Widen JIT int fast paths to full int64 range

[KRRT7]

This work widens the JIT int fast paths from the compact-only range to the full int64_t range.

It also fixes follow-up correctness issues in specialized widened paths for non-compact exact PyLongObjects and on 15-bit builds.

Scope:

• widen JIT integer add/subtract/multiply fast paths to operate across the full int64_t range
• accept exact int operands that fit in int64_t, including non-compact PyLongObjects
• keep specialized in-place mutation compact-only and fall back safely for non-compact inputs
• handle widened integer compare without compact-only assumptions
• construct widened arithmetic results with PyLong_FromInt64() so 15-bit builds do not narrow through stwodigits
• add regression coverage for widened operations, non-compact exact ints, boundary cases, and overflow fallback
• add benchmark scripts for measuring widened JIT integer fast-path performance

Linked PRs

• gh-150424: Widen JIT int fast paths to full int64 range #150425

[picnixz]

Do we support 15-bit builds actually?

[picnixz]

In addition, please clearly clarify the issue. The issue description is obscure and looks like a simple LLM report. In particular, please read https://devguide.python.org/getting-started/generative-ai/ first and share benchmarks if they improve.

[markshannon]

If you want to improve int performance then take a look at #101291