from ..py_info import PythonInfo from ..py_spec import PythonSpec from .pep514 import discover_pythons # Map of well-known organizations (as per PEP 514 Company Windows Registry key part) versus Python implementation _IMPLEMENTATION_BY_ORG = { "ContinuumAnalytics": "CPython", "PythonCore": "CPython", } class Pep514PythonInfo(PythonInfo): """A Python information acquired from PEP-514""" def propose_interpreters(spec, cache_dir, env): # see if PEP-514 entries are good # start with higher python versions in an effort to use the latest version available # and prefer PythonCore over conda pythons (as virtualenv is mostly used by non conda tools) existing = list(discover_pythons()) existing.sort( key=lambda i: tuple(-1 if j is None else j for j in i[1:4]) + (1 if i[0] == "PythonCore" else 0,), reverse=True, ) for name, major, minor, arch, exe, _ in existing: # Map well-known/most common organizations to a Python implementation, use the org name as a fallback for # backwards compatibility. implementation = _IMPLEMENTATION_BY_ORG.get(name, name) # Pre-filtering based on Windows Registry metadata, for CPython only skip_pre_filter = implementation.lower() != "cpython" registry_spec = PythonSpec(None, implementation, major, minor, None, arch, exe) if skip_pre_filter or registry_spec.satisfies(spec): interpreter = Pep514PythonInfo.from_exe(exe, cache_dir, env=env, raise_on_error=False) if interpreter is not None: # Final filtering/matching using interpreter metadata if interpreter.satisfies(spec, impl_must_match=True): yield interpreter __all__ = [ "Pep514PythonInfo", "propose_interpreters", ]