First we need nuts & bolts.
- Conda [doc] is a package manager application (
pip+venv+virtualenvwrapper) - Anaconda [link] is a Python distribution which include more than 300 of the most popular Python packages for science, math, engineering, and data analysis.
Then we set up an environment for the tutorial:
$ conda create -n tutopython python=3.4
$ source activate tutopython
It's now time to install some packages :
$ conda install ipython numpy scipy matplotlib
and you're ready to play with ipython's command line interface.
$ ipython
Python 3.4.3 |Continuum Analytics, Inc.| (default, Mar 6 2015, 12:07:41)
Type "copyright", "credits" or "license" for more information.
IPython 4.0.0 -- An enhanced Interactive Python.
? -> Introduction and overview of IPython's features.
%quickref -> Quick reference.
help -> Python's own help system.
object? -> Details about 'object', use 'object??' for extra details.
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But a more powerful environment is available to carry out exploratory computation and data analysis : notebooks.
Notebooks are interactive computational environments, in which you can combine code execution, rich text, mathematics, plots and rich media. See http://ipython.org/notebook.html.
Notebooks are stored as JSON files with a .ipynb extension.
$ conda install ipython-notebook
$ ipython notebook
[I 09:30:28.237 NotebookApp] Using MathJax from CDN: https://cdn.mathjax.org/mathjax/latest/MathJax.js
[I 09:30:29.031 NotebookApp] Serving notebooks from local directory: /Users/honnorat/Documents/YeastLab/tutopython
[I 09:30:29.031 NotebookApp] 0 active kernels
[I 09:30:29.032 NotebookApp] The IPython Notebook is running at: http://localhost:8888/
[I 09:30:29.032 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).
[W 09:30:38.422 NotebookApp] Notebook tuto_filter.ipynb is not trusted
[I 09:30:39.040 NotebookApp] Kernel started: ce530cd1-a559-4e8e-895c-c9543ea61f4f
Now you can open your browser at the given address http://localhost:8888/ and create a new notebook.
- Numpy documentation : http://docs.scipy.org/doc/numpy/user/
- Scipy documentation : http://docs.scipy.org/doc/scipy/reference/