify({'error': 'Invalid file type'}), 400\n\n@app.route('/eda', methods=['GET'])\ndef eda():\n\tfile_path = request.args.get('file_path')\n\tif not file_path or not os.path.exists(file_path):\n\t\treturn jsonify({'error': 'File not found'}), 400\n\ttry:\n\t\tdata = pd.read_csv(file_path)\n\t\tsummary = {\n\t\t\t'columns': list(data.columns),\n\t\t\t'shape': data.shape,\n\t\t\t'describe': data.describe().to_dict()\n\t\t}\n\t\treturn jsonify(summary), 200\n\texcept Exception as e:\n\t\treturn jsonify({'error': str(e)}), 500\n\nif __name__ == '__main__':\n\tapp.run(debug=True)\n\n```\n\nrequirements.txt\n```text\nflask\npytest\n```\n\neda/__init__.py\n```python\n\n```\n\ntest_project_structure.py\n```python\nimport os\nimport pytest\n\n# Test to ensure the project structure is correctly set up\n\ndef test_project_structure():\n\tassert os.path.isfile('app.py'), 'app.py does not exist'\n\tassert os.path.isfile('requirements.txt'), 'requirements.txt does not exist'\n\tassert os.path.isdir('eda'), 'eda directory does not exist'\n\tassert os.path.isfile('eda/__init__.py'), 'eda/__init__.py does not exist'\n\nif __name__ == '__main__':\n\tpytest.main()\n```\n\ntest_app.py\n```python\nimport pytest\nfrom app import app\n\n@pytest.fixture\n\ndef client():\n\tapp.config['TESTING'] = True\n\twith app.test_client() as client:\n\t\tyield client\n\n# Test to ensure the Flask app starts correctly and the home route is accessible\n\ndef test_home(client):\n\trv = client.get('/')\n\tassert rv.status_code == 200\n\tassert b'Welcome to the EDA App!' in rv.data\n\n# Test to ensure the upload route works correctly\n\ndef test_upload_file(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tassert rv.status_code == 200\n\tassert b'File uploaded successfully' in rv.data\n\n# Test to ensure the EDA route works correctly\n\ndef test_eda(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tfile_path = rv.json['file_path']\n\trv = client.get(f'/eda?file_path={file_path}')\n\tassert rv.status_code == 200\n\tassert b'columns' in rv.data\n\tassert b'shape' in rv.data\n\tassert b'describe' in rv.data\n\n```\n\neda/eda.py\n```python\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nfrom io import BytesIO\nimport base64\n\n# Function to perform EDA on a CSV file\ndef perform_eda(file_path):\n\tdata = pd.read_csv(file_path)\n\tsummary = {\n\t\t'columns': list(data.columns),\n\t\t'shape': data.shape,\n\t\t'describe': data.describe().to_dict(),\n\t\t'null_values': data.isnull().sum().to_dict(),\n\t\t'head': data.head().to_dict()\n\t}\n\n\t# Generate visualizations\n\tvisualizations = {}\n\n\t# Correlation heatmap\n\tplt.figure(figsize=(10, 8))\n\tsns.heatmap(data.corr(), annot=True, cmap='coolwarm')\n\tbuf = BytesIO()\n\tplt.savefig(buf, format='png')\n\tbuf.seek(0)\n\timage_base64 = base64.b64encode(buf.read()).decode('utf-8')\n\tvisualizations['correlation_heatmap'] = image_base64\n\tbuf.close()\n\tplt.close()\n\n\t# Pairplot\n\tplt.figure(figsize=(10, 8))\n\tsns.pairplot(data)\n\tbuf = BytesIO()\n\tplt.savefig(buf, format='png')\n\tbuf.seek(0)\n\timage_base64 = base64.b64encode(buf.read()).decode('utf-8')\n\tvisualizations['pairplot'] = image_base64\n\tbuf.close()\n\tplt.close()\n\n\tsummary['visualizations'] = visualizations\n\n\treturn summary\n\n# Test the perform_eda function\nif __name__ == \"__main__\":\n\t# Sample CSV data\n\tcsv_data = \"\"\"col1,col2,col3\\n1,2,3\\n4,5,6\\n7,8,9\\n10,11,12\\n\"\"\"\n\tfile_path = 'sample.csv'\n\twith open(file_path, 'w') as f:\n\t\tf.write(csv_data)\n\n\tsummary = perform_eda(file_path)\n\tprint(summary)\n\n```\n\ntest_eda.py\n```python\nimport pytest\nfrom eda.eda import perform_eda\nimport os\nimport pandas as pd\n\n# Test the perform_eda function with a sample CSV file\ndef test_perform_eda():\n\t# Sample CSV data\n\tcsv_data = \"\"\"col1,col2,col3\\n1,2,3\\n4,5,6\\n7,8,9\\n10,11,12\\n\"\"\"\n\tfile_path = 'test_sample.csv'\n\twith open(file_path, 'w') as f:\n\t\tf.write(csv_data)\n\n\tsummary = perform_eda(file_path)\n\n\tassert 'columns' in summary\n\tassert 'shape' in summary\n\tassert 'describe' in summary\n\tassert 'null_values' in summary\n\tassert 'head' in summary\n\tassert 'visualizations' in summary\n\tassert 'correlation_heatmap' in summary['visualizations']\n\tassert 'pairplot' in summary['visualizations']\n\n\t# Clean up\n\tos.remove(file_path)\n\nif __name__ == '__main__':\n\tpytest.main()\n\n```\n\n"} MainProcess| 2024-07-06 19:34:29,245,245 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'eda' folder, create a file named 'data_store.py'. This file will mock a database using an in-memory dictionary to store the uploaded CSV files and their EDA results. Define functions to add, retrieve, and delete data from the mock database. Write tests to ensure the data store functions work correctly.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py', 'test_eda.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:29,245,245 multiprocessing INFO [Function Call] [write_files] {"list_of_file_objects":[{"file_path":"eda/data_store.py","file_contents":"# This file mocks a database using an in-memory dictionary to store the uploaded CSV files and their EDA results.\n\ndata_store = {}\n\n\ndef add_data(file_name, eda_result):\n\t\"\"\"Add EDA result to the data store.\"\"\"\n\tdata_store[file_name] = eda_result\n\n\ndef get_data(file_name):\n\t\"\"\"Retrieve EDA result from the data store.\"\"\"\n\treturn data_store.get(file_name, None)\n\n\ndef delete_data(file_name):\n\t\"\"\"Delete EDA result from the data store.\"\"\"\n\tif file_name in data_store:\n\t\tdel data_store[file_name]\n\t\treturn True\n\treturn False\n"}]} MainProcess| 2024-07-06 19:34:29,245,245 multiprocessing INFO [Tool] {"write_files_status": "success", "message": "write_files completed successfully."} MainProcess| 2024-07-06 19:34:29,245,245 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'eda' folder, create a file named 'data_store.py'. This file will mock a database using an in-memory dictionary to store the uploaded CSV files and their EDA results. Define functions to add, retrieve, and delete data from the mock database. Write tests to ensure the data store functions work correctly.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py', 'test_eda.py', 'eda/data_store.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:29,245,245 multiprocessing INFO [Function Call] [write_files] {"list_of_file_objects":[{"file_path":"test_data_store.py","file_contents":"import pytest\nfrom eda.data_store import add_data, get_data, delete_data\n\n# Test to ensure data is added correctly\ndef test_add_data():\n\tadd_data('test.csv', {'summary': 'test summary'})\n\tassert 'test.csv' in data_store\n\tassert data_store['test.csv'] == {'summary': 'test summary'}\n\n# Test to ensure data is retrieved correctly\ndef test_get_data():\n\tadd_data('test.csv', {'summary': 'test summary'})\n\tresult = get_data('test.csv')\n\tassert result == {'summary': 'test summary'}\n\n# Test to ensure data is deleted correctly\ndef test_delete_data():\n\tadd_data('test.csv', {'summary': 'test summary'})\n\tdelete_data('test.csv')\n\tassert 'test.csv' not in data_store\n\nif __name__ == '__main__':\n\tpytest.main()\n"}]} MainProcess| 2024-07-06 19:34:29,245,245 multiprocessing INFO [Tool] {"write_files_status": "success", "message": "write_files completed successfully."} MainProcess| 2024-07-06 19:34:29,245,245 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'eda' folder, create a file named 'data_store.py'. This file will mock a database using an in-memory dictionary to store the uploaded CSV files and their EDA results. Define functions to add, retrieve, and delete data from the mock database. Write tests to ensure the data store functions work correctly.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py', 'test_eda.py', 'eda/data_store.py', 'test_data_store.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:29,245,245 multiprocessing INFO [Progress: Step 4/10 | Retries: 0/30 | Token Capacity Used: 60.62% | Tokens remaining 3226] MainProcess| 2024-07-06 19:34:30,216,216 multiprocessing INFO [LLM RESPONSE MESSAGE] MainProcess| 2024-07-06 19:34:30,216,216 multiprocessing INFO [Function Call] [pytest_files] {"files_to_test":["test_data_store.py"]} MainProcess| 2024-07-06 19:34:30,220,220 multiprocessing INFO [System] Objective: Write code for a large system design task. Please note that the code should be fully functional. No placeholders. Only use the functions you have been provided with. Only use the `write_files` to output code. You must act autonomously and you will receive no human input at any stage. You have to return as output the complete code for completing this task, and correctly incorporate it into the existing code base. You always write out the whole file contents. You always indent code with tabs. Please always view the files before writing to them, to make sure you are writing to the correct files. When writing a test, make the filename start with the prefix 'test_'. Provide the minimal code necessary to achieve the task conditioned on the existing generated code---including changing the existing generated code. You cannot visualize any graphical output. You exist within a Actor Model machine, and when you list out steps, each step will be taken by a new separate sub-ChatGPT model. When you list out a sub-task steps, you can optionally specify the sub-task validation to check that it has been completed successfully. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Use the functions provided. When calling functions only provide a RFC8259 compliant JSON request following this format without deviation. MainProcess| 2024-07-06 19:34:30,220,220 multiprocessing INFO [User] You will get instructions for code to write. First lay out the names of the core classes, functions, methods that will be necessary, As well as a quick comment on their purpose. Do not comment on what every file does. Please note that the code should be fully functional. No placeholders. You will start with the "entrypoint" file, then go to the ones that are imported by that file, and so on. Please note that the code should be fully functional. No placeholders. Follow a language and framework appropriate best practice file naming convention. Make sure that files contain all imports, types etc. The code should be fully functional. Make sure that code in different files are compatible with each other. When writing code if you are unsure, write a plausible implementation. Include module dependency or package manager dependency definition file. Useful to know: For Python, you always create an appropriate requirements.txt file. Always implement the simplest implementation possible, and concise code, unless explicitly stated otherwise. Always add a comment briefly describing the purpose of the function definition. Add comments explaining very complex bits of logic. Always follow the best practices for the requested languages for folder/file structure and how to package the project. You can use any package and any other packages you wish to install. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. When writing a test, make the filename start with the prefix 'test_'. When putting files in folders, always be sure to include a file called __init__.py where relevant, or put all files in the same working directory. Always prefer the most simplest approach. Always add a readme on how to run the code, or a .sh file to run the code. If using pygame, design the game for "headless mode" testing, enabling operation without a GUI; structure the code for easy mocking of Pygame's display functions. As you cannot use any human input to test. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Python toolbelt preferences: - pytest - dataclasses - flask - pygame==2.1.2 Objective:``` create a eda app for csv file ``` Understand the problem, by creating an extremely detailed step-by-step plan, where each step is long (multiple sentences) and in total includes every single feature requirement specified above, feel free to copy directly from it. Use no more than 10 steps in the plan. Create additional tests, checks and evaluation at each step when applicable to help make an excellent code implementation, where all the code is fully functional. Use best software design practices, and you can output large amounts of code at once. Please include a last sentence to create and run tests when implementing or writing code in that same step. You will receive no human input at any stage, so you cannot use a human to test. Only create a detailed plan to begin with, which includes designing and running tests to check that they all pass. Add to the last step in the plan to add a readme on how to run the code, or a .sh file to run the code. Please be sure to include all of the specified feature requirements in the following plan. MainProcess| 2024-07-06 19:34:30,220,220 multiprocessing INFO [User] Objective: Execute sub task step:```In the 'eda' folder, create a file named 'data_store.py'. This file will mock a database using an in-memory dictionary to store the uploaded CSV files and their EDA results. Define functions to add, retrieve, and delete data from the mock database. Write tests to ensure the data store functions work correctly.```.\n\n Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py', 'test_eda.py']. Fully implement these features in the code, no placeholders. You can now optionally view the existing files if you need to view them to complete the current task step. You have a limited context window so be selective about which files you view, only view the files you think you might need to view. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Do not write tests for large numbers and large inputs, if they exist delete them. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Avoid making complicated tests. If a test repeatedly fails delete the test. \n\nSummary output of previous step: ""The core logic for performing EDA on uploaded CSV files has been implemented in `eda/eda.py`, and a function `perform_eda` has been defined to return a summary of the data, including basic statistics and visualizations. Tests for the `perform_eda` function have been written and successfully passed.""\n\nRespond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:30,220,220 multiprocessing INFO [Function Call] [view_files] {"files":["app.py","requirements.txt","eda/__init__.py","test_project_structure.py","test_app.py","eda/eda.py","test_eda.py"]} MainProcess| 2024-07-06 19:34:30,220,220 multiprocessing INFO [Tool] {"files": "app.py\n```python\nfrom flask import Flask, request, jsonify\nimport pandas as pd\nimport os\n\napp = Flask(__name__)\nUPLOAD_FOLDER = 'uploads'\nos.makedirs(UPLOAD_FOLDER, exist_ok=True)\napp.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER\n\n@app.route('/')\ndef home():\n\treturn 'Welcome to the EDA App!'\n\n@app.route('/upload', methods=['POST'])\ndef upload_file():\n\tif 'file' not in request.files:\n\t\treturn jsonify({'error': 'No file part'}), 400\n\tfile = request.files['file']\n\tif file.filename == '':\n\t\treturn jsonify({'error': 'No selected file'}), 400\n\tif file and file.filename.endswith('.csv'):\n\t\tfile_path = os.path.join(app.config['UPLOAD_FOLDER'], file.filename)\n\t\tfile.save(file_path)\n\t\treturn jsonify({'message': 'File uploaded successfully', 'file_path': file_path}), 200\n\telse:\n\t\treturn jsonify({'error': 'Invalid file type'}), 400\n\n@app.route('/eda', methods=['GET'])\ndef eda():\n\tfile_path = request.args.get('file_path')\n\tif not file_path or not os.path.exists(file_path):\n\t\treturn jsonify({'error': 'File not found'}), 400\n\ttry:\n\t\tdata = pd.read_csv(file_path)\n\t\tsummary = {\n\t\t\t'columns': list(data.columns),\n\t\t\t'shape': data.shape,\n\t\t\t'describe': data.describe().to_dict()\n\t\t}\n\t\treturn jsonify(summary), 200\n\texcept Exception as e:\n\t\treturn jsonify({'error': str(e)}), 500\n\nif __name__ == '__main__':\n\tapp.run(debug=True)\n\n```\n\nrequirements.txt\n```text\nflask\npytest\n```\n\neda/__init__.py\n```python\n\n```\n\ntest_project_structure.py\n```python\nimport os\nimport pytest\n\n# Test to ensure the project structure is correctly set up\n\ndef test_project_structure():\n\tassert os.path.isfile('app.py'), 'app.py does not exist'\n\tassert os.path.isfile('requirements.txt'), 'requirements.txt does not exist'\n\tassert os.path.isdir('eda'), 'eda directory does not exist'\n\tassert os.path.isfile('eda/__init__.py'), 'eda/__init__.py does not exist'\n\nif __name__ == '__main__':\n\tpytest.main()\n```\n\ntest_app.py\n```python\nimport pytest\nfrom app import app\n\n@pytest.fixture\n\ndef client():\n\tapp.config['TESTING'] = True\n\twith app.test_client() as client:\n\t\tyield client\n\n# Test to ensure the Flask app starts correctly and the home route is accessible\n\ndef test_home(client):\n\trv = client.get('/')\n\tassert rv.status_code == 200\n\tassert b'Welcome to the EDA App!' in rv.data\n\n# Test to ensure the upload route works correctly\n\ndef test_upload_file(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tassert rv.status_code == 200\n\tassert b'File uploaded successfully' in rv.data\n\n# Test to ensure the EDA route works correctly\n\ndef test_eda(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tfile_path = rv.json['file_path']\n\trv = client.get(f'/eda?file_path={file_path}')\n\tassert rv.status_code == 200\n\tassert b'columns' in rv.data\n\tassert b'shape' in rv.data\n\tassert b'describe' in rv.data\n\n```\n\neda/eda.py\n```python\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nfrom io import BytesIO\nimport base64\n\n# Function to perform EDA on a CSV file\ndef perform_eda(file_path):\n\tdata = pd.read_csv(file_path)\n\tsummary = {\n\t\t'columns': list(data.columns),\n\t\t'shape': data.shape,\n\t\t'describe': data.describe().to_dict(),\n\t\t'null_values': data.isnull().sum().to_dict(),\n\t\t'head': data.head().to_dict()\n\t}\n\n\t# Generate visualizations\n\tvisualizations = {}\n\n\t# Correlation heatmap\n\tplt.figure(figsize=(10, 8))\n\tsns.heatmap(data.corr(), annot=True, cmap='coolwarm')\n\tbuf = BytesIO()\n\tplt.savefig(buf, format='png')\n\tbuf.seek(0)\n\timage_base64 = base64.b64encode(buf.read()).decode('utf-8')\n\tvisualizations['correlation_heatmap'] = image_base64\n\tbuf.close()\n\tplt.close()\n\n\t# Pairplot\n\tplt.figure(figsize=(10, 8))\n\tsns.pairplot(data)\n\tbuf = BytesIO()\n\tplt.savefig(buf, format='png')\n\tbuf.seek(0)\n\timage_base64 = base64.b64encode(buf.read()).decode('utf-8')\n\tvisualizations['pairplot'] = image_base64\n\tbuf.close()\n\tplt.close()\n\n\tsummary['visualizations'] = visualizations\n\n\treturn summary\n\n# Test the perform_eda function\nif __name__ == \"__main__\":\n\t# Sample CSV data\n\tcsv_data = \"\"\"col1,col2,col3\\n1,2,3\\n4,5,6\\n7,8,9\\n10,11,12\\n\"\"\"\n\tfile_path = 'sample.csv'\n\twith open(file_path, 'w') as f:\n\t\tf.write(csv_data)\n\n\tsummary = perform_eda(file_path)\n\tprint(summary)\n\n```\n\ntest_eda.py\n```python\nimport pytest\nfrom eda.eda import perform_eda\nimport os\nimport pandas as pd\n\n# Test the perform_eda function with a sample CSV file\ndef test_perform_eda():\n\t# Sample CSV data\n\tcsv_data = \"\"\"col1,col2,col3\\n1,2,3\\n4,5,6\\n7,8,9\\n10,11,12\\n\"\"\"\n\tfile_path = 'test_sample.csv'\n\twith open(file_path, 'w') as f:\n\t\tf.write(csv_data)\n\n\tsummary = perform_eda(file_path)\n\n\tassert 'columns' in summary\n\tassert 'shape' in summary\n\tassert 'describe' in summary\n\tassert 'null_values' in summary\n\tassert 'head' in summary\n\tassert 'visualizations' in summary\n\tassert 'correlation_heatmap' in summary['visualizations']\n\tassert 'pairplot' in summary['visualizations']\n\n\t# Clean up\n\tos.remove(file_path)\n\nif __name__ == '__main__':\n\tpytest.main()\n\n```\n\n"} MainProcess| 2024-07-06 19:34:30,221,221 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'eda' folder, create a file named 'data_store.py'. This file will mock a database using an in-memory dictionary to store the uploaded CSV files and their EDA results. Define functions to add, retrieve, and delete data from the mock database. Write tests to ensure the data store functions work correctly.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py', 'test_eda.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:30,221,221 multiprocessing INFO [Function Call] [write_files] {"list_of_file_objects":[{"file_path":"eda/data_store.py","file_contents":"# This file mocks a database using an in-memory dictionary to store the uploaded CSV files and their EDA results.\n\ndata_store = {}\n\n\ndef add_data(file_name, eda_result):\n\t\"\"\"Add EDA result to the data store.\"\"\"\n\tdata_store[file_name] = eda_result\n\n\ndef get_data(file_name):\n\t\"\"\"Retrieve EDA result from the data store.\"\"\"\n\treturn data_store.get(file_name, None)\n\n\ndef delete_data(file_name):\n\t\"\"\"Delete EDA result from the data store.\"\"\"\n\tif file_name in data_store:\n\t\tdel data_store[file_name]\n\t\treturn True\n\treturn False\n"}]} MainProcess| 2024-07-06 19:34:30,221,221 multiprocessing INFO [Tool] {"write_files_status": "success", "message": "write_files completed successfully."} MainProcess| 2024-07-06 19:34:30,221,221 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'eda' folder, create a file named 'data_store.py'. This file will mock a database using an in-memory dictionary to store the uploaded CSV files and their EDA results. Define functions to add, retrieve, and delete data from the mock database. Write tests to ensure the data store functions work correctly.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py', 'test_eda.py', 'eda/data_store.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:30,221,221 multiprocessing INFO [Function Call] [write_files] {"list_of_file_objects":[{"file_path":"test_data_store.py","file_contents":"import pytest\nfrom eda.data_store import add_data, get_data, delete_data\n\n# Test to ensure data is added correctly\ndef test_add_data():\n\tadd_data('test.csv', {'summary': 'test summary'})\n\tassert 'test.csv' in data_store\n\tassert data_store['test.csv'] == {'summary': 'test summary'}\n\n# Test to ensure data is retrieved correctly\ndef test_get_data():\n\tadd_data('test.csv', {'summary': 'test summary'})\n\tresult = get_data('test.csv')\n\tassert result == {'summary': 'test summary'}\n\n# Test to ensure data is deleted correctly\ndef test_delete_data():\n\tadd_data('test.csv', {'summary': 'test summary'})\n\tdelete_data('test.csv')\n\tassert 'test.csv' not in data_store\n\nif __name__ == '__main__':\n\tpytest.main()\n"}]} MainProcess| 2024-07-06 19:34:30,221,221 multiprocessing INFO [Tool] {"write_files_status": "success", "message": "write_files completed successfully."} MainProcess| 2024-07-06 19:34:30,221,221 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'eda' folder, create a file named 'data_store.py'. This file will mock a database using an in-memory dictionary to store the uploaded CSV files and their EDA results. Define functions to add, retrieve, and delete data from the mock database. Write tests to ensure the data store functions work correctly.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py', 'test_eda.py', 'eda/data_store.py', 'test_data_store.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:30,221,221 multiprocessing INFO [Function Call] [pytest_files] {"files_to_test":["test_data_store.py"]} MainProcess| 2024-07-06 19:34:30,221,221 multiprocessing INFO [Tool] {"output": "Manual tests passed."} MainProcess| 2024-07-06 19:34:30,221,221 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'eda' folder, create a file named 'data_store.py'. This file will mock a database using an in-memory dictionary to store the uploaded CSV files and their EDA results. Define functions to add, retrieve, and delete data from the mock database. Write tests to ensure the data store functions work correctly.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py', 'test_eda.py', 'eda/data_store.py', 'test_data_store.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:30,221,221 multiprocessing INFO [Progress: Step 4/10 | Retries: 0/30 | Token Capacity Used: 64.70% | Tokens remaining 2892] MainProcess| 2024-07-06 19:34:31,176,176 multiprocessing INFO [LLM RESPONSE MESSAGE] MainProcess| 2024-07-06 19:34:31,176,176 multiprocessing INFO [Function Call] [sub_task_step_complete] {} MainProcess| 2024-07-06 19:34:31,180,180 multiprocessing INFO [System] Objective: Write code for a large system design task. Please note that the code should be fully functional. No placeholders. Only use the functions you have been provided with. Only use the `write_files` to output code. You must act autonomously and you will receive no human input at any stage. You have to return as output the complete code for completing this task, and correctly incorporate it into the existing code base. You always write out the whole file contents. You always indent code with tabs. Please always view the files before writing to them, to make sure you are writing to the correct files. When writing a test, make the filename start with the prefix 'test_'. Provide the minimal code necessary to achieve the task conditioned on the existing generated code---including changing the existing generated code. You cannot visualize any graphical output. You exist within a Actor Model machine, and when you list out steps, each step will be taken by a new separate sub-ChatGPT model. When you list out a sub-task steps, you can optionally specify the sub-task validation to check that it has been completed successfully. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Use the functions provided. When calling functions only provide a RFC8259 compliant JSON request following this format without deviation. MainProcess| 2024-07-06 19:34:31,180,180 multiprocessing INFO [User] You will get instructions for code to write. First lay out the names of the core classes, functions, methods that will be necessary, As well as a quick comment on their purpose. Do not comment on what every file does. Please note that the code should be fully functional. No placeholders. You will start with the "entrypoint" file, then go to the ones that are imported by that file, and so on. Please note that the code should be fully functional. No placeholders. Follow a language and framework appropriate best practice file naming convention. Make sure that files contain all imports, types etc. The code should be fully functional. Make sure that code in different files are compatible with each other. When writing code if you are unsure, write a plausible implementation. Include module dependency or package manager dependency definition file. Useful to know: For Python, you always create an appropriate requirements.txt file. Always implement the simplest implementation possible, and concise code, unless explicitly stated otherwise. Always add a comment briefly describing the purpose of the function definition. Add comments explaining very complex bits of logic. Always follow the best practices for the requested languages for folder/file structure and how to package the project. You can use any package and any other packages you wish to install. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. When writing a test, make the filename start with the prefix 'test_'. When putting files in folders, always be sure to include a file called __init__.py where relevant, or put all files in the same working directory. Always prefer the most simplest approach. Always add a readme on how to run the code, or a .sh file to run the code. If using pygame, design the game for "headless mode" testing, enabling operation without a GUI; structure the code for easy mocking of Pygame's display functions. As you cannot use any human input to test. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Python toolbelt preferences: - pytest - dataclasses - flask - pygame==2.1.2 Objective:``` create a eda app for csv file ``` Understand the problem, by creating an extremely detailed step-by-step plan, where each step is long (multiple sentences) and in total includes every single feature requirement specified above, feel free to copy directly from it. Use no more than 10 steps in the plan. Create additional tests, checks and evaluation at each step when applicable to help make an excellent code implementation, where all the code is fully functional. Use best software design practices, and you can output large amounts of code at once. Please include a last sentence to create and run tests when implementing or writing code in that same step. You will receive no human input at any stage, so you cannot use a human to test. Only create a detailed plan to begin with, which includes designing and running tests to check that they all pass. Add to the last step in the plan to add a readme on how to run the code, or a .sh file to run the code. Please be sure to include all of the specified feature requirements in the following plan. MainProcess| 2024-07-06 19:34:31,180,180 multiprocessing INFO [User] Objective: Execute sub task step:```In the 'eda' folder, create a file named 'data_store.py'. This file will mock a database using an in-memory dictionary to store the uploaded CSV files and their EDA results. Define functions to add, retrieve, and delete data from the mock database. Write tests to ensure the data store functions work correctly.```.\n\n Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py', 'test_eda.py']. Fully implement these features in the code, no placeholders. You can now optionally view the existing files if you need to view them to complete the current task step. You have a limited context window so be selective about which files you view, only view the files you think you might need to view. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Do not write tests for large numbers and large inputs, if they exist delete them. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Avoid making complicated tests. If a test repeatedly fails delete the test. \n\nSummary output of previous step: ""The core logic for performing EDA on uploaded CSV files has been implemented in `eda/eda.py`, and a function `perform_eda` has been defined to return a summary of the data, including basic statistics and visualizations. Tests for the `perform_eda` function have been written and successfully passed.""\n\nRespond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:31,180,180 multiprocessing INFO [Function Call] [view_files] {"files":["app.py","requirements.txt","eda/__init__.py","test_project_structure.py","test_app.py","eda/eda.py","test_eda.py"]} MainProcess| 2024-07-06 19:34:31,180,180 multiprocessing INFO [Tool] {"files": "app.py\n```python\nfrom flask import Flask, request, jsonify\nimport pandas as pd\nimport os\n\napp = Flask(__name__)\nUPLOAD_FOLDER = 'uploads'\nos.makedirs(UPLOAD_FOLDER, exist_ok=True)\napp.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER\n\n@app.route('/')\ndef home():\n\treturn 'Welcome to the EDA App!'\n\n@app.route('/upload', methods=['POST'])\ndef upload_file():\n\tif 'file' not in request.files:\n\t\treturn jsonify({'error': 'No file part'}), 400\n\tfile = request.files['file']\n\tif file.filename == '':\n\t\treturn jsonify({'error': 'No selected file'}), 400\n\tif file and file.filename.endswith('.csv'):\n\t\tfile_path = os.path.join(app.config['UPLOAD_FOLDER'], file.filename)\n\t\tfile.save(file_path)\n\t\treturn jsonify({'message': 'File uploaded successfully', 'file_path': file_path}), 200\n\telse:\n\t\treturn jsonify({'error': 'Invalid file type'}), 400\n\n@app.route('/eda', methods=['GET'])\ndef eda():\n\tfile_path = request.args.get('file_path')\n\tif not file_path or not os.path.exists(file_path):\n\t\treturn jsonify({'error': 'File not found'}), 400\n\ttry:\n\t\tdata = pd.read_csv(file_path)\n\t\tsummary = {\n\t\t\t'columns': list(data.columns),\n\t\t\t'shape': data.shape,\n\t\t\t'describe': data.describe().to_dict()\n\t\t}\n\t\treturn jsonify(summary), 200\n\texcept Exception as e:\n\t\treturn jsonify({'error': str(e)}), 500\n\nif __name__ == '__main__':\n\tapp.run(debug=True)\n\n```\n\nrequirements.txt\n```text\nflask\npytest\n```\n\neda/__init__.py\n```python\n\n```\n\ntest_project_structure.py\n```python\nimport os\nimport pytest\n\n# Test to ensure the project structure is correctly set up\n\ndef test_project_structure():\n\tassert os.path.isfile('app.py'), 'app.py does not exist'\n\tassert os.path.isfile('requirements.txt'), 'requirements.txt does not exist'\n\tassert os.path.isdir('eda'), 'eda directory does not exist'\n\tassert os.path.isfile('eda/__init__.py'), 'eda/__init__.py does not exist'\n\nif __name__ == '__main__':\n\tpytest.main()\n```\n\ntest_app.py\n```python\nimport pytest\nfrom app import app\n\n@pytest.fixture\n\ndef client():\n\tapp.config['TESTING'] = True\n\twith app.test_client() as client:\n\t\tyield client\n\n# Test to ensure the Flask app starts correctly and the home route is accessible\n\ndef test_home(client):\n\trv = client.get('/')\n\tassert rv.status_code == 200\n\tassert b'Welcome to the EDA App!' in rv.data\n\n# Test to ensure the upload route works correctly\n\ndef test_upload_file(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tassert rv.status_code == 200\n\tassert b'File uploaded successfully' in rv.data\n\n# Test to ensure the EDA route works correctly\n\ndef test_eda(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tfile_path = rv.json['file_path']\n\trv = client.get(f'/eda?file_path={file_path}')\n\tassert rv.status_code == 200\n\tassert b'columns' in rv.data\n\tassert b'shape' in rv.data\n\tassert b'describe' in rv.data\n\n```\n\neda/eda.py\n```python\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nfrom io import BytesIO\nimport base64\n\n# Function to perform EDA on a CSV file\ndef perform_eda(file_path):\n\tdata = pd.read_csv(file_path)\n\tsummary = {\n\t\t'columns': list(data.columns),\n\t\t'shape': data.shape,\n\t\t'describe': data.describe().to_dict(),\n\t\t'null_values': data.isnull().sum().to_dict(),\n\t\t'head': data.head().to_dict()\n\t}\n\n\t# Generate visualizations\n\tvisualizations = {}\n\n\t# Correlation heatmap\n\tplt.figure(figsize=(10, 8))\n\tsns.heatmap(data.corr(), annot=True, cmap='coolwarm')\n\tbuf = BytesIO()\n\tplt.savefig(buf, format='png')\n\tbuf.seek(0)\n\timage_base64 = base64.b64encode(buf.read()).decode('utf-8')\n\tvisualizations['correlation_heatmap'] = image_base64\n\tbuf.close()\n\tplt.close()\n\n\t# Pairplot\n\tplt.figure(figsize=(10, 8))\n\tsns.pairplot(data)\n\tbuf = BytesIO()\n\tplt.savefig(buf, format='png')\n\tbuf.seek(0)\n\timage_base64 = base64.b64encode(buf.read()).decode('utf-8')\n\tvisualizations['pairplot'] = image_base64\n\tbuf.close()\n\tplt.close()\n\n\tsummary['visualizations'] = visualizations\n\n\treturn summary\n\n# Test the perform_eda function\nif __name__ == \"__main__\":\n\t# Sample CSV data\n\tcsv_data = \"\"\"col1,col2,col3\\n1,2,3\\n4,5,6\\n7,8,9\\n10,11,12\\n\"\"\"\n\tfile_path = 'sample.csv'\n\twith open(file_path, 'w') as f:\n\t\tf.write(csv_data)\n\n\tsummary = perform_eda(file_path)\n\tprint(summary)\n\n```\n\ntest_eda.py\n```python\nimport pytest\nfrom eda.eda import perform_eda\nimport os\nimport pandas as pd\n\n# Test the perform_eda function with a sample CSV file\ndef test_perform_eda():\n\t# Sample CSV data\n\tcsv_data = \"\"\"col1,col2,col3\\n1,2,3\\n4,5,6\\n7,8,9\\n10,11,12\\n\"\"\"\n\tfile_path = 'test_sample.csv'\n\twith open(file_path, 'w') as f:\n\t\tf.write(csv_data)\n\n\tsummary = perform_eda(file_path)\n\n\tassert 'columns' in summary\n\tassert 'shape' in summary\n\tassert 'describe' in summary\n\tassert 'null_values' in summary\n\tassert 'head' in summary\n\tassert 'visualizations' in summary\n\tassert 'correlation_heatmap' in summary['visualizations']\n\tassert 'pairplot' in summary['visualizations']\n\n\t# Clean up\n\tos.remove(file_path)\n\nif __name__ == '__main__':\n\tpytest.main()\n\n```\n\n"} MainProcess| 2024-07-06 19:34:31,180,180 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'eda' folder, create a file named 'data_store.py'. This file will mock a database using an in-memory dictionary to store the uploaded CSV files and their EDA results. Define functions to add, retrieve, and delete data from the mock database. Write tests to ensure the data store functions work correctly.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py', 'test_eda.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:31,181,181 multiprocessing INFO [Function Call] [write_files] {"list_of_file_objects":[{"file_path":"eda/data_store.py","file_contents":"# This file mocks a database using an in-memory dictionary to store the uploaded CSV files and their EDA results.\n\ndata_store = {}\n\n\ndef add_data(file_name, eda_result):\n\t\"\"\"Add EDA result to the data store.\"\"\"\n\tdata_store[file_name] = eda_result\n\n\ndef get_data(file_name):\n\t\"\"\"Retrieve EDA result from the data store.\"\"\"\n\treturn data_store.get(file_name, None)\n\n\ndef delete_data(file_name):\n\t\"\"\"Delete EDA result from the data store.\"\"\"\n\tif file_name in data_store:\n\t\tdel data_store[file_name]\n\t\treturn True\n\treturn False\n"}]} MainProcess| 2024-07-06 19:34:31,181,181 multiprocessing INFO [Tool] {"write_files_status": "success", "message": "write_files completed successfully."} MainProcess| 2024-07-06 19:34:31,181,181 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'eda' folder, create a file named 'data_store.py'. This file will mock a database using an in-memory dictionary to store the uploaded CSV files and their EDA results. Define functions to add, retrieve, and delete data from the mock database. Write tests to ensure the data store functions work correctly.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py', 'test_eda.py', 'eda/data_store.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:31,181,181 multiprocessing INFO [Function Call] [write_files] {"list_of_file_objects":[{"file_path":"test_data_store.py","file_contents":"import pytest\nfrom eda.data_store import add_data, get_data, delete_data\n\n# Test to ensure data is added correctly\ndef test_add_data():\n\tadd_data('test.csv', {'summary': 'test summary'})\n\tassert 'test.csv' in data_store\n\tassert data_store['test.csv'] == {'summary': 'test summary'}\n\n# Test to ensure data is retrieved correctly\ndef test_get_data():\n\tadd_data('test.csv', {'summary': 'test summary'})\n\tresult = get_data('test.csv')\n\tassert result == {'summary': 'test summary'}\n\n# Test to ensure data is deleted correctly\ndef test_delete_data():\n\tadd_data('test.csv', {'summary': 'test summary'})\n\tdelete_data('test.csv')\n\tassert 'test.csv' not in data_store\n\nif __name__ == '__main__':\n\tpytest.main()\n"}]} MainProcess| 2024-07-06 19:34:31,181,181 multiprocessing INFO [Tool] {"write_files_status": "success", "message": "write_files completed successfully."} MainProcess| 2024-07-06 19:34:31,181,181 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'eda' folder, create a file named 'data_store.py'. This file will mock a database using an in-memory dictionary to store the uploaded CSV files and their EDA results. Define functions to add, retrieve, and delete data from the mock database. Write tests to ensure the data store functions work correctly.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py', 'test_eda.py', 'eda/data_store.py', 'test_data_store.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:31,181,181 multiprocessing INFO [Function Call] [pytest_files] {"files_to_test":["test_data_store.py"]} MainProcess| 2024-07-06 19:34:31,181,181 multiprocessing INFO [Tool] {"output": "Manual tests passed."} MainProcess| 2024-07-06 19:34:31,181,181 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'eda' folder, create a file named 'data_store.py'. This file will mock a database using an in-memory dictionary to store the uploaded CSV files and their EDA results. Define functions to add, retrieve, and delete data from the mock database. Write tests to ensure the data store functions work correctly.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py', 'test_eda.py', 'eda/data_store.py', 'test_data_store.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:31,181,181 multiprocessing INFO [Function Call] [sub_task_step_complete] {} MainProcess| 2024-07-06 19:34:31,181,181 multiprocessing INFO [Tool] {"status": "TASK_STEP_COMPLETE", "message": "All tests passed"} MainProcess| 2024-07-06 19:34:31,181,181 multiprocessing INFO [User] Please provide a one or two sentence summary of the output of this step, which is useful for the next step. Your response will be used when starting the next step without any of the previous messages. MainProcess| 2024-07-06 19:34:31,181,181 multiprocessing INFO [Progress: Step 4/10 | Retries: 0/30 | Token Capacity Used: 66.44% | Tokens remaining 2749] MainProcess| 2024-07-06 19:34:32,568,568 multiprocessing INFO [LLM RESPONSE MESSAGE] MainProcess| 2024-07-06 19:34:32,569,569 multiprocessing INFO [Assistant] The `eda/data_store.py` file has been created to mock a database using an in-memory dictionary, with functions to add, retrieve, and delete data. Tests for these functions have been written and successfully passed. MainProcess| 2024-07-06 19:34:32,569,569 multiprocessing INFO [STEP COMPLETE] sub step completed MainProcess| 2024-07-06 19:34:32,571,571 multiprocessing INFO [System] Objective: Write code for a large system design task. Please note that the code should be fully functional. No placeholders. Only use the functions you have been provided with. Only use the `write_files` to output code. You must act autonomously and you will receive no human input at any stage. You have to return as output the complete code for completing this task, and correctly incorporate it into the existing code base. You always write out the whole file contents. You always indent code with tabs. Please always view the files before writing to them, to make sure you are writing to the correct files. When writing a test, make the filename start with the prefix 'test_'. Provide the minimal code necessary to achieve the task conditioned on the existing generated code---including changing the existing generated code. You cannot visualize any graphical output. You exist within a Actor Model machine, and when you list out steps, each step will be taken by a new separate sub-ChatGPT model. When you list out a sub-task steps, you can optionally specify the sub-task validation to check that it has been completed successfully. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Use the functions provided. When calling functions only provide a RFC8259 compliant JSON request following this format without deviation. MainProcess| 2024-07-06 19:34:32,572,572 multiprocessing INFO [User] You will get instructions for code to write. First lay out the names of the core classes, functions, methods that will be necessary, As well as a quick comment on their purpose. Do not comment on what every file does. Please note that the code should be fully functional. No placeholders. You will start with the "entrypoint" file, then go to the ones that are imported by that file, and so on. Please note that the code should be fully functional. No placeholders. Follow a language and framework appropriate best practice file naming convention. Make sure that files contain all imports, types etc. The code should be fully functional. Make sure that code in different files are compatible with each other. When writing code if you are unsure, write a plausible implementation. Include module dependency or package manager dependency definition file. Useful to know: For Python, you always create an appropriate requirements.txt file. Always implement the simplest implementation possible, and concise code, unless explicitly stated otherwise. Always add a comment briefly describing the purpose of the function definition. Add comments explaining very complex bits of logic. Always follow the best practices for the requested languages for folder/file structure and how to package the project. You can use any package and any other packages you wish to install. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. When writing a test, make the filename start with the prefix 'test_'. When putting files in folders, always be sure to include a file called __init__.py where relevant, or put all files in the same working directory. Always prefer the most simplest approach. Always add a readme on how to run the code, or a .sh file to run the code. If using pygame, design the game for "headless mode" testing, enabling operation without a GUI; structure the code for easy mocking of Pygame's display functions. As you cannot use any human input to test. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Python toolbelt preferences: - pytest - dataclasses - flask - pygame==2.1.2 Objective:``` create a eda app for csv file ``` Understand the problem, by creating an extremely detailed step-by-step plan, where each step is long (multiple sentences) and in total includes every single feature requirement specified above, feel free to copy directly from it. Use no more than 10 steps in the plan. Create additional tests, checks and evaluation at each step when applicable to help make an excellent code implementation, where all the code is fully functional. Use best software design practices, and you can output large amounts of code at once. Please include a last sentence to create and run tests when implementing or writing code in that same step. You will receive no human input at any stage, so you cannot use a human to test. Only create a detailed plan to begin with, which includes designing and running tests to check that they all pass. Add to the last step in the plan to add a readme on how to run the code, or a .sh file to run the code. Please be sure to include all of the specified feature requirements in the following plan. MainProcess| 2024-07-06 19:34:32,572,572 multiprocessing INFO [User] Objective: Execute sub task step:```In the 'app.py' file, integrate the 'eda.py' and 'data_store.py' functionalities. Update the upload route to save the uploaded CSV file to the mock database and call the 'perform_eda' function. Update the route to display the EDA results to retrieve the results from the mock database. Write tests to ensure the integration works correctly and the EDA results are displayed as expected.```.\n\n Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py', 'test_eda.py', 'eda/data_store.py', 'test_data_store.py']. Fully implement these features in the code, no placeholders. You can now optionally view the existing files if you need to view them to complete the current task step. You have a limited context window so be selective about which files you view, only view the files you think you might need to view. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Do not write tests for large numbers and large inputs, if they exist delete them. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Avoid making complicated tests. If a test repeatedly fails delete the test. \n\nSummary output of previous step: ""The `eda/data_store.py` file has been created to mock a database using an in-memory dictionary, with functions to add, retrieve, and delete data. Tests for these functions have been written and successfully passed.""\n\nRespond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:32,572,572 multiprocessing INFO [Progress: Step 5/10 | Retries: 0/30 | Token Capacity Used: 21.85% | Tokens remaining 6402] MainProcess| 2024-07-06 19:34:33,875,875 multiprocessing INFO [LLM RESPONSE MESSAGE] MainProcess| 2024-07-06 19:34:33,875,875 multiprocessing INFO [Function Call] [view_files] {"files": ["app.py", "eda/eda.py", "eda/data_store.py"]} MainProcess| 2024-07-06 19:34:33,875,875 multiprocessing INFO [Function Call] [view_files] {"files": ["test_app.py", "test_eda.py", "test_data_store.py"]} MainProcess| 2024-07-06 19:34:33,877,877 multiprocessing INFO [System] Objective: Write code for a large system design task. Please note that the code should be fully functional. No placeholders. Only use the functions you have been provided with. Only use the `write_files` to output code. You must act autonomously and you will receive no human input at any stage. You have to return as output the complete code for completing this task, and correctly incorporate it into the existing code base. You always write out the whole file contents. You always indent code with tabs. Please always view the files before writing to them, to make sure you are writing to the correct files. When writing a test, make the filename start with the prefix 'test_'. Provide the minimal code necessary to achieve the task conditioned on the existing generated code---including changing the existing generated code. You cannot visualize any graphical output. You exist within a Actor Model machine, and when you list out steps, each step will be taken by a new separate sub-ChatGPT model. When you list out a sub-task steps, you can optionally specify the sub-task validation to check that it has been completed successfully. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Use the functions provided. When calling functions only provide a RFC8259 compliant JSON request following this format without deviation. MainProcess| 2024-07-06 19:34:33,878,878 multiprocessing INFO [User] You will get instructions for code to write. First lay out the names of the core classes, functions, methods that will be necessary, As well as a quick comment on their purpose. Do not comment on what every file does. Please note that the code should be fully functional. No placeholders. You will start with the "entrypoint" file, then go to the ones that are imported by that file, and so on. Please note that the code should be fully functional. No placeholders. Follow a language and framework appropriate best practice file naming convention. Make sure that files contain all imports, types etc. The code should be fully functional. Make sure that code in different files are compatible with each other. When writing code if you are unsure, write a plausible implementation. Include module dependency or package manager dependency definition file. Useful to know: For Python, you always create an appropriate requirements.txt file. Always implement the simplest implementation possible, and concise code, unless explicitly stated otherwise. Always add a comment briefly describing the purpose of the function definition. Add comments explaining very complex bits of logic. Always follow the best practices for the requested languages for folder/file structure and how to package the project. You can use any package and any other packages you wish to install. You cannot use any databases as none are setup in the local environment, instead mock a database with an in memory dictionary to store data. No data saved to disk will persist between steps or write operations. When writing a test, make the filename start with the prefix 'test_'. When putting files in folders, always be sure to include a file called __init__.py where relevant, or put all files in the same working directory. Always prefer the most simplest approach. Always add a readme on how to run the code, or a .sh file to run the code. If using pygame, design the game for "headless mode" testing, enabling operation without a GUI; structure the code for easy mocking of Pygame's display functions. As you cannot use any human input to test. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Python toolbelt preferences: - pytest - dataclasses - flask - pygame==2.1.2 Objective:``` create a eda app for csv file ``` Understand the problem, by creating an extremely detailed step-by-step plan, where each step is long (multiple sentences) and in total includes every single feature requirement specified above, feel free to copy directly from it. Use no more than 10 steps in the plan. Create additional tests, checks and evaluation at each step when applicable to help make an excellent code implementation, where all the code is fully functional. Use best software design practices, and you can output large amounts of code at once. Please include a last sentence to create and run tests when implementing or writing code in that same step. You will receive no human input at any stage, so you cannot use a human to test. Only create a detailed plan to begin with, which includes designing and running tests to check that they all pass. Add to the last step in the plan to add a readme on how to run the code, or a .sh file to run the code. Please be sure to include all of the specified feature requirements in the following plan. MainProcess| 2024-07-06 19:34:33,878,878 multiprocessing INFO [User] Objective: Execute sub task step:```In the 'app.py' file, integrate the 'eda.py' and 'data_store.py' functionalities. Update the upload route to save the uploaded CSV file to the mock database and call the 'perform_eda' function. Update the route to display the EDA results to retrieve the results from the mock database. Write tests to ensure the integration works correctly and the EDA results are displayed as expected.```.\n\n Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py', 'test_eda.py', 'eda/data_store.py', 'test_data_store.py']. Fully implement these features in the code, no placeholders. You can now optionally view the existing files if you need to view them to complete the current task step. You have a limited context window so be selective about which files you view, only view the files you think you might need to view. All tests should always be interpretable and you should be able to clearly reason what the correct answer is without any doubt. Do not write tests for large numbers and large inputs, if they exist delete them. If a test is failing the error could be the code, or the test is incorrect, so feel free to overwrite and change the tests when they are incorrect, to make all tests pass. Avoid making complicated tests. If a test repeatedly fails delete the test. \n\nSummary output of previous step: ""The `eda/data_store.py` file has been created to mock a database using an in-memory dictionary, with functions to add, retrieve, and delete data. Tests for these functions have been written and successfully passed.""\n\nRespond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:33,878,878 multiprocessing INFO [Function Call] [view_files] {"files": ["app.py", "eda/eda.py", "eda/data_store.py"]} MainProcess| 2024-07-06 19:34:33,878,878 multiprocessing INFO [Function Call] [view_files] {"files": ["test_app.py", "test_eda.py", "test_data_store.py"]} MainProcess| 2024-07-06 19:34:33,878,878 multiprocessing INFO [Tool] {"files": "app.py\n```python\nfrom flask import Flask, request, jsonify\nimport pandas as pd\nimport os\n\napp = Flask(__name__)\nUPLOAD_FOLDER = 'uploads'\nos.makedirs(UPLOAD_FOLDER, exist_ok=True)\napp.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER\n\n@app.route('/')\ndef home():\n\treturn 'Welcome to the EDA App!'\n\n@app.route('/upload', methods=['POST'])\ndef upload_file():\n\tif 'file' not in request.files:\n\t\treturn jsonify({'error': 'No file part'}), 400\n\tfile = request.files['file']\n\tif file.filename == '':\n\t\treturn jsonify({'error': 'No selected file'}), 400\n\tif file and file.filename.endswith('.csv'):\n\t\tfile_path = os.path.join(app.config['UPLOAD_FOLDER'], file.filename)\n\t\tfile.save(file_path)\n\t\treturn jsonify({'message': 'File uploaded successfully', 'file_path': file_path}), 200\n\telse:\n\t\treturn jsonify({'error': 'Invalid file type'}), 400\n\n@app.route('/eda', methods=['GET'])\ndef eda():\n\tfile_path = request.args.get('file_path')\n\tif not file_path or not os.path.exists(file_path):\n\t\treturn jsonify({'error': 'File not found'}), 400\n\ttry:\n\t\tdata = pd.read_csv(file_path)\n\t\tsummary = {\n\t\t\t'columns': list(data.columns),\n\t\t\t'shape': data.shape,\n\t\t\t'describe': data.describe().to_dict()\n\t\t}\n\t\treturn jsonify(summary), 200\n\texcept Exception as e:\n\t\treturn jsonify({'error': str(e)}), 500\n\nif __name__ == '__main__':\n\tapp.run(debug=True)\n\n```\n\neda/eda.py\n```python\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nfrom io import BytesIO\nimport base64\n\n# Function to perform EDA on a CSV file\ndef perform_eda(file_path):\n\tdata = pd.read_csv(file_path)\n\tsummary = {\n\t\t'columns': list(data.columns),\n\t\t'shape': data.shape,\n\t\t'describe': data.describe().to_dict(),\n\t\t'null_values': data.isnull().sum().to_dict(),\n\t\t'head': data.head().to_dict()\n\t}\n\n\t# Generate visualizations\n\tvisualizations = {}\n\n\t# Correlation heatmap\n\tplt.figure(figsize=(10, 8))\n\tsns.heatmap(data.corr(), annot=True, cmap='coolwarm')\n\tbuf = BytesIO()\n\tplt.savefig(buf, format='png')\n\tbuf.seek(0)\n\timage_base64 = base64.b64encode(buf.read()).decode('utf-8')\n\tvisualizations['correlation_heatmap'] = image_base64\n\tbuf.close()\n\tplt.close()\n\n\t# Pairplot\n\tplt.figure(figsize=(10, 8))\n\tsns.pairplot(data)\n\tbuf = BytesIO()\n\tplt.savefig(buf, format='png')\n\tbuf.seek(0)\n\timage_base64 = base64.b64encode(buf.read()).decode('utf-8')\n\tvisualizations['pairplot'] = image_base64\n\tbuf.close()\n\tplt.close()\n\n\tsummary['visualizations'] = visualizations\n\n\treturn summary\n\n# Test the perform_eda function\nif __name__ == \"__main__\":\n\t# Sample CSV data\n\tcsv_data = \"\"\"col1,col2,col3\\n1,2,3\\n4,5,6\\n7,8,9\\n10,11,12\\n\"\"\"\n\tfile_path = 'sample.csv'\n\twith open(file_path, 'w') as f:\n\t\tf.write(csv_data)\n\n\tsummary = perform_eda(file_path)\n\tprint(summary)\n\n```\n\neda/data_store.py\n```python\n# This file mocks a database using an in-memory dictionary to store the uploaded CSV files and their EDA results.\n\ndata_store = {}\n\n\ndef add_data(file_name, eda_result):\n\t\"\"\"Add EDA result to the data store.\"\"\"\n\tdata_store[file_name] = eda_result\n\n\ndef get_data(file_name):\n\t\"\"\"Retrieve EDA result from the data store.\"\"\"\n\treturn data_store.get(file_name, None)\n\n\ndef delete_data(file_name):\n\t\"\"\"Delete EDA result from the data store.\"\"\"\n\tif file_name in data_store:\n\t\tdel data_store[file_name]\n\t\treturn True\n\treturn False\n\n```\n\n"} MainProcess| 2024-07-06 19:34:33,878,878 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'app.py' file, integrate the 'eda.py' and 'data_store.py' functionalities. Update the upload route to save the uploaded CSV file to the mock database and call the 'perform_eda' function. Update the route to display the EDA results to retrieve the results from the mock database. Write tests to ensure the integration works correctly and the EDA results are displayed as expected.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py', 'test_eda.py', 'eda/data_store.py', 'test_data_store.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:33,878,878 multiprocessing INFO [Tool] {"files": "test_app.py\n```python\nimport pytest\nfrom app import app\n\n@pytest.fixture\n\ndef client():\n\tapp.config['TESTING'] = True\n\twith app.test_client() as client:\n\t\tyield client\n\n# Test to ensure the Flask app starts correctly and the home route is accessible\n\ndef test_home(client):\n\trv = client.get('/')\n\tassert rv.status_code == 200\n\tassert b'Welcome to the EDA App!' in rv.data\n\n# Test to ensure the upload route works correctly\n\ndef test_upload_file(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tassert rv.status_code == 200\n\tassert b'File uploaded successfully' in rv.data\n\n# Test to ensure the EDA route works correctly\n\ndef test_eda(client):\n\tdata = {\n\t\t'file': (io.BytesIO(b\"col1,col2\\n1,2\\n3,4\"), 'test.csv')\n\t}\n\trv = client.post('/upload', data=data, content_type='multipart/form-data')\n\tfile_path = rv.json['file_path']\n\trv = client.get(f'/eda?file_path={file_path}')\n\tassert rv.status_code == 200\n\tassert b'columns' in rv.data\n\tassert b'shape' in rv.data\n\tassert b'describe' in rv.data\n\n```\n\ntest_eda.py\n```python\nimport pytest\nfrom eda.eda import perform_eda\nimport os\nimport pandas as pd\n\n# Test the perform_eda function with a sample CSV file\ndef test_perform_eda():\n\t# Sample CSV data\n\tcsv_data = \"\"\"col1,col2,col3\\n1,2,3\\n4,5,6\\n7,8,9\\n10,11,12\\n\"\"\"\n\tfile_path = 'test_sample.csv'\n\twith open(file_path, 'w') as f:\n\t\tf.write(csv_data)\n\n\tsummary = perform_eda(file_path)\n\n\tassert 'columns' in summary\n\tassert 'shape' in summary\n\tassert 'describe' in summary\n\tassert 'null_values' in summary\n\tassert 'head' in summary\n\tassert 'visualizations' in summary\n\tassert 'correlation_heatmap' in summary['visualizations']\n\tassert 'pairplot' in summary['visualizations']\n\n\t# Clean up\n\tos.remove(file_path)\n\nif __name__ == '__main__':\n\tpytest.main()\n\n```\n\ntest_data_store.py\n```python\nimport pytest\nfrom eda.data_store import add_data, get_data, delete_data\n\n# Test to ensure data is added correctly\ndef test_add_data():\n\tadd_data('test.csv', {'summary': 'test summary'})\n\tassert 'test.csv' in data_store\n\tassert data_store['test.csv'] == {'summary': 'test summary'}\n\n# Test to ensure data is retrieved correctly\ndef test_get_data():\n\tadd_data('test.csv', {'summary': 'test summary'})\n\tresult = get_data('test.csv')\n\tassert result == {'summary': 'test summary'}\n\n# Test to ensure data is deleted correctly\ndef test_delete_data():\n\tadd_data('test.csv', {'summary': 'test summary'})\n\tdelete_data('test.csv')\n\tassert 'test.csv' not in data_store\n\nif __name__ == '__main__':\n\tpytest.main()\n\n```\n\n"} MainProcess| 2024-07-06 19:34:33,878,878 multiprocessing INFO [User] Has the sub task step been completed of:```In the 'app.py' file, integrate the 'eda.py' and 'data_store.py' functionalities. Update the upload route to save the uploaded CSV file to the mock database and call the 'perform_eda' function. Update the route to display the EDA results to retrieve the results from the mock database. Write tests to ensure the integration works correctly and the EDA results are displayed as expected.```.\n\n If yes, call the function `sub_task_step_complete`, otherwise reflect and correct the full code to complete the task. Note: Condition any new code files on the existing code files: ['app.py', 'requirements.txt', 'eda/__init__.py', 'test_project_structure.py', 'test_app.py', 'eda/eda.py', 'test_eda.py', 'eda/data_store.py', 'test_data_store.py']. Fully implement these features in the code, no placeholders.\n Respond now only with a function call of one of the following functions provided: `sub_task_step_complete`, `view_files`, `run_python_file`, `pytest_files`, `write_files`, `delete_files`, and if you want to output code only use the `write_files` function to output code. MainProcess| 2024-07-06 19:34:33,878,878 multiprocessing INFO [Progress: Step 5/10 | Retries: 0/30 | Token Capacity Used: 54.22% | Tokens remaining 3750] MainProcess| 2024-07-06 19:34:34,507,507 multiprocessing INFO [L2MAC][OpenAI API Request Error] ('Error code: 400 - {\'error\': {\'message\': "An assistant message with \'tool_calls\' must be followed by tool messages responding to each \'tool_call_id\'. The following tool_call_ids did not have response messages: call_Ma2hfBLbX9wA8lDM3ggq1TfQ", \'type\': \'invalid_request_error\', \'param\': \'messages.[5].role\', \'code\': None}}',) | num_retries: 0 / 10 MainProcess| 2024-07-06 19:34:34,507,507 multiprocessing INFO [L2MAC][OpenAI API Request Error] ('Error code: 400 - {\'error\': {\'message\': "An assistant message with \'tool_calls\' must be followed by tool messages responding to each \'tool_call_id\'. The following tool_call_ids did not have response messages: call_Ma2hfBLbX9wA8lDM3ggq1TfQ", \'type\': \'invalid_request_error\', \'param\': \'messages.[5].role\', \'code\': None}}',) | num_retries: 1 / 10 | Now sleeping for 3.6888437030500962 seconds MainProcess| 2024-07-06 19:34:38,980,980 multiprocessing INFO [L2MAC][OpenAI API Request Error] ('Error code: 400 - {\'error\': {\'message\': "An assistant message with \'tool_calls\' must be followed by tool messages responding to each \'tool_call_id\'. The following tool_call_ids did not have response messages: call_Ma2hfBLbX9wA8lDM3ggq1TfQ", \'type\': \'invalid_request_error\', \'param\': \'messages.[5].role\', \'code\': None}}',) | num_retries: 1 / 10 MainProcess| 2024-07-06 19:34:38,980,980 multiprocessing INFO [L2MAC][OpenAI API Request Error] ('Error code: 400 - {\'error\': {\'message\': "An assistant message with \'tool_calls\' must be followed by tool messages responding to each \'tool_call_id\'. The following tool_call_ids did not have response messages: call_Ma2hfBLbX9wA8lDM3ggq1TfQ", \'type\': \'invalid_request_error\', \'param\': \'messages.[5].role\', \'code\': None}}',) | num_retries: 2 / 10 | Now sleeping for 12.969638059071054 seconds MainProcess| 2024-07-06 19:34:48,139,139 multiprocessing INFO process shutting down