Nuitka Release 0.4.0
This is to inform you about the new stable release of Nuitka. It is the extremely compatible Python compiler, “download now”.
This release brings massive progress on all fronts. The big highlight is of course: Full Python3.2 support. With this release, the test suite of CPython3.2 is considered passing when compiled with Nuitka.
Then lots of work on optimization and infrastructure. The major goal of this release was to get in shape for actual optimization. This is also why for the first time, it is tested that some things are indeed compile time optimized to spot regressions easier. And we are having performance diagrams, even if weak ones:
New Features
Python3.2 is now fully supported.
Fully correct
metaclass =
semantics now correctly supported. It had been working somewhat previously, but now all the corner cases are covered too.Keyword only parameters.
Annotations of functions return value and their arguments.
Exception causes, chaining, automatic deletion of exception handlers
as
values.Added support for starred assigns.
Unicode variable names are also supported, although it’s of course ugly, to find a way to translate these to C++ ones.
Bug fixes
Checking compiled code with
instance(some_function, types.FunctionType)
as “zope.interfaces” does, was causing compatibility problems. Now this kind of check passes for compiled functions too.The frame of modules had an empty locals dictionary, which is not compatible to CPython which puts the globals dictionary there too.
For nested exceptions and interactions with generator objects, the exceptions in
sys.exc_info()
were not always fully compatible. They now are.The
range
builtin was not raising exceptions if given arguments appeared to not have side effects, but were still illegal, e.g.range([], 1, -1)
was optimized away if the value was not used.Don’t crash on imported modules with syntax errors. Instead, the attempted recursion is simply not done.
Doing a
del
on__defaults
and__module__
of compiled functions was crashing. This was noticed by a Python3 test for__kwdefaults__
that exposed this compiled functions weakness.Wasn’t detecting duplicate arguments, if one of them was not a plain arguments. Star arguments could collide with normal ones.
The
__doc__
of classes is now only set, where it was in fact specified. Otherwise it only polluted the name space oflocals()
.When
return
from the tried statements of atry/finally
block, was overridden, by the final block, a reference was leaked. Example code:try: return 1 finally: return 2
Raising exception instances with value, was leaking references, and not raising the
TypeError
error it is supposed to do.When raising with multiple arguments, the evaluation order of them was not enforced, it now is. This fixes a reference leak when raising exceptions, where building the exception was raising an exception.
Optimization
Optimizing attribute access to compile time constants for the first time. The old registry had no actual user yet.
Optimizing subscript and slices for all compile time constants beyond constant values, made easy by using inheritance.
Built-in references now convert to strings directly, e.g. when used in a print statement. Needed for the testing approach “compiled file contains only prints with constant value”.
Optimizing calls to constant nodes directly into exceptions.
Optimizing built-in
bool
for arguments with known truth value. This would be creations of tuples, lists, and dictionaries.Optimizing
a is b
anda is not b
based on aliasing interface, which at this time effectively is limited to telling thata is a
is true anda is not a
is false, but this will expand.Added support for optimizing
hasattr
,getattr
, andsetattr
built-ins as well. Thehasattr
was needed for theclass
re-formulation of Python3 anyway.Optimizing
getattr
with string argument and no default to simple attribute access.Added support for optimizing
isinstance
built-in.Was handling “BreakException” and “ContinueException” in all loops that used
break
orcontinue
instead of only where necessary.When catching “ReturnValueException”, was raising an exception where a normal return was sufficient. Raising them now only where needed, which also means, function need not catch them ever.
Cleanups
The handling of classes for Python2 and Python3 have been re-formulated in Python more completely.
The calling of the determined “metaclass” is now in the node tree, so this call may possible to in-line in the future. This eliminated some static C++ code.
Passing of values into dictionary creation function is no longer using hard coded special parameters, but temporary variables can now have closure references, making this normal and visible to the optimization.
Class dictionary creation functions are therefore no longer as special as they used to be.
There is no class creation node anymore, it’s merely a call to
type
or the metaclass detected.
Re-formulated complex calls through helper functions that process the star list and dict arguments and do merges, checks, etc.
Moves much C++ code into the node tree visibility.
Will allow optimization to eliminate checks and to compile time merge, once in-line functions and loop unrolling are supported.
Added “return None” to function bodies without a an aborting statement at the end, and removed the hard coded fallback from function templates. Makes it explicit in the node tree and available for optimization.
Merged C++ classes for frame exception keeper with frame guards.
The exception is now saved in the compiled frame object, making it potentially more compatible to start with.
Aligned module and function frame guard usage, now using the same class.
There is now a clear difference in the frame guard classes. One is for generators and one is for functions, allowing to implement their different exception behavior there.
The optimization registries for calls, subscripts, slices, and attributes have been replaced with attaching them to nodes.
The ensuing circular dependency has been resolved by more local imports for created nodes.
The package “nuitka.transform.optimization.registries” is no more.
New per node methods “computeNodeCall”, “computeNodeSubscript”, etc. dispatch the optimization process to the nodes directly.
Use the standard frame guard code generation for modules too.
Added a variant “once”, that avoids caching of frames entirely.
The variable closure taking has been cleaned up.
Stages are now properly numbered.
Python3 only stage is not executed for Python2 anymore.
Added comments explaining things a bit better.
Now an early step done directly after building a tree.
The special code generation used for unpacking from iterators and catching “StopIteration” was cleaned up.
Now uses template, Generator functions, and proper identifiers.
The
return
statements in generators are now re-formulated intoraise StopIteration
for generators, because that’s what they really are. Allowed to remove special handling ofreturn
nodes in generators.The specialty of CPython2.6 yielding non-None values of lambda generators, was so far implemented in code generation. This was moved to tree building as a re-formulation, making it subject to normal optimization.
Mangling of attribute names in functions contained in classes, has been moved into the early tree building. So far it was done during code generation, making it invisible to the optimization stages.
Removed tags attribute from node classes. This was once intended to make up for non-inheritance of similar node kinds, but since we have function references, the structure got so clean, it’s no more needed.
Introduced new package
nuitka.tree
, where the building of node trees, and operations on them live, as well as recursion and variable closure.Removed
nuitka.transform
and move its former childrennuitka.optimization
andnuitka.finalization
one level up. The deeply nested structure turned out to have no advantage.Checks for Python version was sometimes “> 300”, where of course “>= 300” is the only thing that makes sense.
Split out helper code for exception raising from the handling of exception objects.
New Tests
The complete CPython3.2 test suite was adapted (no
__code__
, no__closure__
, etc.) and is now passing, but only without “–debug”, because otherwise some of the generated C++ triggers (harmless) warnings.Added new test suite designed to prove that expressions that are known to be compile time constant are indeed so. This works using the XML output done with
--dump-xml
and then searching it to only have print statements with constant values.Added new basic CPython3.2 test “Functions32” and “ParameterErrors32” to cover keyword only parameter handling.
Added tests to cover generator object and exception interactions.
Added tests to cover
try/finally
andreturn
in one or both branches correctly handling the references.Added tests to cover evaluation order of arguments when raising exceptions.
Organisational
Changed my email from GMX over to Gmail, the old one will still continue to work. Updated the copyright notices accordingly.
Uploaded Nuitka to PyPI as well.
Summary
This release marks a milestone. The support of Python3 is here. The re-formulation of complex calls, and the code generation improvements are quite huge. More re-formulation could be done for argument parsing, but generally this is now mostly complete.
The 0.3.x series had a lot releases. Many of which brought progress with
re-formulations that aimed at making optimization easier or possible.
Sometimes small things like making “return None” explicit. Sometimes
bigger things, like making class creations normal functions, or getting
rid of or
and and
. All of this was important ground work, to
make sure, that optimization doesn’t deal with complex stuff.
So, the 0.4.x series begins with this. The focus from now on can be
almost purely optimization. This release contains already some of it,
with frames being optimized away, with the assignment keepers from the
or
and and
re-formulation being optimized away. This will be
about achieving goals from the “ctypes” plan as discussed in the
Developer Manual.
Also the performance page will be expanded with more benchmarks and diagrams as I go forward. I have finally given up on “codespeed”, and do my own diagrams.