12 April 2024

Nuitka Release 2.2

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

This release focused on compatibility and significant optimization progress for loops, such as list operations within. The main line of change is to be able to support Python 3.12 in the next release.

Bug Fixes

  • Standalone: Added support for pypdfium2 package. Fixed in 2.1.1 already.

  • Standalone: Make cefpython3 work on Linux. Fixed in 2.1.1 already.

  • ArchLinux: Added platform linker option to be usable with their current Arch Python package. Fixed in 2.1.1 already.

  • Fix, ctypes.CDLL optimization used a misspelled argument name for use_last_error, such that keyword argument calls were statically optimized into TypeError at compile-time. Fixed in 2.1.1 already.

  • Fix, list.insert was not properly annotating exceptions. Raises by producing the inserted value raised or the index was not annotated and, therefore, could fail to be caught locally. Fixed in 2.1.1 already.

  • Standalone: Added support for selenium package. Fixed in 2.1.2 already.

  • Standalone: Added support for hydra package. Fixed in 2.1.2 already.

  • Standalone: Updated dotenv workaround for newer version. Fixed in 2.1.3 already.

  • Fix, PySide6 slots failed to be moved between threads. For that we need to make function renames visible in the owning class as well. Fixed in 2.1.3 already.

  • Standalone: Added support for win32com.server.register. Fixed in 2.1.3 already.

  • Standalone: Handle “string” import errors of uvicorn gracefully. Fixed in 2.1.3 already.

  • Fix, the dill-compat plugin needs also needs to expose the compiled type names as built-ins for the pickle module to find them.

  • Standalone: Added support for gruut package. Fixed in 2.1.3 already.

  • Standalone: Added support for newer toga to also include toga_winforms metadata. Fixed in 2.1.3 already.

  • Standalone: Added support for newer tensorflow package. Fixed in 2.1.4 already.

  • Standalone: Fix, matplotlib needs to emit a dependency on the backend to be included. Otherwise it could be missing at run-time in some cases. Fixed in 2.1.4 already.

  • Onefile: Respect XDG_CACHE_HOME variable on non-Windows platforms. Some users might configure that to not to be ~/.cache, respect that. Fixed in 2.1.4 already.

  • Python2: Some cases of list.insert were not properly handling all index types. Fixed in 2.1.4 already.

  • Fix, optimized list.remove failed to handle tuple arguments properly. Removing tuple values from lists could cause errors. Fixed in 2.1.4 already.

  • Standalone: Added missing implicit dependencies for pyarrow.datasets. Fixed in 2.1.4 already.

  • Standalone: Added support for dask.dataframe module. Fixed in 2.1.4 already.

  • Standalone: Added DLLs for tensorrt_libs package. Fixed in 2.1.4 already.

  • Standalone: Added missing metadata of numpy for xarray package. Fixed in 2.1.4 already.

  • Standalone: Added support for newer scipy. Fixed in 2.1.5 already.

  • Standalone: Fix, older gcc could give warning about C code to work with PYTHONPATH which caused build errors on older systems. Fixed in 2.1.5 already.

  • Fix, locals representing nodes could not be cloned, and as a result, some code re-formulations failed to compile in try constructs. Fixed in 2.1.5 already.

  • Standalone: Added data files for names package. Fixed in 2.1.5 already.

  • Standalone: Added data files for randomname package. Fixed in 2.1.5 already.

  • Standalone: Fix, the standalone standard library scan was not fully ignoring git folders, subfolders were still looked at and could cause issues. Fixed in 2.1.5 already.

  • Standalone: Added support for newer transformers. Fixed in 2.1.5 already.

  • Standalone: Add support for newer bitsandbytes. Fixed in 2.1.5 already.

  • Scons: Fix, when locating binaries, do not use directories but only files.

    A directory on PATH that was named gcc could be mistaken to be a gcc binary causing errors. Fixed in 2.1.6 already.

  • Windows: Fix, by default, scan only for .bin and .exe binaries for Nuitka Package Configuration EXE dependency patterns. This was the intended value, but it had not taken effect yet. Fixed in 2.1.6 already.

  • Fix, the __compiled__.containing_dir should be an absolute path. For it to be usable after a change of directory is done by the program that is required. Fixed in 2.1.6 already.

  • Standalone: Added support for more parts of networkx package. Fixed in 2.1.6 already.

  • Windows: Fix working with UNC paths and re-parse points at compile time.

    Now Nuitka should work with mapped and even unmapped to drive paths like \\some-hostname\unc-test as they are common in some VM setups.

  • Windows: Make sure the download path is an external use path in scons as well, otherwise the home directory could be an unusable path for MinGW64, causing it not to find files.

  • Standalone: Added missing dependency of sspilib that prevented requests-ntlm from working on Windows.

  • Python3.5+: Add support for using dictionary un-packings in class declarations. That is a rarely used in actual Python code, but was found missing by tests recently.

  • Python3.11: Fix, code objects co_qualname attribute was not actually the qualified name, but the same as co_name only.

  • Anaconda: Fix, must not consider the Anaconda lib directory as a system directory, because then those DLLs that are not included.

  • Fix, cannot trust dynamic hard modules as much otherwise, huggingface_hub.utils.tqdm ended up being a module and not the class it’s supposed to be.

  • macOS: Fix, on newer macOS the libc++ and libz DLLs cannot be found anymore, we need to ignore that actively as our code insists on full resolution to catch bugs.

  • Fix, support for newer zaber_motion was not really working.

  • Standalone: Added required data files for pyviz_comms.

  • Standalone: Added required data files for panel package.

  • Standalone: Added required data files for bokeh package.

  • Standalone: Fixup scipy for Anaconda.

  • Fix, need to make parent module usages more explicit.

    Otherwise, plugin mechanisms like no-follow from a parent module cannot affect its child modules, as they can end up being followed to only after them.

  • Fix, the dill-compat plugin in module mode cannot assume the main module name to be the one from compile time, need to look the actual one up at runtime.

New Features

  • Added experimental support for Python 3.12, this is passing basic tests, but known to crash a lot at run-time still, you are recommended to use pre-releases of Nuitka, as official support is not going to happen before 2.3 release.

  • Standalone: Added support for tensorflow.function JIT

    With preserved source code of decorated functions and we can provide it at run-time to tensorflow JIT so it can do its tracing executions.

  • For Nuitka Package Configuration, we now have change_class similar to change_function to replace a full class definition with something else, this can be used to modify classes to become stubs or even unusable.

  • For the experimental @pyqtSlot decorator, we also should handle the @asyncSlot the same way. Added in 2.1.1 already.

  • Added new kind of warning of plugin category and use it in the Nuitka Package Configuration to inform matplotlib users to select a GUI backend via plugin selection. Added in 2.1.4 already.

  • Zig: Added support for zig as CC value. Due to it not supporting C11 fully yet, we need to use the C++ workaround and cannot compile for Python 3.11 or higher yet.

  • For the __compiled__ value, we now have a __compiled__.main that is the name of the compiled module. For modules, Nuitka determines this at run time; in other modes, it is the name of the main module.

Optimization

  • Use set specific API in contains tests, rather than generic sequence one.

  • Lower value in something tests for known set and list values to use frozenset and tuple respectively.

  • Recognize exact type shapes of loop variables where possible. This enables appends to list to be optimized to their dedicated nodes among other things, with those often being a lot faster than generic code. This speeds up e.g. list append tests by a significant amount.

  • Optimization: Have dedicated helper for list.remove, such that it is not using a Python DLL call where that is slow.

  • ArchLinux: Enable static libpython by default, it is usable indeed. Added in 2.1.2 already.

  • Anti-Bloat: Avoid unittest usage in antlr package.

  • Anti-Bloat: Avoid IPython in celery package. Added in 2.1.2 already.

  • Anti-Bloat: Avoid using setuptools in transformers package for more modules. Added in 2.1.3 already.

  • Anti-Bloat: Avoid testing packages for newer tensorflow package as well. Added in 2.1.4 already.

  • Optimization: Avoid recompiling azure package which is not performance relevant. Added in 2.1.4 already.

  • Avoid packages owned by Nuitka plugins in matploblib backends unless the corresponding plugin is actually active. Added in 2.1.4 already.

  • Anti-Bloat: Avoid setuptools in deepspeed package. Added in 2.1.4 already.

  • Anti-Bloat: Avoid setuptools in transformers package. Added in 2.1.4 already.

  • Anti-Bloat: Avoid scipy usage causing torch or cupy usage. Added in 2.1.4 already.

  • Anti-Bloat: Recognize keras testing modules as unittest bloat.

  • Faster code generation due to enhancements in how identifiers are cached for module names and the indentation codes.

  • Optimization: Handle no_docstrings issue for torio package.

  • Anti-Bloat: Avoid IPython from imgui_bundle package.

  • Anti-Bloat: Remove testing module usage when dask is used.

  • Anti-Bloat: Avoid unitest usage in tf_keras package as well.

  • Anti-Bloat: Avoid IPython from bokeh package.

Organizational

  • UI: Catch conflicts between data files and EXE/DLLs/extension module filenames. Previously, you could overwrite binaries with data files, but that is now rejected as an explicit error.

  • Onefile: Avoid using the program name without suffix inside the dist folder, as that avoids collisions with data file directories of the same name, e.g., if the package and main binary have the same name, they would clash previously, but adding a .bin suffix to the binary avoids that entirely.

  • UI: Don’t force {VERSION} in specs to be resolved to four digits.

    That made it hard for users, who will be surprised to see 1.0 become 1.0.0.0 when that is only needed for Windows version information really.

  • UI: Catch wrong values for --jobs value sooner, negative and non-integer values error exit immediately. Added in 2.1.1 already.

  • UI: Nicer usage name when invoked with python -m nuitka

    The recommended form of invocation of Nuitka should not have an ugly invocation reference mentioning __main__.py instead put the python -m nuitka notion there.

  • UI: Reorder options for the plugins group to be more readable.

  • Plugins: Remove obsolete plugins from standard plugin documentation. Removed in 2.1.4 already.

  • UI: The Windows release was coming from the compiling Python and as such wrong, for example, Windows 11 always showed up as Windows 10, and some older versions of Python didn’t know Windows 10, yet, so this could be confusing in issue analysis.

  • UI: Do not warn about static libpython for Python debug mode compilation. It is misleading as often it doesn’t work for that configuration, and it’s only a distraction since debugging Python reference counts is not about performance. Changed in 2.1.4 already.

  • UI: Catch newlines in spec values. They break code C code generation potentially; they also are likely copy&paste mistakes that won’t do what the user expects. Added in 2.1.4 already.

  • Quality: Updated to the latest version of black.

  • Quality: Fix, isort and black can corrupt outputs, catch that.

  • Debugging: Generate Scons debug script

    It can serve to quickly re-execute a Scons compilation without re-executing Nuitka again. This is best used where there is no Python level change but only C changes and no expectation of producing a usable result.

    Because no post-processing is applied, and as a consequence this is not usable to produce binaries that work. In the future, we might expand this to be able to run post-processing still.

  • Debugging: Disabling all freelists is now honored for more code, tuples and empty dictionaries as well.

  • UI: Add macOS version to help output, which is sometimes vital for issue analysis.

  • Reports: Add the OS release to reports as well.

  • Reports: Exclude parent path imports from compilation reports for module usages that are found and end up not being excluded.

  • Watch: Reporting more problems, catching more errors, and adding the ability to create PRs from changes. However, it does not yet do it automatically.

  • Visual Code: Have plugins C files in the include path as well.

Tests

  • Tests: Fix, cannot assume setuptools to be installed, some RPM based systems don’t have it.

  • Run commercial code signing test only on Windows.

  • Allow for standalone testing file access to the Azure agent folders. For tests on Azure, it’s like the home directory.

  • Make sure optimization tests are named to make it clear that they are tests.

Cleanups

  • Remove useless --execute-with-pythonpath option, we don’t use that anymore at all.

Summary

The JIT mechanism added for tensorflow should be possible to generalize and will be applied to other JITs, like numba and others in the future as well.

The road to Python 3.12 is not fully complete, but the end feels closer now, and the subsequent release hopefully will add the official support for it.

Nuitka Release 2.1   Nuitka Release 2.3