Changelog

2017-01-05 Serge Guelton <serge.guelton@telecom-bretagne.eu>

  • Python 3 support
  • (unsound) Type Checker
  • Various bug fixes and perf improvement, as usual

2016-07-05 Serge Guelton <serge.guelton@telecom-bretagne.eu>

  • Fix install / setup minor issues
  • Restore OpenMP support
  • Fix GMP installation issue

2016-06-13 Serge Guelton <serge.guelton@telecom-bretagne.eu>

  • Better Jupyter Note book integration
  • Numpy Broadcasting support
  • Improved value binding analysis
  • Simple inlining optimization
  • Type engine improvement
  • Less fat in the generated modules
  • More and better support for various Numpy functions
  • Various performance improvement
  • Global variable handling, as constants only though

2016-01-05 Serge Guelton <serge.guelton@telecom-bretagne.eu>

  • IPython’s magic for pythran now supports extra compile flags
  • Pythran’s C++ output is compatible with Python3 and pythran3 can compile it!
  • More syntax checks (and less template traceback)
  • Improved UI (multiline pythran exports, better setup.py...)
  • Pythonic leaning / bugfixing (this tends to be a permanent item)
  • More generic support for numpy’s dtype
  • Simpler install (no more boost.python deps, nor nt2 configuration)
  • Faster compilation (no more boost.python deps, smarter pass manager)
  • Better testing (gcc + clang)

2015-10-13 Serge Guelton <serge.guelton@telecom-bretagne.eu>

  • Significantly decrease compilation time
  • Faster execution of numpy generalized slicing
  • Tentative conda support
  • Tentative Windows support (using Win Python)
  • Preserve original docstrings
  • Add __pythran__ global variable to pythran generated modules
  • Faster implementation of various itertools functions
  • Rely on distutils for module code compilation
  • Support most of numpy.random
  • Remove git and make dependency to install nt2
  • Proper pip support instead of distuils
  • Remove dependency to boost.python
  • Remove dependency to tcmalloc
  • Pythonic library cleaning (less dependencies / header / splitting / mrpropering)
  • More lazy computations
  • More numpy function support (including dot on matrices, linalg.norm, mean)
  • Lot of code cleaning / refactoring (both in Python and C++)
  • Many bugfixes, thanks to all the bug reporters!

2015-04-06 Serge Guelton <serge.guelton@telecom-bretagne.eu>

  • Various numpy.* function implementation improvement (incl. concatenate, str.join, itertools.combinations)
  • Better error detection during install step
  • 32 bit compatibility
  • Complete rewrite of the expression engine
  • Improved support of numpy extended expression
  • Better user feedback on invalid pythran spec
  • More efficient support of string litterals
  • Faster exponentiation when index is an integer
  • NT2 revision bump
  • No-copy list as numpy expression parameters
  • Accept C and fortran layout for input arrays
  • Range value analysis and boundcheck removal
  • Newaxis style indexing
  • Better array-of-complex support
  • Glimpses of python3 support
  • Support for importing user defined modules
  • Archlinux support
  • Accept strided array as exported function input

2014-10-22 Serge Guelton <serge.guelton@telecom-bretagne.eu>

  • Full SIMD support! Almost all numpy expressions are vectorized
  • Better memory management at the Python/C++ layer, esp. when sharing
  • Support named parameters
  • Better complex numbers support
  • A lot of internal code cleaning
  • Better code generation for regular loops
  • MacOS install guide & ArchLinux packages
  • Travis run the test suite, w and w/ SIMD, w and w/ OpenMP
  • Many performance improvements at the numpy expression level
  • Faster array copies, including slices
  • Much better constant folding
  • Distutils support through a PythranExtension
  • Improve implementation of many numpy functions
  • Improve forward substitution
  • Use most recent nt2 version
  • Make dependency on libgomp optional

2014-05-17 Serge Guelton <serge.guelton@telecom-bretagne.eu>

  • Improved C++ compilation time (twice as fast)
  • Efficient extended slicing
  • Support most numpy dtype ([u]int8,..., [u]int64, float32, float64)
  • Support indexing array through boolean array
  • Add a nice Pythran logo :-)
  • Improve validation a lot
  • Reduce native module loading overhead
  • Forward substitution implementation
  • More numpy support and many bug fixes!
  • Remove array auto vectorization/parallelization