TODO

Général:

✓ scinder Cours en "intro" et "avancé"
✓ introduire jupyter/jupyterlab
* Utiliser directive ipython
  (https://matplotlib.org/sampledoc/ipython_directive.html)

Cours avancé:

✓ Classes avancées: https://aboucaud.github.io/slides/2016/python-classes/#/
* Annotations (type hints: https://www.python.org/dev/peps/pep-0484/, variable
  annotations: https://www.python.org/dev/peps/pep-0526/)
* Data Classes (https://www.python.org/dev/peps/pep-0557/, ou
  https://pypi.org/project/dataclasses/ pour Python 3.6)
✓ f-strings (uniquement 3.6+) :pep:`498`
* distutils, setuptools (e.g. https://docs.python.org/3/distributing/)

  Ajouter une section "Installation et création de librairies" dans "Python
  avancé", avec exemples pip et setuptools. Environnements virtuels?

* Interface librairie/fonction C
* Interface web: https://atlastk.org/

Science:

* ipython avancé & jupyter notebooks/lab

  - https://www.dataquest.io/blog/jupyter-notebook-tutorial/
  - :pypi:`nbdime`: diffing and merging of Jupyter Notebooks
  - IDE en ligne: https://repl.it/

Science avancée:

* Format de données: HDF5 (h5py), FITS (astropy.io.fits), NetCDF
* optimisation / parallélisation
  (p.ex. https://chryswoods.com/parallel_python/index.html)
* Tuto Pandas (https://www.marsja.se/pandas-dataframe-read-csv-excel-subset/)
* Check https://github.com/paris-saclay-cds/python-workshop

* Python 3.6+
  - underscores: 1_000_000 et '{:_}' (:pep:`515`)

* Python 3.8+ (https://docs.python.org/3/whatsnew/3.8.html)
  - f-string {expr=}
  - assignment expression, opérateur morse (walrus) :=
  - positional-only parameters
  
Projets/exercices:

* jeu du taquin