pyrefly-type-coverage（Pyrefly 类型覆盖）

Pyrefly Type Coverage Skill

Prerequisites

• The file must live in a project with a pyrefly.toml.
• pyrefly, lintrunner, and the project's test runner must be on PATH. If any are missing, stop and ask whether a conda environment needs activating — don't install or substitute (per repo CLAUDE.md).

Step 1: Remove file-level type-check suppressions

Delete any of these from the top of the file (pyrefly honors # mypy: ignore-errors for mypy compat, so that one must go too):

# pyre-ignore-all-errors
# pyre-ignore-all-errors[16,21,53,56]
# @lint-ignore-every PYRELINT
# mypy: ignore-errors

Step 2: Add a sub-config entry to pyrefly.toml

[[sub-config]]
matches = "path/to/directory/**"
[sub-config.errors]
implicit-import = false
implicit-any = true
bad-param-name-override = false
unannotated-return = true
unannotated-parameter = true

IMPORTANT: Setting any error key in [sub-config.errors] overrides only that key relative to the parent — but enabling unannotated-return / unannotated-parameter / implicit-any will resurface errors that were previously hidden file-wide. If you see unrelated errors (e.g., bad-param-name-override) flooding the output, mirror the parent config's setting for that key in the sub-config to silence them.

Step 3: Run pyrefly

pyrefly check <FILENAME>

Goal: resolve all unannotated-return, unannotated-parameter, and implicit-any errors by adding annotations — see Step 4's ladder. These three target categories are always resolvable; never suppress them with # pyrefly: ignore. The single exception is @compatibility(is_backward_compatible=True) (Step 4).

Other categories (bad-argument-type, missing-attribute, …) are real type bugs. Handle them by where pyrefly reports them:

• Reported in another file (path!= target): leave it. Don't widen scope. If the error is now blocking the target, suppress at the report site with # pyrefly: ignore[<category>] # TODO.
• Reported in the target file but the message names a symbol defined elsewhere (e.g., bad-return because an imported function's annotation is wrong): suppress locally with the same TODO comment. Don't invent a cast() that papers over the upstream gap.
• Reported in the target file, originates locally: fix it.

Use # pyrefly: ignore[...] only as a last resort, and only on non-target categories.

Step 4: Add annotations

Examine call sites when the right type isn't obvious from the function body.

Annotation conventions

• Use PEP 604 / PEP 585 syntax (int | None, list[str]) — assume Python >= 3.10.
• Prefer collections.abc over typing for ABCs (Callable, Sequence, Generator,...).
• For generic helpers, import from typing when available on the project's minimum Python version, and from typing_extensions only when you need a newer feature (e.g., Self and override if supporting < 3.11/3.12, or PEP 696 default= for TypeVar / ParamSpec). Don't blanket-import from typing_extensions.
• Always parameterize Callable — Callable[..., Any] when the signature is genuinely unknown, never bare Callable. (See ParamSpec below for the signature-preserving wrapper case.)
• Class attributes assigned in __init__ should get a class-level annotation so pyrefly can see them.
• Break import cycles with if TYPE_CHECKING: — annotation-only imports go inside the guard, and use from __future__ import annotations (or string forward refs) so runtime imports stay lazy: from __future__ import annotations from typing import TYPE_CHECKING if TYPE_CHECKING: from torch.fx import GraphModule def transform(gm: GraphModule) -> GraphModule:...
• Never suppress the three target categories. unannotated-return, unannotated-parameter, and implicit-any are always resolvable by adding an annotation; # pyrefly: ignore[<one of those>] is not an acceptable outcome. The single exception is the Backward compatibility carve-out below.
• Widen, don't bail. When the right type is hard to infer, walk down this ladder rather than reaching for an ignore:

1. Most specific concrete type observable from call sites and return paths. 2. A union (X | Y), Sequence[X]-style abstract type, or a bound TypeVar for genuinely generic functions (identity-passthrough, container helpers). 3. object — strictest fallback that still type-checks. Forces callers to narrow before use, e.g., def serialize(value: object) -> str:. Visually similar to Any but stricter — pyrefly rejects value.foo() without an isinstance. 4. Any — last rung. Always preferred over a # pyrefly: ignore on a target category, but only after rungs 1–3 fail. Be able to articulate why each earlier rung doesn't fit (e.g., "union exceeds 8 types", "no observable common bound", "callers genuinely never narrow").

• Read at least three call sites before deciding a parameter must be Any — don't pattern-match "looks dynamic" on the first try.
• Narrow-scope # pyrefly: ignore[...] (on a non-target category) is reserved for cases where pyrefly is *actually wrong* about a specific local error — dynamic metaprogramming, third-party stub gaps: # pyrefly: ignore[attr-defined] result = getattr(obj, dynamic_name)()

Backward compatibility (the one exception to never-suppress)

CRITICAL: Functions decorated with @compatibility(is_backward_compatible=True) must NOT have their signatures changed. The backward-compat test (test_function_back_compat) compares stringified inspect.signature against a golden file — adding annotations (even -> None) changes that string and the test fails. Use pyrefly ignore comments instead:

@compatibility(is_backward_compatible=True)
def my_function(  # pyrefly: ignore[unannotated-return]
    self,
    arg1,  # can't add type here either
):
    ...

The # pyrefly: ignore comment must be on the def line (where pyrefly reports the error), not on the closing ).

ParamSpec for signature-preserving wrappers (decorators, functools.wraps-style helpers). Use Callable[P, R] so the wrapped function's signature flows through to the caller — Callable[..., Any] loses it. Skip ParamSpec if the wrapper genuinely accepts arbitrary callables. Pair with Concatenate[X, P] when the wrapper prepends or appends args.

from collections.abc import Callable
from typing import ParamSpec, TypeVar

P = ParamSpec("P")
R = TypeVar("R")

def log_calls(fn: Callable[P, R]) -> Callable[P, R]:
    def wrapper(*args: P.args, **kwargs: P.kwargs) -> R:
        return fn(*args, **kwargs)
    return wrapper

Step 5: Iterate

Re-run pyrefly check. New annotations often surface bad-return errors where the function actually returns an incompatible type — fix those. Repeat until clean.

Step 6: Lint

Required before handing off — annotations frequently shift import order and line length:

lintrunner -a <files...>

Resolve anything lintrunner can't auto-fix manually.

Step 7: Test

Precedence when something fails: tests passing > pyrefly clean > annotation strictness. If a freshly-added annotation breaks a test, narrow it one rung in the discipline ladder (e.g., concrete → object, or remove an Any widening that broke a downstream isinstance check) before reverting the file.

1. Backward-compat check. Run iff grep -l '@compatibility(is_backward_compatible=True)' <target> returns the file — the decorator is the actual precondition for the golden file. The broader "imports torch.fx" heuristic catches half of torch/. python -m pytest test/test_fx.py::TestFXAPIBackwardCompatibility -x -v
2. Unit tests for the modified module. Search both ways before concluding no coverage exists: # torch/foo/bar.py is usually covered by test/test_foo.py or test/test_bar.py ls test/ | grep -i <module-name> # or by import grep -rl "from torch.foo.bar import\|import torch.foo.bar" test/ If both come up empty, tell the user — don't silently skip. Type changes can introduce real runtime regressions (Optional[X] vs X, Sequence vs list when .append is called, etc.).

Notes

• Forward refs in class bodies without from __future__ import annotations still need string quoting: class MyClass: def __new__(cls) -> "MyClass":...
• Committing: don't commit unless the user explicitly asks (per repo CLAUDE.md). Stop and surface the diff for review when the file is clean.