The adaptive counter doesn't do anything currently in the free-threaded
build and TSan reports a data race due to concurrent modifications to
the counter.
Co-authored-by: blurb-it[bot] <43283697+blurb-it[bot]@users.noreply.github.com>
Co-authored-by: Hugo van Kemenade <1324225+hugovk@users.noreply.github.com>
In the free-threaded build, we need to lock pending->mutex when clearing
the handling_thread in order not to race with a concurrent
make_pending_calls in the same interpreter.
* Reject uop definitions that declare values as 'unused' that are already cached by prior uops
* Track which variables are defined and only load from memory when needed
* Support explicit `flush` in macro definitions.
* Make sure stack is flushed in where needed.
The `used` field must be written using atomic stores because `set_len`
and iterators may access the field concurrently without holding the
per-object lock.
Refactor the fast Unicode hash check into `_PyObject_HashFast` and use relaxed
atomic loads in the free-threaded build.
After this change, the TSAN doesn't report data races for this method.
This PR sets up tagged pointers for CPython.
The general idea is to create a separate struct _PyStackRef for everything on the evaluation stack to store the bits. This forces the C compiler to warn us if we try to cast things or pull things out of the struct directly.
Only for free threading: We tag the low bit if something is deferred - that means we skip incref and decref operations on it. This behavior may change in the future if Mark's plans to defer all objects in the interpreter loop pans out.
This implies a strict stack reference discipline is required. ALL incref and decref operations on stackrefs must use the stackref variants. It is unsafe to untag something then do normal incref/decref ops on it.
The new incref and decref variants are called dup and close. They mimic a "handle" API operating on these stackrefs.
Please read Include/internal/pycore_stackref.h for more information!
---------
Co-authored-by: Mark Shannon <9448417+markshannon@users.noreply.github.com>
* Add an InternalDocs file describing how interning should work and how to use it.
* Add internal functions to *explicitly* request what kind of interning is done:
- `_PyUnicode_InternMortal`
- `_PyUnicode_InternImmortal`
- `_PyUnicode_InternStatic`
* Switch uses of `PyUnicode_InternInPlace` to those.
* Disallow using `_Py_SetImmortal` on strings directly.
You should use `_PyUnicode_InternImmortal` instead:
- Strings should be interned before immortalization, otherwise you're possibly
interning a immortalizing copy.
- `_Py_SetImmortal` doesn't handle the `SSTATE_INTERNED_MORTAL` to
`SSTATE_INTERNED_IMMORTAL` update, and those flags can't be changed in
backports, as they are now part of public API and version-specific ABI.
* Add private `_only_immortal` argument for `sys.getunicodeinternedsize`, used in refleak test machinery.
* Make sure the statically allocated string singletons are unique. This means these sets are now disjoint:
- `_Py_ID`
- `_Py_STR` (including the empty string)
- one-character latin-1 singletons
Now, when you intern a singleton, that exact singleton will be interned.
* Add a `_Py_LATIN1_CHR` macro, use it instead of `_Py_ID`/`_Py_STR` for one-character latin-1 singletons everywhere (including Clinic).
* Intern `_Py_STR` singletons at startup.
* For free-threaded builds, intern `_Py_LATIN1_CHR` singletons at startup.
* Beef up the tests. Cover internal details (marked with `@cpython_only`).
* Add lots of assertions
Co-Authored-By: Eric Snow <ericsnowcurrently@gmail.com>