06 January 2020

Nuitka Release 0.6.6

This is to inform you about the new stable release of Nuitka. It is the extremely compatible Python compiler, “download now”.

This release contains huge amounts of crucial bug fixes all across the board. There is also new optimization and many organizational improvements.

Bug Fixes

  • Fix, the top level module must not be bytecode. Otherwise we end up violating the requirement for an entry point on the C level.

  • Fix, avoid optimizing calls with default values used. This is not yet working and needed to be disabled for now.

  • Python3: Fix, missing keyword only arguments were not enforced to be provided keyword only, and were not giving the compatible error message when missing.

  • Windows: Find win32com DLLs too, even if they live in subfolders of site-packages, and otherwise not found. They are used by other DLLs that are found.

  • Standalone: Fixup for problem with standard library module in most recent Anaconda versions.

  • Scons: Fix, was using CXXFLAGS and CPPFLAGS even for the C compiler, which is wrong, and could lead to compilation errors.

  • Windows: Make --clang limited to clang-cl.exe as using it inside a MinGW64 is not currently supported.

  • Standalone: Added support for using lib2to2.pgen.

  • Standalone: Added paths used by openSUSE to the Tcl/Tk plugin.

  • Python3.6+: Fix, the __main__ package was None, but should be "" which allows relative imports from itself.

  • Python2: Fix, compile time optimization of floor division was using normal division.

  • Python3: Fix, some run time operations with known type shapes, were falsely reporting error message with unicode or long, which is of course not compatible.

  • Fix, was caching parent package, but these could be replaced e.g. due to bytecode demotion later, causing crashes during their optimization.

  • Fix, the value of __compiled__ could be corrupted when being deleted, which some modules wrappers do.

  • Fix, the value of __package__ could be corrupted when being deleted.

  • Scons: Make sure we can always output the compiler output, even if it has a broken encoding. This should resolve MSVC issues on non-English systems, e.g. German or Chinese.

  • Standalone: Support for newest sklearn was added.

  • macOS: Added resolver for run time variables in otool output, that gets PyQt5 to work on it again.

  • Fix, floor division of run time calculations with float values should not result in int, but float values instead.

  • Standalone: Enhanced support for boto3 data files.

  • Standalone: Added support for osgeo and gdal.

  • Windows: Fix, there were issues with spurious errors attaching the constants blob to the binary due to incorrect C types provided.

  • Distutils: Fix, need to allow / as separator for package names too.

  • Python3.6+: Fix reference losses in asyncgen when throwing exceptions into them.

  • Standalone: Added support for dill.

  • Standalone: Added support for scikit-image and skimage.

  • Standalone: Added support for weasyprint.

  • Standalone: Added support for dask.

  • Standalone: Added support for pendulum.

  • Standalone: Added support for pytz and pytzdata.

  • Fix, --python-flags=no_docstrings no longer implies disabling the assertions.

New Features

  • Added experimental support for Python 3.8, there is only very few things missing for full support.

  • Distutils: Added support for packages that are in a namespace and not just top level.

  • Distutils: Added support for single modules, not only packages, by supporting py_modules as well.

  • Distutils: Added support for distinct namespaces.

  • Windows: Compare Python and C compiler architecture for MSVC too, and catch the most common user error of mixing 32 and 64 bits.

  • Scons: Output variables used from the outside, so the debugging is easier.

  • Windows: Detect if clang installed inside MSVC automatically and use it if requested via --clang option. This is only the 32 bits variant, but currently the easy way to use it on Windows with Nuitka.

Optimization

  • Loop variables were analysed, but results were only available on the inside of the loop, preventing many optimization in these cases.

  • Added optimization for the abs built-in, which is also a numerical operator.

  • Added optimization for the all built-in, adding a new concept of iteration handle, for efficient checking that avoids looking at very large sequences, of which properties can still be known.

    all(range(1, 100000))  # no need to look at all of them

  • Added support for optimizing ImportError construction with keyword-only arguments. Previously only used without these were optimized.

    raise ImportError(path="lala", name="lele")  # now optimized

  • Added manual specialization for single argument calls, solving a TODO, as these will be very frequent.

  • Memory: Use single child form of node class where possible, the general class now raises an error if used with used with only one child name, this will use less memory at compile time.

  • Memory: Avoid list for non-local declarations in every function, these are very rare, only have it if absolutely necessary.

  • Generate more compact code for potential NameError exceptions being raised. These are very frequent, so this improves scalability with large files.

  • Python2: Annotate comparison of None with int and str types as not raising an exception.

  • Shared empty body functions and generators.

    One shared implementation for all empty functions removes that burden from the C compiler, and from the CPU instruction cache. All the shared C code does is to release its arguments, or to return an empty generator function in case of generator.

  • Memory: Added support for automatic releases of parameter variables from the node tree. These are normally released in a try finally block, however, this is now handled during code generation for much more compact C code generated.

  • Added specialization for int and long operations %, <<, >>, |, &, ^, **, @.

  • Added dedicated nodes for representing and optimizing based on shapes for all binary operations.

  • Disable gcc macro tracing unless in debug mode, to save memory during the C compilation.

  • Restored Python2 fast path for int with unknown object types, restoring performance for these.

Cleanups

  • Use dedicated ModuleName type that makes the tests that check if a given module name is inside a namespace as methods. This was hard to get right and as a result, adopting this fixed a few bugs and or inconsistent results.

  • Expand the use of nuitka.PostProcessing to cover all actions needed to get a runnable binary. This includes using install_name_tool on macOS standalone, as well copying the Python DLL for acceleration mode, cleaning the x bit for module mode. Previously only a part of these lived there.

  • Avoid including the definitions of dynamically created helper functions in the C code, instead just statically declare the ones expected to be there. This resolves Visual Code complaining about it, and should make life also easier for the compiler and caches like ccache.

  • Create more helper code in closer form to what clang-format does, so they are easier to compare to the static forms. We often create hard coded variants for few arguments of call functions, and generate them for many argument variations.

  • Moved setter/getter methods for Nuitka nodes consistently to the start of the node class definitions.

  • Generate C code much closer to what clang-format would change it to be.

  • Unified calling install_name_tool on macOS into one function that takes care of all the things, including e.g. making the file writable.

  • Debug output from scons should be more consistent and complete now.

  • Sort files for compilation in scons for better reproducible results.

  • Create code objects version independent, avoiding python version checks by pre-processor, hiding new stuff behind macros, that ignore things on older Python versions.

Tests

  • Added many more built-in tests for increased coverage of the newly covered ones, some of them being generic tests that allow to test all built-ins with typical uses.

  • Many tests have become more PyLint clean as a result of work with Visual Code and it complaining about them.

  • Added test to check PyPI health of top 50 packages. This is a major GSoC 2019 result.

  • Output the standalone directory contents for Windows too in case of a failure.

  • Added generated tests to fully cover operations on different type shapes and their errors as well as results for typical values.

  • Added support for testing against installed version of Nuitka.

  • Cleanup up tests, merging those for only Python 3.2 with 3.3 as we no longer support that version anyway.

  • Execute the Python3 tests for macOS on Travis too.

Organizational

  • The donation sponsored machine called donatix had to be replaced due to hardware breakage. It was replaced with a Raspberry-Pi 4.

  • Enhanced plugin documentation.

  • Added description of the git workflow to the Developer Manual.

  • Added checker script check-nuitka-with-codespell that reports typos in the source code for easier use of codespell with Nuitka.

  • Use newest PyLint and clang-format.

  • Also check plugin documentation files for ReST errors.

  • Much enhanced support for Visual Code configuration.

  • Trigger module code is now written into the build directory in debug mode, to aid debugging.

  • Added deep check function that descends into tuples to check their elements too.

Summary

This release comes after a long time of 4 months without a release, and has accumulated massive amounts of changes. The work on CPython 3.8 is not yet complete, and the performance work has yet to show actual fruit, but has also progressed on all fronts. Connecting the dots and pieces seems not far away.

bksahu’s GSoC warp up   Nuitka Release 0.6.7