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",
]
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