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  • Advanced Python for science
  • About this training
  • Preliminaries
    • About setting up a computer for programming and computing
    • Notes for Windows users
    • Notes for macOS users
    • Notes for Linux and WSL users
    • Python
    • Conda ecosystem
    • Editors and IDEs
    • Versioning tools
    • Clone the repo of this training
    • Check your installation
  • Appetizer with JupyterLite
    • First steps pure Python: function calls
    • First steps pure Python: objects, types and variables
    • First usage of Python libraries
  • Get and use the training source
  • Generalities on Python
    • Main characteristics
    • Python limitations
    • Different ways to use Python
    • Tools to develop Python code
  • Basic Pure Python
    • Simple types, variables
    • Strings, bytes and immutability
    • Conditions (if and match)
    • Lists and tuples
    • Indexing and slicing
    • Loops (while and for)
    • Exceptions and traceback
    • Read / write files
    • More data structures
  • Structure and reuse code
    • Functions (very basic)
    • Testing
    • Practice: Read corrupted files
    • Modules, packages and imports
    • Classes and objects
    • Practice: intro to classes
    • The standard library
    • Documentation
    • Back to functions (less basics)
  • Use, make & share Python software
    • Introduction: PyPI and friends
    • Conda & the conda-forge project
    • Global installation of Python apps
    • Using Third-party libraries
    • Modern Python packaging
  • Scientific Python (basics)
    • Python scientific ecosystem
    • Introduction to Numpy and the Python Array API standard
    • NumPy efficiency
    • Creation of Numpy arrays
    • Manipulating NumPy arrays
    • Introduction to Matplotlib and alternatives
    • Practice: image processing
    • Introduction to Pandas and alternatives
    • Practice: weather data
  • Recommended file formats
    • HDF5 and NetCDF files
  • Software engineering
    • Versioning
    • Continuous integration
    • Documentation
    • Debugging
    • Gradual typing
  • Intermediate pure Python
    • Decorators
    • OOP and magic methods
    • Generators
    • OOP and heritage
    • Define context managers
  • Performance optimization
    • Generalities on optimization in sequential
    • Profiling
  • Other languages and wrapping
    • Wrapping C and C++
    • Wrapping Rust
    • Wrapping Fortran
  • Parallelism
    • Threading
    • Concurrency
    • Multiprocessing
    • MPI and mpi4py
  • Tools for Python HPC
    • Cython
    • Pythran
    • Numba
    • JAX
    • Codon
  • Application on numerical kernels
    • NBody
    • DTW
  • A bit of Web
  • Native Python applications
  • GPU
  • Databases
  • Future & science fiction
    • Subinterpreters
    • Free Threading Python
    • Faster CPython and CPython JIT
    • HPy
    • Todo list
  • Repository
  • Open issue

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