* Instead of calling get_identifiers_and_strings(), extract identifiers and strings from pycore_global_strings.h.
* Avoid ast.literal_eval(), it's very slow.
We tried this before with a dict and for all interned strings. That ran into problems due to interpreter isolation. However, exclusively using a per-interpreter cache caused some inconsistency that can eliminate the benefit of interning. Here we circle back to using a global cache, but only for statically allocated strings. We also use a more-basic _Py_hashtable_t for that global cache instead of a dict.
Ideally we would only have the global cache, but the optional isolation of each interpreter's allocator means that a non-static string object must not outlive its interpreter. Thus we would have to store a copy of each such interned string in the global cache, tied to the main interpreter.
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
* 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().