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Python initiation training by py-edu-fr
Preliminaries
About setting up a computer for scientific computing
Notes for Windows users
Notes for macOS users
Notes for Linux and WSL users
Python
Conda ecosystem
Editors/IDE
Versioning tools
Clone the repo of this training
Appetizer with JupyterLite
Introduction to JupyterLab
First steps with pure Python
First usage of Python libraries
Generalities on Python
Main characteristics
Different ways to use Python
Tools to develop Python code
Basic Pure Python
Preliminaries
Strings, bytes and immutability
Conditions (
if
and
match
blocks)
Lists and tuples
Loops (while and for)
Exceptions and traceback
Read / write files
More data structures
Structure and reuse code
Functions (very basics)
Modules, packages and imports
Classes and objects
The standard library
Documentation and testing
Back to functions (less basics)
Using Python software
PyPI and PyPA
Conda and the conda-forge project
Global installations of Python tools
Using Python libraries
Basic packaging
Scientific Python (basics)
Python scientific ecosystem
Create your own working environment
Introduction to Numpy and the Python Array API standard
NumPy efficiency
Creation of Numpy arrays
Manipulating NumPy arrays
Introduction to Matplotlib and alternatives
Introduction to Pandas and alternatives
More
Introduction about performance
List of useful projects
List of web resources to find and get help
Tools based on AI to develop with Python
List of subjects not approached during this py-edu-fr training
Repository
Open issue
.md
.pdf
Classes and objects
Classes and objects
#
Very basics: only show how to define simple objects with
class
