Nuitka Release 0.6.10

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

This release comes with many new features, e.g. onefile support, as well as many new optimization and bug fixes.

Bug Fixes

• Fix, was memory leaking arguments of all complex call helper functions. Fixed in 0.6.9.6 already.

• Plugins: Fix, the dill-compat code needs to follow API change. Fixed in 0.6.9.7 already.

• Windows: Fixup for multiprocessing module and complex call helpers that could crash the program. Fixed in 0.6.9.7 already.

• Fix, the frame caching could leak memory when using caching for functions and generators used in multiple threads.

• Python3: Fix, importing an extension module below a compiled module was not possible in accelerated mode.

• Python3: Fix, keyword arguments for open built-in were not fully compatible.

• Fix, the scons python check should also not accept directories, otherwise strange misleading error will occur later.

• Windows: When Python is installed through a symbolic link, MinGW64 and Scons were having issues, added a workaround to resolve it even on Python2.

• Compatibility: Added support for co_freevars in code objects, e.g. newer matplotlib needs this.

• Standalone: Add needed data files for gooey. Fixed in 0.6.9.4 already.

• Scons: Fix, was not respecting --quiet option when running Scons. Fixed in 0.6.9.3 already.

• Scons: Fix, wasn’t automatically detecting Scons from promised paths. Fixed in 0.6.9.2 already.

• Scons: Fix, the clcache output parsing wasn’t robust enough. Fixed in 0.6.9.1 already.

• Python3.8: Ignore all non-strings provided in doc-string fashion, they are not to be considered.

• Fix, getattr, setattr and hasattr could not be used in finally clauses anymore. Fixed in 0.6.9.1 already.

• Windows: For Python3 enhanced compatibility for Windows no console mode, they need a sys.stdin or else e.g. input will not be compatible and raise RuntimeError.

New Features

• Added experimental support for Python 3.9, in such a way that the CPython3.8 test suite passes now, the 3.9 suite needs investigation still, so we might be missing new features.

• Added experimental support for Onefile mode with --onefile that uses AppImage on Linux and our own bootstrap binary on Windows. Other platforms are not supported at this time. With this, the standalone folder is packed into a single binary. The Windows variant currently doesn’t yet do any compression yet, but the Linux one does.

• Windows: Added downloading of ccache.exe, esp. as the other sources so far recommended were not working properly after updates. This is taken from the official project and should be good.

• Windows: Added downloading of matching MinGW64 C compiler, if no other was found, or that was has the wrong architecture, e.g. 32 bits where we need 64 bits.

• Windows: Added ability to copy icon resources from an existing binary with new option --windows-icon-from-exe.

• Windows: Added ability to provide multiple icon files for use with different desktop resolutions with new option --windows-icon-from-ico that got renamed to disambiguate from other icon options.

• Windows: Added support for requesting UAC admin right with new option --windows-uac-admin.

• Windows: Added support for requesting “uiaccess” rights with yet another new option --windows-uac-uiaccess.

• Windows: Added ability to specify version info to the binary. New options --windows-company-name, --windows-product-name, --windows-file-version, --windows-product-version, and --windows-file-description have been added. Some of these have defaults.

• Enhanced support for using the Win32 compiler of MinGW64, but it’s not perfect yet and not recommended.

• Windows: Added support for LTO mode for MSVC as well, this seems to allow more optimization.

• Plugins: The numpy plugin now handles matplotlib3 config files correctly.

Optimization

• Use less C variables in dictionary created, not one per key/value pair. This improved scalability of C compilation.

• Use common code for module variable access, leading to more compact code and enhanced scalability of C compilation.

• Use error exit during dictionary creation to release the dictionary, list, tuple, and set in case of an error occurring while they are still under construction. That avoids releases of it in error exists, reducing the generated code size by a lot. This improves scalability of C compilation for generating these.

• Annotate no exception raise for local variables of classes with know dict shape, to avoid useless error exits.

• Annotate no exception exit for staticmethod and classmethod as they do not check their arguments at all. This makes code generated for classes with these methods much more compact, mainly improving their scalability in C compilation.

• In code generation, prefer bool over nuitka_bool which allows to annotate exception result, leading to more compact code. Also cleanup so that code generation always go through the C type objects, rather than doing cases locally, adding a C type for bool.

• Use common code for C code handling const None return only, to cases where there is any immutable constant value returned, avoid code generation for this common case. Currently mutable constants are not handled, this may be added in the future.

• Annotate no exception for exception type checks in handlers for Python2 and no exception if the value has exception type shape for Python3. The exception type shape was newly added. This avoids useless exception handlers in most cases, where the provided exception is just a built-in exception name.

• Improve speed of often used compile time methods on nodes representing constant values, by making their implementation type specific to improve frontend compile time speed, we check e.g. mutable and hashable a lot.

• Provide truth value for variable references, enhancing loop optimization and merge value tracing, to also decide this correctly for values only read, and then changed through attribute, e.g. append on lists. This allows many more static optimization.

• Use staticmethod for methods in Nuitka nodes to achieve faster frontend compile times where possible.

• Use dedicated helper code for calls with single argument, avoiding the need have a call site local C array of size one, just to pass a pointer to it.

• Added handling of hash slot, to predict hashable keys for dictionary and sets.

• Share more slot provision for built-in type shapes from mixin classes, to get them more universally provided, even for special types, where their consideration is unusual.

• Trace “user provided” flag only for constants where it really matters, i.e. for containers and generally potentially large values, but not for every number or boolean value.

• Added lowering of bytearray constant values to bytes value iteration, while handling constant values for this optimization with dedicated code for improved frontend compilation speed.

• The dict built-in now annotates the dictionary type shape of its result.

• The wrapping side-effects node now passes on the type shape of the wrapped value, allowing for optimization of these too.

• Split slice nodes into variants with 1, 2 or 3 arguments, to avoid the overhead of determining which case we have, as well as to save a bit of memory, since these are more frequently used on Python3 for subscript operations. Also annotate their type shape, allowing more optimization.

• Faster dictionary lookups, esp. in cases where errors occur, because we were manually recreating a KeyError that is already provided by the dict implementation. This should also be faster, as it avoids a CPython API call overhead on the DLL and they can provide a reference or not for the returned value, simplifying using code.

• Faster dictionary containment checks, with our own dedicated helper, we can use code that won’t create an exception when an item is not present at all.

• Faster hash lookups with our own helper, separating cases where we want an exception for non-hashable values or not. These should also be faster to call.

• Avoid acquiring thread state in exception handling that checks if a StopIteration occurred, to improved speed on Python3, where is involves locking, but this needs to be applied way more often.

• Make sure checks to debug mode and full compatibility mode are done with the variables introduced, to avoid losing performance due to calls for Nuitka compile time enhancements. This was so far only done partially.

• Split constant references into two base classes, only one of them tracking if the value was provided by the user. This saves compile time memory and avoids the overhead to check if sizes are exceeded in cases they cannot possibly be so.

• The truth value of container creations is now statically known, because the empty container creation is no longer a possibility for these nodes, allowing more optimization for them.

• Optimize the bool built-in with no arguments directory, allow to simplify the node for single argument form to avoid checks if an argument was given.

• Added iteration handles for xrange values, and make them faster to create by being tied to the node type, avoiding shared types, instead using the mixin approach. This is in preparation to using them for standard iterator tracing as well. So far they are only used for any and all decision.

• Added detection if a iterator next can raise, using existing iterator checking which allows to remove needless checks and exception traces. Adding a code variant for calls to next that cannot fail, while tuning the code used for next and unpacking next, to use faster exception checking in the C code. This will speed up unpacking performance for some forms of unpacking from known sizes.

• Make sure to use the fastest tuple API possible in all of Nuitka, many place e.g. used PyTuple_Size, and one was in a performance critical part, e.g. in code that used when compiled functions as called as a method.

• Added optimized variant for _PyList_Extend for slightly faster unpacking code.

• Added optimized variant for PyList_Append for faster list contractions code.

• Avoid using RemoveFileSpec and instead provide our own code for that task, slightly reducing file size and avoiding to use the Shlapi link library.

Tests

• Made reflected test use common cleanup of test folder, which is more robust against Windows locking issues.

• Only output changed CPython output after the forced update of cached value was done, avoiding duplicate or outdated outputs.

• Avoid complaining about exceptions for in-place operations in case they are lowered to non-inplace operations and then raise unsupported, not worth the effort to retain original operator.

• Added generated test for subscript operations, also expanding coverage in generated tests by making sure, conditional paths are both taken by varying the cond value.

• Use our own code helper to check if an object has an attribute, which is faster, because it avoids creating exceptions in the first place, instead of removing them afterwards.

Cleanups

• Make sure that code generation always go through the C type objects rather than local elif casing of the type. This required cleaning up many of the methods and making code more abstract.

• Added base class for C types without reference counting, so they can share the code that ignores their handling.

• Remove getConstant for constant value nodes, use the more general getCompileTimeConstant instead, and provide quick methods that test for empty tuple or dict, to use for checking concrete values, e.g. with call operations.

• Unified container creation into always using a factory function, to be sure that existing container creations are not empty.

• Stop using @calledWithBuiltinArgumentNamesDecorator where possible, and instead make explicit wrapping or use correct names. This was used to allow e.g. an argument named list to be passed from built-in optimization, but that can be done in a cleaner fashion. Also aligned no attributes and the argument names, there was inconsistency there.

• Name mangling was done differently for attribute names and normal names and with non-shared code, and later than necessary, removing this as a step from variable closure taking after initial tree build.

• As part of the icon changes, now handled in Python code, we stop using the rc binary and handle all resources ourselves, allowing to remove that code from the Scons side of things.

• Moved file comparison code of standalone mode into file utils function for use in plugins as well.

• Unified how path concatenation is done in Nuitka helper code, there were more or less complete variants, this is making sure, the most capable form is used in all cases.

• Massive cleanup to our scons file, by moving out util code that only scons uses, hacks we apply to speed up scons, and more to separate modules with dedicated interfaces.

• When using enumerate we now provide start value of 1 where it is appropriate, e.g. when counting source code lines, rather than adding count+1 on every usage, making code more readable.

Organisational

• Do not recommend Anaconda on Windows anymore, it seems barely possible to get anything installed on it with a fresh download, due to the resolver literally working for days without finishing, and then reporting conflicts, it would only we usable when starting with Miniconda, but that seems less interesting to users, also gcc 5.2 is way too old these days.

• The commit hook should be reinstalled, since it got improved and adapted for newer git versions.

• Added link to donations to funding document, following a Github standard.

• Bumped requirements for development to the latest versions, esp. newer isort.

• Added a rough description of tests to do to add a new CPython test suite, to allow others to take this task in the future.

• Updated the git hook so that Windows and newest git works.

• Make it more clear in the documentation that Microsoft Appstore Python is not supported.

Summary

This is the big release in terms of scalability. The optimization in this release mostly focused on getting things that cause increased compile times sorted out. A very important fix avoids loop optimization to leak into global passes of all modules unnecessarily, but just as important, generated code now is much better for the C compiler to consume in observed problematic cases.

More optimization changes are geared towards reducing Nuitka frontend compile time, which could also be a lot in some cases, ending up specializing more constant nodes and how they expose themselves to optimization.

Other optimization came from supporting Python 3.9 and things come across during the implementation of that feature, e.g. to be able to make differences with unpacking error messages, we provide more code to handle it ourselves, and to manually optimize how to interact with e.g. list objects.

For Windows, the automatic download of ccache and a matching MinGW64 if none was found, is a new step, that should lower the barrier of entry for people who have no clue what a C compiler is. More changes are bound to come in this field with future releases, e.g. making a minimum version requirement for gcc on Windows that excludes unfit C compilers.

All in all, this release should be taken as a major cleanup, resolving many technical debts of Nuitka and preparing more optimization to come.

Previous: Nuitka Release 0.6.9   Next: Nuitka Release 0.6.11