24103052497

Committed 07 Apr 2026 08:33PM UTC coverage: 52.311% (-40.6%) from 92.909%

Build # 24103052497

Build Type

Pull #23228

github

Committed by

web-flow

Commit Message

Merge 18fdfb0fd into b05152cd9

Pull Request Pull Request #23228: Add persistent dependency inference cache for incremental --changed-dependents

Coverage Stats

31 of 136 new or added lines in 2 files covered. (22.79%)

23028 existing lines in 605 files now uncovered.

31671 of 60544 relevant lines covered (52.31%)

1.05 hits per line

Source File
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75.86

/src/python/pants/backend/python/util_rules/partition.py

# Copyright 2022 Pants project contributors (see CONTRIBUTORS.md).
# Licensed under the Apache License, Version 2.0 (see LICENSE).

from __future__ import annotations

import itertools
from collections import defaultdict
from collections.abc import Iterable, Mapping, Sequence
from typing import TypeVar

from pants.backend.python.subsystems.setup import PythonSetup
from pants.backend.python.target_types import InterpreterConstraintsField, PythonResolveField
from pants.backend.python.util_rules.interpreter_constraints import (
    FieldSetWithInterpreterConstraints,
    InterpreterConstraints,
)
from pants.engine.internals.graph import find_all_targets
from pants.engine.rules import implicitly
from pants.engine.target import FieldSet
from pants.util.ordered_set import OrderedSet

ResolveName = str


_FS = TypeVar("_FS", bound=FieldSetWithInterpreterConstraints)


def _partition_by_interpreter_constraints_and_resolve(
    field_sets: Sequence[_FS],
    python_setup: PythonSetup,
) -> Mapping[tuple[ResolveName, InterpreterConstraints], OrderedSet[_FS]]:
    resolve_and_interpreter_constraints_to_field_sets: Mapping[
        tuple[str, InterpreterConstraints], OrderedSet[_FS]
    ] = defaultdict(lambda: OrderedSet())
    for field_set in field_sets:
        resolve = field_set.resolve.normalized_value(python_setup)
        interpreter_constraints = InterpreterConstraints.create_from_field_sets(
            [field_set], python_setup
        )
        resolve_and_interpreter_constraints_to_field_sets[(resolve, interpreter_constraints)].add(
            field_set
        )

    return resolve_and_interpreter_constraints_to_field_sets


async def _find_all_unique_interpreter_constraints(
    python_setup: PythonSetup,
    field_set_type: type[FieldSet],
    *,
    extra_constraints_per_tgt: Iterable[InterpreterConstraintsField] = (),
) -> InterpreterConstraints:
    """Find all unique interpreter constraints used by given field set.

    This will find the constraints for each individual matching field set, and then OR across all
    unique constraints. Usually, Pants partitions when necessary so that conflicting interpreter
    constraints can be handled gracefully. But in some cases, like the `generate-lockfiles` goal,
    we need to combine those targets into a single value. This ORs, so that if you have a
    ==2.7 partition and ==3.6 partition, for example, we return ==2.7 OR ==3.6.

    Returns the global interpreter constraints if no relevant targets were matched.
    """
    all_tgts = await find_all_targets(**implicitly())
    extra_constraints_blank_resolves = [
        (ics_field, None) for ics_field in extra_constraints_per_tgt
    ]
    unique_constraints = {
        InterpreterConstraints.create_from_compatibility_fields(
            [
                (
                    tgt[InterpreterConstraintsField],
                    tgt[PythonResolveField] if tgt.has_field(PythonResolveField) else None,
                ),
                *extra_constraints_blank_resolves,
            ],
            python_setup,
        )
        for tgt in all_tgts
        if tgt.has_field(InterpreterConstraintsField) and field_set_type.is_applicable(tgt)
    }
    if not unique_constraints and extra_constraints_per_tgt:
        unique_constraints.add(
            InterpreterConstraints.create_from_compatibility_fields(
                extra_constraints_blank_resolves,
                python_setup,
            )
        )
    constraints = InterpreterConstraints(
        itertools.chain.from_iterable(ic for ic in unique_constraints if ic)
    )
    return constraints or InterpreterConstraints(python_setup.interpreter_constraints)

1	# Copyright 2022 Pants project contributors (see CONTRIBUTORS.md).
2	# Licensed under the Apache License, Version 2.0 (see LICENSE).
3
4	from __future__ import annotations	2✔
5
6	import itertools	2✔
7	from collections import defaultdict	2✔
8	from collections.abc import Iterable, Mapping, Sequence	2✔
9	from typing import TypeVar	2✔
10
11	from pants.backend.python.subsystems.setup import PythonSetup	2✔
12	from pants.backend.python.target_types import InterpreterConstraintsField, PythonResolveField	2✔
13	from pants.backend.python.util_rules.interpreter_constraints import (	2✔
14	FieldSetWithInterpreterConstraints,
15	InterpreterConstraints,
16	)
17	from pants.engine.internals.graph import find_all_targets	2✔
18	from pants.engine.rules import implicitly	2✔
19	from pants.engine.target import FieldSet	2✔
20	from pants.util.ordered_set import OrderedSet	2✔
21
22	ResolveName = str	2✔
23
24
25	_FS = TypeVar("_FS", bound=FieldSetWithInterpreterConstraints)	2✔
26
27
28	def _partition_by_interpreter_constraints_and_resolve(	2✔
29	field_sets: Sequence[_FS],
30	python_setup: PythonSetup,
31	) -> Mapping[tuple[ResolveName, InterpreterConstraints], OrderedSet[_FS]]:
32	resolve_and_interpreter_constraints_to_field_sets: Mapping[	2✔
33	tuple[str, InterpreterConstraints], OrderedSet[_FS]
34	] = defaultdict(lambda: OrderedSet())
35	for field_set in field_sets:	2✔
36	resolve = field_set.resolve.normalized_value(python_setup)	2✔
37	interpreter_constraints = InterpreterConstraints.create_from_field_sets(	2✔
38	[field_set], python_setup
39	)
40	resolve_and_interpreter_constraints_to_field_sets[(resolve, interpreter_constraints)].add(	2✔
41	field_set
42	)
43
44	return resolve_and_interpreter_constraints_to_field_sets	2✔
45
46
47	async def _find_all_unique_interpreter_constraints(	2✔
48	python_setup: PythonSetup,
49	field_set_type: type[FieldSet],
50	*,
51	extra_constraints_per_tgt: Iterable[InterpreterConstraintsField] = (),
52	) -> InterpreterConstraints:
53	"""Find all unique interpreter constraints used by given field set.
54
55	This will find the constraints for each individual matching field set, and then OR across all
56	unique constraints. Usually, Pants partitions when necessary so that conflicting interpreter
57	constraints can be handled gracefully. But in some cases, like the `generate-lockfiles` goal,
58	we need to combine those targets into a single value. This ORs, so that if you have a
59	==2.7 partition and ==3.6 partition, for example, we return ==2.7 OR ==3.6.
60
61	Returns the global interpreter constraints if no relevant targets were matched.
62	"""
UNCOV 63	all_tgts = await find_all_targets(**implicitly())	×
UNCOV 64	extra_constraints_blank_resolves = [	×
65	(ics_field, None) for ics_field in extra_constraints_per_tgt
66	]
UNCOV 67	unique_constraints = {	×
68	InterpreterConstraints.create_from_compatibility_fields(
69	[
70	(
71	tgt[InterpreterConstraintsField],
72	tgt[PythonResolveField] if tgt.has_field(PythonResolveField) else None,
73	),
74	*extra_constraints_blank_resolves,
75	],
76	python_setup,
77	)
78	for tgt in all_tgts
79	if tgt.has_field(InterpreterConstraintsField) and field_set_type.is_applicable(tgt)
80	}
UNCOV 81	if not unique_constraints and extra_constraints_per_tgt:	×
82	unique_constraints.add(	×
83	InterpreterConstraints.create_from_compatibility_fields(
84	extra_constraints_blank_resolves,
85	python_setup,
86	)
87	)
UNCOV 88	constraints = InterpreterConstraints(	×
89	itertools.chain.from_iterable(ic for ic in unique_constraints if ic)
90	)
UNCOV 91	return constraints or InterpreterConstraints(python_setup.interpreter_constraints)	×

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