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Welcome to the pystarters repository

COURSE DETAILS

COURSE TAs and contacts

  • Antonin Blot
  • George Dimitriadis
  • Jesse Geerts
  • Francesca Greenstreet
  • Stephen Lenzi
  • Goncalo Lopez
  • Arne Meyer
  • Maxime Rio
  • Charly Rousseau

Detailed schedule and weekly learning goals

Week 01, 27/02: Introduction to the pyclub, Python and the programming tools used in the class

  • Learn about the pyclub and the program for the year.
  • Understand the objectives of PyStarters.
  • Basic style - writing pythonic code (python3, import/packages, modules, enumerate …) to ease sharing.
  • Basic tools (pycharm, jupyter …).
  • The python interpreter.
  • The python documentation.
  • Setting up a python environment (hands on).
  • Introduction to next week’s exercises

Weeks 02 - 03, 13/03 - 27/03:Built in Python data types and Jupyter.

  • Learn about environments.
  • Work with anaconda.
  • Master Jupyter.
  • Learn to manipulate python built in variables efficiently.
  • Learn about ducktyping in python (e.g. for iterables)
  • introduction to the STL ?

Weeks 04 - 05, 10/04 - 14/04: Version control

  • Introduction to the concept of VCS.
  • Install and learn basic git usage.

Weeks 06 - 07, 24/04 - 08/05: Functions and Procedural programming

  • Modularising programs into functions
  • Pass by value vs pass by reference
  • The python import system
  • Docstrings

Weeks 08 - 09, 29/05 - 12/06: Python science libraries

  • Numpy (efficient array operations)
  • Scipy
  • Matplotlib (graphics)

Weeks 10 - 11, 26/06 - 10/07: Follow up of week 5

Weeks 12 - 13, 24/07 - 14/08: Object oriented programming

  • Introduction to OO programming in Python
  • Special methods and operator overloading

Weeks 14 - 15, 28/08 - 11/09: Exceptions and testing

  • Exception handling
  • Defining custom exceptions
  • Introduction to software testing
  • Unit testing with pytest

Weeks 16 - 17, 25/09 - 16/10: Packaging

  • distutils
  • setuptools
  • conda recipes

Weeks 18 - 21, 30/10, 13/11, 27/11, 11/12: Selection of topics between GUI programming, profiling and optimisation, scripting, R in python for statistics

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  • Jupyter Notebook 52.4%
  • Python 47.6%