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flask_production_guide.txt
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flask_production_guide.txt
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# Flask_python Issues
## No.:
## Title:
## https links:
0.
Python Flask versus FastAPI: Which Should You Choose? - Apr 21, 2022 • 9 min read
https://www.netguru.com/blog/python-flask-versus-fastapi
1.
Python Web — 快速建置網站的Flask套件
https://seanyeh.medium.com/python-web-%E5%BF%AB%E9%80%9F%E5%BB%BA%E7%BD%AE%E7%B6%B2%E7%AB%99%E7%9A%84flask%E5%A5%97%E4%BB%B6-59318830bd63
2.
Quickstart
https://flask.palletsprojects.com/en/2.1.x/quickstart/
独立 WSGI 容器
https://dormousehole.readthedocs.io/en/latest/deploying/wsgi-standalone.html#gunicorn
部署到生产环境
https://flask-zh.readthedocs.io/tutorial/deploy/
3.
Python Web Flask — Flask-RESTful簡易CRUD API製作
https://medium.com/seaniap/python-web-flask-flask-restful%E7%B0%A1%E6%98%93crud-api%E8%A3%BD%E4%BD%9C-1a4023c1b768
4.
Python Flask 入門指南 : 輕量級網頁框架教學
https://devs.tw/post/448
5.
Python Web Flask — 使用靜態檔案
https://medium.com/seaniap/python-web-flask-%E4%BD%BF%E7%94%A8%E9%9D%9C%E6%85%8B%E6%AA%94%E6%A1%88-ac00e863a470
6.
Python Web Flask — Blueprints 解決大架構的網站
https://medium.com/seaniap/python-web-flask-blueprints-%E8%A7%A3%E6%B1%BA%E5%A4%A7%E6%9E%B6%E6%A7%8B%E7%9A%84%E7%B6%B2%E7%AB%99-1f9878312526
7.
Using async and await
https://flask.palletsprojects.com/en/2.1.x/async-await/?highlight=concurrency
Using async on Windows on Python 3.8
Python 3.8 has a bug related to asyncio on Windows.
If you encounter something like ValueError: set_wakeup_fd only works in main thread, please upgrade to Python 3.9.
8.
PowerShell does not support automatic activation of conda virtual environment
https://github.com/microsoft/vscode-python/issues/11638
https://github.com/Microsoft/vscode-python/issues/2898
9.
How does a Flask app serve multiple users/requests at once?
https://www.reddit.com/r/flask/comments/cesmvt/how_does_a_flask_app_serve_multiple_usersrequests/
10.
Handling Multiple Requests on Flask
https://medium.com/@dkhd/handling-multiple-requests-on-flask-60208eacc154
11.
Does anyone have experience running Flask at scale?
https://news.ycombinator.com/item?id=12467227
I used it once, for a small internal reporting service,
and was shocked to find that it was designed to process only a single request at a time, per process.
Is this a problem in the real world, or do decent caching rules and query design render it a non issue?
I ran a small site that was written in Flask and received couple of millions requests a day without any problems.
I used Nginx as a HTTP proxy and gunicorn for WSGI. It worked decently well, although it was pretty resources intensive (CPU, RAM).
Today you can use something like Caddy[0] and Gunicorn[1]
flasks builtin web server is for debug/development use. Run your flask apps under gunicorn, twisted web or any of the other supported servers in production.
Nobody ever uses the built-in Flask server for production. The common deployment pattern is to load the Flask app into a WSGI or asyncio serve, which will then handle requests with scalable threading/process models.
Look into uwsgi or gunicorn, and you'll never look back :)
12.
Flask 學習路線圖教學
https://github.com/hsuanchi/flask-template
13.
Async in Flask 2.0
https://testdriven.io/blog/flask-async/
Flask 2.0, which was released on May 11th, 2021, adds built-in support for asynchronous routes,
error handlers, before and after request functions, and teardown callbacks!
When Should Async Be Used?
While asynchronous execution tends to dominate discussions and generate headlines, it's not the best approach for every situation.
It's ideal for I/O-bound operations, when both of these are true:
There's a number of operations
Each operation takes less than a few seconds to finish
For example:
making HTTP or API calls
interacting with a database
working with the file system
It's not appropriate for background and long-running tasks as well as cpu-bound operations, like:
Running machine learning models
Processing images or PDFs
Performing backups
Such tasks would be better implemented using a task queue like Celery to manage separate long-running tasks.
Asynchronous HTTP Client/Server for asyncio and Python
https://docs.aiohttp.org/en/stable/
14.
The problem with Flask async views and async globals
https://dev.to/sethmlarson/the-problem-with-flask-async-views-and-async-globals-pl
15.
Flask想上線? 你還需要一些酷東西
https://minglunwu.github.io/notes/2021/flask_plus_wsgi.html
16.
Concurrency and async / await
https://fastapi.tiangolo.com/async/
Asynchronous Code
https://fastapi.tiangolo.com/async/#technical-details
Concurrency and Burgers
https://fastapi.tiangolo.com/async/#concurrency-and-burgers
Speeding Up Python with Concurrency, Parallelism, and asyncio
https://testdriven.io/blog/concurrency-parallelism-asyncio/
17.
ML model deployment option with concurrency (Flask + uWSGI)
https://medium.com/roonyx/ml-model-deployment-option-with-concurrency-flask-uwsgi-4aeafea0d07e
18.
Deploy Machine Learning Model using Flask
https://www.geeksforgeeks.org/deploy-machine-learning-model-using-flask/
19.
How to Deploy Machine Learning Models using Flask (with Code!)
https://www.analyticsvidhya.com/blog/2020/04/how-to-deploy-machine-learning-model-flask/
20.
An End-to-End Guide on Approaching an ML Problem and Deploying It Using Flask and Docker
https://www.analyticsvidhya.com/blog/2021/10/an-end-to-end-guide-on-approaching-an-ml-problem-and-deploying-it-using-flask-and-docker/
21.
Deploying Machine Learning Models using Flask
https://www.section.io/engineering-education/deploying-machine-learning-models-using-flask/
22.
推荐算法+可视化 vue+flask 爬虫大数据项目架构思路分享
https://segmentfault.com/a/1190000041557042
https://github.com/redcomet88/redcomet88
23.
Tutorial: How to use Vue components in Flask
https://www.reddit.com/r/flask/comments/qxmjxg/tutorial_how_to_use_vue_components_in_flask/
Web Development with Python and Vue.js Components
https://blog.reverielabs.com/python-vue-components/
Full-stack single page application with Vue.js and Flask
https://codeburst.io/full-stack-single-page-application-with-vue-js-and-flask-b1e036315532
https://github.com/oleg-agapov/flask-vue-spa
24.
WSGI
https://zh.wikipedia.org/zh-tw/Web%E6%9C%8D%E5%8A%A1%E5%99%A8%E7%BD%91%E5%85%B3%E6%8E%A5%E5%8F%A3
Web伺服器閘道介面（Python Web Server Gateway Interface，縮寫為WSGI）是為Python語言定義的Web伺服器和Web應用程式或框架之間的一種簡單而通用的介面
https://ithelp.ithome.com.tw/articles/10157271
Django 到底是怎麼用你的程式？這就要從 WSGI 開始說起。
絕大多數用 Python 寫成的網路服務，在本質上都是一個 WSGI 應用程式。WSGI，亦即「web server gateway interface」，
是一個由 Python 官方制定，用來統一伺服器程式與 Python 程式之間溝通方式的標準。
每個 WSGI 應用程式，都需要搭配一個 WSGI 伺服器來執行。當一個 WSGI 伺服器被啟動時，會進行以下的動作：
1)初始化。
2)設定環境變數等執行參數。
3)找到與它對應的 WSGI 應用程式。
4)進入一個迴圈，不斷等待來自網路的請求（requests）。
5)當得到請求時，呼叫 WSGI 應用程式，並告知該請求內部的參數與資料。
6)回到迴圈。
重複 2—4，直到使用者或系統要求它停止。
當你建立一個 Django 專案時，Django 會自動幫你產生一個 WSGI 應用程式。你寫的所有程式，都不會被直接使用，
而是由那個 WSGI 程式在執行時，視需求自動 import 元件來使用。
所以當你使用 Django 開發時，可能會覺得好像建立了一堆東西，但是它們都沒有被呼叫。
沒什麼好擔心的，呼叫它們是 WSGI 應用程式的工作！
25.
python3-部署Flask 到 Nginx (實際生產環境)
https://jeffwen0105.com/1759-2/
https://jeffwen0105.com/python-%E4%BD%BF%E7%94%A8flask-%E8%A3%BD%E4%BD%9C%E7%B0%A1%E5%96%AE%E7%9A%84%E7%99%BB%E5%85%A5%E5%8F%8A%E7%99%BB%E5%87%BA%E7%B6%B2%E7%AB%99/
26.
https://kknews.cc/zh-tw/code/jaxxmge.html
配置Supervisor環境
在production環境，起停和狀態的監控最好用supervisior之類的進程管理，監控工具。
supervisor是一個用python語言編寫的進程管理工具，supervisor 能將一個普通的命令行進程變為後台daemon，
它可以很方便的監聽、啟動、停止、重啟一個或多個進程。當一個進程意外被殺死，supervisor監聽到進程死後，
可以很方便的讓進程自動恢復，不再需要程式設計師或系統管理員自己編寫代碼來控制。可以運行在各種類unix的機器上。
1，安裝
sudo apt-get install supervisor #ubuntu下安裝
也可以用pip安裝，但是推薦用apt-get安裝，節省一些配置得步驟。
原文網址：https://kknews.cc/code/jaxxmge.html
將一個flask項目上傳到linux伺服器生產環境，總結起來分為以下幾步：
1，配置LNMP環境：首先得有linux伺服器，其次配置python環境，mysql環境，nginx環境。
這樣其實就已經可以上線運行了，可是，flask的內置伺服器不適合生產環境使用，這個時候需要加入真正的WSGI伺服器。
2，配置Gunicorn WSGI伺服器環境
有了真正伺服器，那麼還需要一個統一管理進程的工具，進行啟動，重啟，開啟多進程，集中式管理。
3，配置Supervisor進程管理工具環境
27.
使用 Flask 和 Vue.js 来构建全栈单页应用
https://learnku.com/python/t/24985
28.
Myths About Asynchronous PHP: It Is Not Truly Asynchronous
https://sergeyzhuk.me/2021/03/03/myths-about-asynchronous-php/
29.
Calling REST API of a Flask app from another Flask app
https://stackoverflow.com/questions/59549527/calling-rest-api-of-a-flask-app-from-another-flask-app
30.
Integrating an External API into a Flask Application
https://www.section.io/engineering-education/integrating-external-apis-with-flask/
31.
Complete Guide on Rest API with Python and Flask
https://www.analyticsvidhya.com/blog/2022/01/rest-api-with-python-and-flask/
32.
Flask: An Easy Access Door to API development
https://towardsdatascience.com/flask-an-easy-access-door-to-api-development-2147ae694ceb
https://github.com/tseth92/flask_simplified
33.
[Day 30] 使用 Heroku 部署機器學習 API
https://ithelp.ithome.com.tw/articles/10280857
[Day 29] 使用 Python Flask 架設 API 吧！
https://ithelp.ithome.com.tw/articles/10280422
[Day 28] 儲存訓練好的模型
https://ithelp.ithome.com.tw/articles/10280076
全民瘋AI系列2.0
https://github.com/andy6804tw/2021-13th-ironman
34.
Deploying-Flask-To-Heroku
https://github.com/twtrubiks/Deploying-Flask-To-Heroku/blob/master/README.md
35.
如何使用 Heroku 部屬一個 Web App 網頁應用程式
https://blog.techbridge.cc/2020/03/08/how-to-use-heroku-to-deploy-clear-mysql-db-web-app-tutorial/