Using NumPy C-API

• How to extend NumPy
  • Writing an extension module
  • Required subroutine
  • Defining functions
    • Functions without keyword arguments
    • Functions with keyword arguments
    • Reference counting
  • Dealing with array objects
    • Converting an arbitrary sequence object
    • Creating a brand-new ndarray
    • Getting at ndarray memory and accessing elements of the ndarray
  • Example
• Using Python as glue
  • Calling other compiled libraries from Python
  • Hand-generated wrappers
  • f2py
    • Creating source for a basic extension module
    • Creating a compiled extension module
    • Improving the basic interface
    • Inserting directives in Fortran source
    • A filtering example
    • Calling f2py from Python
    • Automatic extension module generation
    • Conclusion
  • Cython
    • Complex addition in Cython
    • Image filter in Cython
    • Conclusion
  • ctypes
    • Having a shared library
    • Loading the shared library
    • Converting arguments
    • Calling the function
    • Complete example
    • Conclusion
  • Additional tools you may find useful
    • SWIG
    • SIP
    • Boost Python
    • PyFort
• Writing your own ufunc
  • Creating a new universal function
  • Example Non-ufunc extension
  • Example NumPy ufunc for one dtype
  • Example NumPy ufunc with multiple dtypes
  • Example NumPy ufunc with multiple arguments/return values
  • Example NumPy ufunc with structured array dtype arguments
• Beyond the Basics
  • Iterating over elements in the array
    • Basic Iteration
    • Iterating over all but one axis
    • Iterating over multiple arrays
    • Broadcasting over multiple arrays
  • User-defined data-types
    • Adding the new data-type
    • Registering a casting function
    • Registering coercion rules
    • Registering a ufunc loop
  • Subtyping the ndarray in C
    • Creating sub-types
    • Specific features of ndarray sub-typing
      • The __array_finalize__ method
      • The __array_priority__ attribute
      • The __array_wrap__ method