It now raises an exception if sys.modules doesn't hold a strong
reference to the module.
Elaborate the comment explaining why a weak reference is used to
create a borrowed reference.
* Replace PyWeakref_GET_OBJECT() with _PyWeakref_GET_REF().
* _sqlite/blob.c now holds a strong reference to the blob object
while calling close_blob().
* _xidregistry_find_type() now holds a strong reference to registered
while using it.
finalize_modules_clear_weaklist() now holds a strong reference to the
module longer than before: replace PyWeakref_GET_OBJECT() with
_PyWeakref_GET_REF().
* Add tests on PyImport_AddModuleRef(), PyImport_AddModule() and
PyImport_AddModuleObject().
* pythonrun.c: Replace Py_XNewRef(PyImport_AddModule(name)) with
PyImport_AddModuleRef(name).
Refactor PyRun_InteractiveOneObjectEx(), _PyRun_SimpleFileObject()
and PyRun_SimpleStringFlags():
* Keep a strong reference to the __main__ module while using its
dictionary (PyModule_GetDict()). Use PyImport_AddModule() with
Py_XNewRef().
* Declare variables closer to where they are defined.
* Rename variables to use name longer than 1 character.
* Add pyrun_one_parse_ast() sub-function.
* Add table describing possible executable classes for out-of-process debuggers.
* Remove shim code object creation code as it is no longer needed.
* Make lltrace a bit more robust w.r.t. non-standard frames.
This fixes a race during import. The existing _PyRuntimeState.imports.pkgcontext is shared between interpreters, and occasionally this would cause a crash when multiple interpreters were importing extensions modules at the same time. To solve this we add a thread-local variable for the value. We also leave the existing state (and infrequent race) in place for platforms that do not support thread-local variables.
For a while now, pending calls only run in the main thread (in the main interpreter). This PR changes things to allow any thread run a pending call, unless the pending call was explicitly added for the main thread to run.
The risk of a race with this state is relatively low, but we play it safe anyway. We do avoid using the lock in performance-sensitive cases where the risk of a race is very, very low.
This avoids the problematic race in drop_gil() by skipping the FORCE_SWITCHING code there for finalizing threads.
(The idea for this approach came out of discussions with @markshannon.)
Remove functions in the C API:
* PyEval_AcquireLock()
* PyEval_ReleaseLock()
* PyEval_InitThreads()
* PyEval_ThreadsInitialized()
But keep these functions in the stable ABI.
Mention "make regen-limited-abi" in "make regen-all".
Remove the following old functions to configure the Python
initialization, deprecated in Python 3.11:
* PySys_AddWarnOptionUnicode()
* PySys_AddWarnOption()
* PySys_AddXOption()
* PySys_HasWarnOptions()
* PySys_SetArgvEx()
* PySys_SetArgv()
* PySys_SetPath()
* Py_SetPath()
* Py_SetProgramName()
* Py_SetPythonHome()
* Py_SetStandardStreamEncoding()
* _Py_SetProgramFullPath()
Most of these functions are kept in the stable ABI, except:
* Py_SetStandardStreamEncoding()
* _Py_SetProgramFullPath()
Update Doc/extending/embedding.rst and Doc/extending/extending.rst to
use the new PyConfig API.
_testembed.c:
* check_stdio_details() now sets stdio_encoding and stdio_errors
of PyConfig.
* Add definitions of functions removed from the API but kept in the
stable ABI.
* test_init_from_config() and test_init_read_set() now use
PyConfig_SetString() instead of PyConfig_SetBytesString().
Remove _Py_ClearStandardStreamEncoding() internal function.
Deprecate the old Py_UNICODE and PY_UNICODE_TYPE types in the C API:
use wchar_t instead.
Replace Py_UNICODE with wchar_t in multiple C files.
Co-authored-by: Inada Naoki <songofacandy@gmail.com>
* Remove the Lib/test/imghdrdata/ directory.
* Copy 5 pictures (gif, png, ppm, pgm, xbm) from removed
Lib/test/imghdrdata/ to a new Lib/test/tkinterdata/ directory.
* Update Sphinx from 4.5 to 6.2 in Doc/requirements.txt.
* socket_helper.transient_internet() no longer imports nntplib to
catch nntplib.NNTPTemporaryError.
* ssltests.py no longer runs test_nntplib.
* "make quicktest" no longer runs test_nntplib.
* WASM: remove nntplib from OMIT_NETWORKING_FILES.
* Remove mentions to nntplib in the email documentation.
This commit replaces the Python implementation of the tokenize module with an implementation
that reuses the real C tokenizer via a private extension module. The tokenize module now implements
a compatibility layer that transforms tokens from the C tokenizer into Python tokenize tokens for backward
compatibility.
As the C tokenizer does not emit some tokens that the Python tokenizer provides (such as comments and non-semantic newlines), a new special mode has been added to the C tokenizer mode that currently is only used via
the extension module that exposes it to the Python layer. This new mode forces the C tokenizer to emit these new extra tokens and add the appropriate metadata that is needed to match the old Python implementation.
Co-authored-by: Pablo Galindo <pablogsal@gmail.com>
This implements PEP 695, Type Parameter Syntax. It adds support for:
- Generic functions (def func[T](): ...)
- Generic classes (class X[T](): ...)
- Type aliases (type X = ...)
- New scoping when the new syntax is used within a class body
- Compiler and interpreter changes to support the new syntax and scoping rules
Co-authored-by: Marc Mueller <30130371+cdce8p@users.noreply.github.com>
Co-authored-by: Eric Traut <eric@traut.com>
Co-authored-by: Larry Hastings <larry@hastings.org>
Co-authored-by: Alex Waygood <Alex.Waygood@Gmail.com>
When monitoring LINE events, instrument all instructions that can have a predecessor on a different line.
Then check that the a new line has been hit in the instrumentation code.
This brings the behavior closer to that of 3.11, simplifying implementation and porting of tools.
This PR removes `_Py_dg_stdnan` and `_Py_dg_infinity` in favour of
using the standard `NAN` and `INFINITY` macros provided by C99.
This change has the side-effect of fixing a bug on MIPS where the
hard-coded value used by `_Py_dg_stdnan` gave a signalling NaN
rather than a quiet NaN.
---------
Co-authored-by: Mark Dickinson <dickinsm@gmail.com>
This is the culmination of PEP 684 (and of my 8-year long multi-core Python project)!
Each subinterpreter may now be created with its own GIL (via Py_NewInterpreterFromConfig()). If not so configured then the interpreter will share with the main interpreter--the status quo since subinterpreters were added decades ago. The main interpreter always has its own GIL and subinterpreters from Py_NewInterpreter() will always share with the main interpreter.
We also add PyInterpreterState.ceval.own_gil to record if the interpreter actually has its own GIL.
Note that for now we don't actually respect own_gil; all interpreters still share the one GIL. However, PyInterpreterState.ceval.own_gil does reflect PyInterpreterConfig.own_gil. That lie is a temporary one that we will fix when the GIL really becomes per-interpreter.
Here we are doing no more than adding the value for Py_mod_multiple_interpreters and using it for stdlib modules. We will start checking for it in gh-104206 (once PyInterpreterState.ceval.own_gil is added in gh-104204).
In preparation for a per-interpreter GIL, we add PyInterpreterState.ceval.gil, set it to the shared GIL for each interpreter, and use that rather than using _PyRuntime.ceval.gil directly. Note that _PyRuntime.ceval.gil is still the actual GIL.
This function no longer makes sense, since its runtime parameter is
no longer used. Use directly _PyThreadState_GET() and
_PyInterpreterState_GET() instead.
This breaks the tests, but we are keeping it as a separate commit so
that the move operation and editing of the moved files are separate, for
a cleaner history.
We also expose PyInterpreterConfig. This is part of the PEP 684 (per-interpreter GIL) implementation. We will add docs as soon as we can.
FYI, I'm adding the new config field for per-interpreter GIL in gh-99114.
This is strictly about moving the "obmalloc" runtime state from
`_PyRuntimeState` to `PyInterpreterState`. Doing so improves isolation
between interpreters, specifically most of the memory (incl. objects)
allocated for each interpreter's use. This is important for a
per-interpreter GIL, but such isolation is valuable even without it.
FWIW, a per-interpreter obmalloc is the proverbial
canary-in-the-coalmine when it comes to the isolation of objects between
interpreters. Any object that leaks (unintentionally) to another
interpreter is highly likely to cause a crash (on debug builds at
least). That's a useful thing to know, relative to interpreter
isolation.
This speeds up `super()` (by around 85%, for a simple one-level
`super().meth()` microbenchmark) by avoiding allocation of a new
single-use `super()` object on each use.
Deep-frozen code objects are cannot be shared (currently) by
interpreters, due to how adaptive specialization can modify the
bytecodes. We work around this by only using the deep-frozen objects in
the main interpreter. This does incur a performance penalty for
subinterpreters, which we may be able to resolve later.
We replace _PyRuntime.tstate_current with a thread-local variable. As part of this change, we add a _Py_thread_local macro in pyport.h (only for the core runtime) to smooth out the compiler differences. The main motivation here is in support of a per-interpreter GIL, but this change also provides some performance improvement opportunities.
Note that we do not provide a fallback to the thread-local, either falling back to the old tstate_current or to thread-specific storage (PyThread_tss_*()). If that proves problematic then we can circle back. I consider it unlikely, but will run the buildbots to double-check.
Also note that this does not change any of the code related to the GILState API, where it uses a thread state stored in thread-specific storage. I suspect we can combine that with _Py_tss_tstate (from here). However, that can be addressed separately and is not urgent (nor critical).
(While this change was mostly done independently, I did take some inspiration from earlier (~2020) work by @markshannon (main...markshannon:threadstate_in_tls) and @vstinner (#23976).)
This is the implementation of PEP683
Motivation:
The PR introduces the ability to immortalize instances in CPython which bypasses reference counting. Tagging objects as immortal allows up to skip certain operations when we know that the object will be around for the entire execution of the runtime.
Note that this by itself will bring a performance regression to the runtime due to the extra reference count checks. However, this brings the ability of having truly immutable objects that are useful in other contexts such as immutable data sharing between sub-interpreters.
* The majority of the monitoring code is in instrumentation.c
* The new instrumentation bytecodes are in bytecodes.c
* legacy_tracing.c adapts the new API to the old sys.setrace and sys.setprofile APIs
The function is like Py_AtExit() but for a single interpreter. This is a companion to the atexit module's register() function, taking a C callback instead of a Python one.
We also update the _xxinterpchannels module to use _Py_AtExit(), which is the motivating case. (This is inspired by pain points felt while working on gh-101660.)
In gh-102744 we added is_core_module() (in Python/import.c), which relies on get_core_module_dict() (also added in that PR). The problem is that_PyImport_FixupBuiltin(), which ultimately calls is_core_module(), is called on the builtins module before interp->builtins_copyis set. Consequently, the builtins module isn't considered a "core" module while it is getting "fixed up" and its module def m_copy erroneously gets set. Under isolated interpreters this causes problems since sys and builtins are allowed even though they are still single-phase init modules. (This was discovered while working on gh-101660.)
The solution is to stop relying on get_core_module_dict() in is_core_module().
Sharing mutable (or non-immortal) objects between interpreters is generally not safe. We can work around that but not easily.
There are two restrictions that are critical for objects that break interpreter isolation.
The first is that the object's state be guarded by a global lock. For now the GIL meets this requirement, but a granular global lock is needed once we have a per-interpreter GIL.
The second restriction is that the object (and, for a container, its items) be deallocated/resized only when the interpreter in which it was allocated is the current one. This is because every interpreter has (or will have, see gh-101660) its own object allocator. Deallocating an object with a different allocator can cause crashes.
The dict for the cache of module defs is completely internal, which simplifies what we have to do to meet those requirements. To do so, we do the following:
* add a mechanism for re-using a temporary thread state tied to the main interpreter in an arbitrary thread
* add _PyRuntime.imports.extensions.main_tstate`
* add _PyThreadState_InitDetached() and _PyThreadState_ClearDetached() (pystate.c)
* add _PyThreadState_BindDetached() and _PyThreadState_UnbindDetached() (pystate.c)
* make sure the cache dict (_PyRuntime.imports.extensions.dict) and its items are all owned by the main interpreter)
* add a placeholder using for a granular global lock
Note that the cache is only used for legacy extension modules and not for multi-phase init modules.
https://github.com/python/cpython/issues/100227
This reverts commit 87be8d9.
This approach to keeping the interned strings safe is turning out to be too complex for my taste (due to obmalloc isolation). For now I'm going with the simpler solution, making the dict per-interpreter. We can revisit that later if we want a sharing solution.
This is effectively two changes. The first (the bulk of the change) is where we add _Py_AddToGlobalDict() (and _PyRuntime.cached_objects.main_tstate, etc.). The second (much smaller) change is where we update PyUnicode_InternInPlace() to use _Py_AddToGlobalDict() instead of calling PyDict_SetDefault() directly.
Basically, _Py_AddToGlobalDict() is a wrapper around PyDict_SetDefault() that should be used whenever we need to add a value to a runtime-global dict object (in the few cases where we are leaving the container global rather than moving it to PyInterpreterState, e.g. the interned strings dict). _Py_AddToGlobalDict() does all the necessary work to make sure the target global dict is shared safely between isolated interpreters. This is especially important as we move the obmalloc state to each interpreter (gh-101660), as well as, potentially, the GIL (PEP 684).
https://github.com/python/cpython/issues/100227
* Eliminate all remaining uses of Py_SIZE and Py_SET_SIZE on PyLongObject, adding asserts.
* Change layout of size/sign bits in longobject to support future addition of immortal ints and tagged medium ints.
* Add functions to hide some internals of long object, and for setting sign and digit count.
* Replace uses of IS_MEDIUM_VALUE macro with _PyLong_IsCompact().
Aside from sys and builtins, _io is the only core builtin module that hasn't been ported to multi-phase init. We may do so later (e.g. gh-101948), but in the meantime we must at least take care of the module's static types properly. (This came up while working on gh-101660.)
https://github.com/python/cpython/issues/94673
The error-handling code in new_interpreter() has been broken for a while. We hadn't noticed because those code mostly doesn't fail. (I noticed while working on gh-101660.) The problem is that we try to clear/delete the newly-created thread/interpreter using itself, which just failed. The solution is to switch back to the calling thread state first.
https://github.com/python/cpython/issues/98608
Victor Stinner
chgnrdv
YAMAMOTO Takashi
Mark Shannon
Irit Katriel
Crowthebird
Brandt Bucher
Eric Snow
Nikita Sobolev
Erlend E. Aasland
Pablo Galindo Salgado
Dong-hee Na
Kirill Podoprigora
Jelle Zijlstra
Guido van Rossum
Inada Naoki
Lysandros Nikolaou
Carl Meyer
Marta Gómez Macías
Kumar Aditya
Zachary Ware
Steve Dower
gsallam
penguin_wwy
Sebastian Berg
Arthur Pastel
John Belmonte
Tomas R
Petr Viktorin
Tian Gao
Paul Ganssle
Carey Metcalfe
Ken Jin
Barry Warsaw
Shantanu
Eddie Elizondo
Oleg Iarygin
Benjamin Peterson
Brett Cannon