Added atomic operations to `scanner_begin()` and `scanner_end()` to prevent
race conditions on the `executing` flag in free-threaded builds. Also added
tests for concurrent usage of the `re` module.
Without the atomic operations, `test_scanner_concurrent_access()` triggers
`assert(self->executing)` failures, or a thread sanitizer run emits errors.
If we overflowed the global version counter (i.e., after 2*24 calls to
`_PyMonitoring_SetEvents`), we bailed out after setting global monitoring
events but before instrumenting code objects, which led to assertion errors
later on.
Also add a `time.sleep()` to `test_free_threading.test_monitoring` to avoid
overflowing the global version counter.
Added a critical section to protect the states of `ReaderObj` and `WriterObj` in the free-threading build. Without the critical sections, both new free-threading tests were crashing.
Only raises if the stack pointer is both below the limit *and* above the stack base.
This prevents false positives for user-space threads, as the stack pointer will be outside those bounds
if the stack has been swapped.
The dataclasses `__init__` function is generated dynamically by a call to `exec()` and so doesn't have deferred reference counting enabled. Enable deferred reference counting on functions when assigned as an attribute to type objects to avoid reference count contention when creating dataclass instances.
Adapted from a patch for Python 3.14 submitted to the Debian BTS by John
https://bugs.debian.org/1105111#20
Co-authored-by: John David Anglin <dave.anglin@bell.net>
- Introduce a new field in the GC state to store the frame that initiated garbage collection.
- Update RemoteUnwinder to include options for including "<native>" and "<GC>" frames in the stack trace.
- Modify the sampling profiler to accept parameters for controlling the inclusion of native and GC frames.
- Enhance the stack collector to properly format and append these frames during profiling.
- Add tests to verify the correct behavior of the profiler with respect to native and GC frames, including options to exclude them.
Co-authored-by: Pablo Galindo Salgado <pablogsal@gmail.com>
This PR changes the current JIT model from trace projection to trace recording. Benchmarking: better pyperformance (about 1.7% overall) geomean versus current https://raw.githubusercontent.com/facebookexperimental/free-threading-benchmarking/refs/heads/main/results/bm-20251108-3.15.0a1%2B-7e2bc1d-JIT/bm-20251108-vultr-x86_64-Fidget%252dSpinner-tracing_jit-3.15.0a1%2B-7e2bc1d-vs-base.svg, 100% faster Richards on the most improved benchmark versus the current JIT. Slowdown of about 10-15% on the worst benchmark versus the current JIT. **Note: the fastest version isn't the one merged, as it relies on fixing bugs in the specializing interpreter, which is left to another PR**. The speedup in the merged version is about 1.1%. https://raw.githubusercontent.com/facebookexperimental/free-threading-benchmarking/refs/heads/main/results/bm-20251112-3.15.0a1%2B-f8a764a-JIT/bm-20251112-vultr-x86_64-Fidget%252dSpinner-tracing_jit-3.15.0a1%2B-f8a764a-vs-base.svg
Stats: 50% more uops executed, 30% more traces entered the last time we ran them. It also suggests our trace lengths for a real trace recording JIT are too short, as a lot of trace too long aborts https://github.com/facebookexperimental/free-threading-benchmarking/blob/main/results/bm-20251023-3.15.0a1%2B-eb73378-CLANG%2CJIT/bm-20251023-vultr-x86_64-Fidget%252dSpinner-tracing_jit-3.15.0a1%2B-eb73378-pystats-vs-base.md .
This new JIT frontend is already able to record/execute significantly more instructions than the previous JIT frontend. In this PR, we are now able to record through custom dunders, simple object creation, generators, etc. None of these were done by the old JIT frontend. Some custom dunders uops were discovered to be broken as part of this work gh-140277
The optimizer stack space check is disabled, as it's no longer valid to deal with underflow.
Pros:
* Ignoring the generated tracer code as it's automatically created, this is only additional 1k lines of code. The maintenance burden is handled by the DSL and code generator.
* `optimizer.c` is now significantly simpler, as we don't have to do strange things to recover the bytecode from a trace.
* The new JIT frontend is able to handle a lot more control-flow than the old one.
* Tracing is very low overhead. We use the tail calling interpreter/computed goto interpreter to switch between tracing mode and non-tracing mode. I call this mechanism dual dispatch, as we have two dispatch tables dispatching to each other. Specialization is still enabled while tracing.
* Better handling of polymorphism. We leverage the specializing interpreter for this.
Cons:
* (For now) requires tail calling interpreter or computed gotos. This means no Windows JIT for now :(. Not to fret, tail calling is coming soon to Windows though https://github.com/python/cpython/pull/139962
Design:
* After each instruction, the `record_previous_inst` function/label is executed. This does as the name suggests.
* The tracing interpreter lowers bytecode to uops directly so that it can obtain "fresh" values at the point of lowering.
* The tracing version behaves nearly identical to the normal interpreter, in fact it even has specialization! This allows it to run without much of a slowdown when tracing. The actual cost of tracing is only a function call and writes to memory.
* The tracing interpreter uses the specializing interpreter's deopt to naturally form the side exit chains. This allows it to side exit chain effectively, without repeating much code. We force a re-specializing when tracing a deopt.
* The tracing interpreter can even handle goto errors/exceptions, but I chose to disable them for now as it's not tested.
* Because we do not share interpreter dispatch, there is should be no significant slowdown to the original specializing interpreter on tailcall and computed got with JIT disabled. With JIT enabled, there might be a slowdown in the form of the JIT trying to trace.
* Things that could have dynamic instruction pointer effects are guarded on. The guard deopts to a new instruction --- `_DYNAMIC_EXIT`.
Update `bytearray` to contain a `bytes` and provide a zero-copy path to
"extract" the `bytes`. This allows making several code paths more efficient.
This does not move any codepaths to make use of this new API. The documentation
changes include common code patterns which can be made more efficient with
this API.
---
When just changing `bytearray` to contain `bytes` I ran pyperformance on a
`--with-lto --enable-optimizations --with-static-libpython` build and don't see
any major speedups or slowdowns with this; all seems to be in the noise of
my machine (Generally changes under 5% or benchmarks that don't touch
bytes/bytearray).
Co-authored-by: Victor Stinner <vstinner@python.org>
Co-authored-by: Maurycy Pawłowski-Wieroński <5383+maurycy@users.noreply.github.com>
Many functions related to compiling or parsing Python code, such as
compile(), ast.parse(), symtable.symtable(),
and importlib.abc.InspectLoader.source_to_code() now allow to pass
the module name used when filtering syntax warnings.
Allow the --enable-pystats build option to be used with free-threading. The
stats are now stored on a per-interpreter basis, rather than process global.
For free-threaded builds, the stats structure is allocated per-thread and
then periodically merged into the per-interpreter stats structure (on thread
exit or when the reporting function is called). Most of the pystats related
code has be moved into the file Python/pystats.c.
