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Adds explicit import caching for Python modules and functions:
API:
- py:import/1 - Import and cache a module
- py:import/2 - Import module and cache a specific function
- py:flush_imports/0 - Clear all import caches
- py:import_stats/0 - Get cache entry count
- py:import_list/0 - List cached imports as #{Module => [Funcs]}
Key behaviors:
- __main__ is never cached (returns error)
- Caching is per-process namespace (via PID affinity)
- All Python execution commands benefit from the cache
Tests:
- py_import_SUITE: 12 tests for basic import functionality
- py_import_owngil_SUITE: 9 tests for OWN_GIL mode (Python 3.12+)
- Multi-process and concurrent stress tests included
When using py_context:exec to define a function and then py_context:call with '__main__' as the module, the function was not found because '__main__' was looked up via PyImport_ImportModule (real Python module) instead of ctx->globals where exec stores defined functions. Add special handling to nif_context_call and owngil_execute_call to check ctx->globals first when module is '__main__', matching the existing behavior in nif_context_call_with_env.
string.ascii_lowercase is a string constant, not a callable function. The test was failing for contexts that included the string module because calling it raised TypeError. Use string.capwords instead.
- new/1: Create context with options map (mode => auto|subinterp|worker|owngil) - destroy/1: Alias for stop/1 for API consistency - call/4: Wrapper for call/5 with empty kwargs - eval/2: Wrapper for eval/3 with empty locals
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Summary
py:import/1- Import and cache a modulepy:import/2- Import module and cache a specific functionpy:flush_imports/0- Clear all import cachespy:import_stats/0- Get cache entry countpy:import_list/0- List cached imports as#{Module => [Funcs]}Caching is per-process (via PID affinity) and
__main__is never cached.