fix(types): mypy clean again over src; stub-less libraries and the benchmark imports handled in pyproject

66 errors had accumulated in src since the last green run (the hunt modules of groups 4-6, stats, candidates,
runner). Codex typed them without behaviour change; the 17 inline import-untyped ignores it added are replaced by
one override for dspy, pandas, statsmodels and scikit-learn, and the hunt package's lazy imports of benchmarks/
(never type-checked, not in files) are followed silently so src stays strict against their signatures.

Co-Authored-By: Claude Fable 5.1 <[email protected]>

pyproject.toml

@@ -90,6 +90,17 @@ ignore_missing_imports = true
 module = "yaml"
 ignore_missing_imports = true
 
+# dspy, pandas, statsmodels and scikit-learn ship no py.typed marker and no stub packages are dev dependencies.
+[[tool.mypy.overrides]]
+module = ["dspy", "dspy.*", "pandas", "pandas.*", "statsmodels.*", "sklearn.*"]
+ignore_missing_imports = true
+
+# The hunt package reaches the benchmark scorers and manifests lazily. benchmarks/ is not in `files` and has never
+# been type-checked; src stays strict against its signatures while errors inside benchmarks/ are not reported.
+[[tool.mypy.overrides]]
+module = "benchmarks.*"
+follow_imports = "silent"
+
 [dependency-groups]
 dev = [
     "dagger-io>=0.21.7",

src/openultrasast/hunt/ablation.py

@@ -190,7 +190,7 @@ def run(
     if table.digest() != manifest.table_digest:
         raise ValueError("table digest does not match registration")
     runner.refuse_pilot(Path(pool_manifest_path), pilot_report=False)
-    folds: dict[str, tuple[str, int]] = {}
+    folds: dict[str, tuple[str, int | None]] = {}
     for row in table.rows:
         key, value = row["change_id"], (row["repo"], row.get("fold"))
         if key in folds and folds[key] != value:

src/openultrasast/hunt/accept.py

@@ -77,7 +77,7 @@ class Decision:
                 artifact.configurations.append(record)
 
 
-def _record(value: Any) -> dict[str, Any]:
+def _record(value: Estimate | FoldResult | Mapping[str, Any]) -> dict[str, Any]:
     """Convert dataclass estimates and ordinary mappings to JSON records."""
     return asdict(value) if is_dataclass(value) else dict(value)
 
@@ -124,7 +124,8 @@ def decide(
     instructions = [state.get("signature", {}).get("instructions", "") for state in candidate.state.values()]
     if any(not isinstance(text, str) or len(text) > rule.instruction_cap for text in instructions):
         reasons.append("instruction_cap")
-    compiled, heldout = {}, {}
+    compiled: dict[str, dict[str, Any]] = {}
+    heldout: dict[str, dict[str, Any]] = {}
     for scope, source, target in (("compile", compile_results, compiled), ("holdout", holdout_results, heldout)):
         for family, result in source.items():
             record = _record(result)
@@ -150,10 +151,10 @@ def decide(
         reasons.append("no_positive_recall_difference")
     if _valid_number(holdout_diff) and abs(holdout_diff) <= rule.tolerance:
         reasons.append("holdout_tie")
-    for family, result in heldout.items():
+    for family, heldout_record in heldout.items():
         if family == "pooled":
             continue
-        diff = result["recall"].get("diff")
+        diff = heldout_record["recall"].get("diff")
         floor = rule.regression_budget.get(family, rule.regression_budget.get("default", 0))
         if _valid_number(diff) and diff < floor:
             reasons.append(f"family_regression:{family}")

src/openultrasast/hunt/artifact.py

@@ -28,7 +28,7 @@ def _exhausted(usage: Mapping[str, float], budget: Mapping[str, float]) -> bool:
 class RunArtifact:
     program_id: str
     schema_version: int
-    mask: tuple[str, ...]
+    mask: tuple[str, ...] | list[str]
     data_digests: dict[str, str]
     configurations: list[dict[str, Any]]
     usage: dict[str, float]

src/openultrasast/hunt/contamination.py

@@ -4,13 +4,14 @@ from __future__ import annotations
 
 import hashlib
 import json
+import re
 import tomllib
-from collections.abc import Iterable
+from collections.abc import Callable, Iterable
 from datetime import UTC, datetime
 from pathlib import Path
 
 
-def _eligibility():
+def _eligibility() -> tuple[re.Pattern[str], Callable[[str], str]]:
     """The benchmark's name normaliser and GitHub URL pattern, imported late so the package imports without the benchmarks tree."""
     from benchmarks.unseen.eligibility import URL, normalize
 

src/openultrasast/hunt/producers.py

@@ -234,7 +234,7 @@ def _roles(function: Any, facts: Any) -> dict[str, str]:
     for call in function.calls:
         for arguments in call.arg_names:
             names.update(arguments)
-    roles = {}
+    roles: dict[str, str] = {}
     for role, entries, attribute in (
         ("source", facts.sources, "patterns"),
         ("sink", facts.sinks, "calls"),

src/openultrasast/hunt/program.py

@@ -67,7 +67,8 @@ def signature_for(mask: Iterable[str] = ()) -> type[dspy.Signature]:
             continue
         fields[name] = (str, dspy.InputField(desc=desc))
     fields["findings"] = (list[Finding], dspy.OutputField(desc="JSON list; empty when the change is ordinary"))
-    return dspy.Signature(fields, BASELINE_INSTRUCTION)
+    signature: type[dspy.Signature] = dspy.Signature(fields, BASELINE_INSTRUCTION)
+    return signature
 
 
 def numbered(lines: Sequence[str], start: int, end: int) -> str:
@@ -194,7 +195,9 @@ class _Loop(dspy.ReAct):
 
     loop_parse_failed = False
 
-    def _call_with_potential_trajectory_truncation(self, module, trajectory, **input_args):
+    def _call_with_potential_trajectory_truncation(
+        self, module: dspy.Module, trajectory: dict[str, Any], **input_args: str
+    ) -> dspy.Prediction:
         try:
             return super()._call_with_potential_trajectory_truncation(module, trajectory, **input_args)
         except dspy.utils.exceptions.AdapterParseError as error:

src/openultrasast/hunt/propose.py

@@ -20,7 +20,7 @@ from .metric import search_metric, search_outcome
 from .table import FEATURE_COLUMNS, canonical_json
 
 
-class _Optimisers(Mapping):
+class _Optimisers(Mapping[str, type]):
     """Load a DSPy optimiser class only when its registry entry is requested."""
 
     names = {"gepa": "GEPA", "miprov2": "MIPROv2", "bootstrap": "BootstrapFewShot"}
@@ -28,7 +28,8 @@ class _Optimisers(Mapping):
     def __getitem__(self, name: str) -> type:
         import dspy
 
-        return getattr(dspy, self.names[name])
+        optimiser: type = getattr(dspy, self.names[name])
+        return optimiser
 
     def __iter__(self) -> Iterator[str]:
         return iter(self.names)
@@ -93,7 +94,8 @@ def compile_examples(
 
     from .program import INPUTS
 
-    repo_folds, ids = {}, set()
+    repo_folds: dict[str, int] = {}
+    ids: set[str] = set()
     for change in changes:
         if change["id"] in ids:
             raise ValueError("change IDs must be unique")
@@ -230,7 +232,13 @@ def _compile(round: Round, program: Any, examples: list, optimiser: Any, metric:
             if dspy.settings.lm is None:
                 raise ValueError("GEPA needs a configured reflection model in dspy.context")
 
-            def feedback(example, prediction, trace=None, pred_name=None, pred_trace=None):
+            def feedback(
+                example: dspy.Example,
+                prediction: dspy.Prediction,
+                trace: Any = None,
+                pred_name: str | None = None,
+                pred_trace: Any = None,
+            ) -> dspy.Prediction:
                 """Give GEPA the same score and the metric's compile-only feedback."""
                 import dspy
 

src/openultrasast/hunt/report.py

@@ -90,7 +90,7 @@ def _instrument(records: Sequence[Mapping]) -> dict:
     )
 
 
-def _clean(records: Sequence[Mapping]) -> list[dict]:
+def _clean(records: Sequence[dict[str, Any]]) -> list[dict[str, Any]]:
     """Remove stale findings on failures while preserving the scorer's coverage checks."""
     from benchmarks.unseen import score
 
@@ -109,7 +109,7 @@ def _clean(records: Sequence[Mapping]) -> list[dict]:
     return result
 
 
-def _rate(values: list[float], repos: list[str], *, binary: bool = False, scale: float = 1) -> dict:
+def _rate(values: Sequence[float], repos: list[str], *, binary: bool = False, scale: float = 1) -> dict:
     """Report a mean with its count and a repository-clustered interval, plus Wilson for proportions."""
     from benchmarks.unseen import score
 
@@ -127,7 +127,7 @@ def _rate(values: list[float], repos: list[str], *, binary: bool = False, scale:
     return result
 
 
-def _family_records(records: Sequence[Mapping], family: str | None) -> list[dict]:
+def _family_records(records: Sequence[dict[str, Any]], family: str | None) -> list[dict[str, Any]]:
     """Keep a family's positives and count only its findings over all ordinary pushes."""
     result = []
     for original in records:
@@ -217,7 +217,7 @@ def _baseline_comparison(baselines: list[list[dict]], records: list[dict], famil
     from benchmarks.unseen import score
     from benchmarks.valid import metrics
 
-    units = [
+    units: list[dict[str, Any]] = [
         dict(change=after, repeat=repeat, a=_outcome(before, before, 10), b=_outcome(after, after, 10))
         for repeat, baseline in enumerate(baselines)
         for before, after in zip(baseline, records, strict=True)
@@ -232,7 +232,7 @@ def _baseline_comparison(baselines: list[list[dict]], records: list[dict], famil
             suspicions_per_push=asdict(suspicions),
             mcnemar=asdict(stats.mcnemar_exact([u["a"]["hit"] for u in positives], [u["b"]["hit"] for u in positives])),
         )
-        rows = {"recall": [], "false_alarms_per_100_pushes": [], "precision": []}
+        rows: dict[str, list[dict[str, Any]]] = {"recall": [], "false_alarms_per_100_pushes": [], "precision": []}
         for baseline in baselines:
             before = metrics.scoring_records(_family_records(baseline, family))
             after = metrics.scoring_records(_family_records(records, family))
@@ -426,7 +426,7 @@ def pilot_gain(
     records = _records(directory / "records", changes)
     proof = _instrument(records)
     _write(directory / "instrument.json", proof)
-    analysis = dict(
+    analysis: dict[str, Any] = dict(
         program_id=candidate.program_id,
         comparison=decision.comparison,
         measurement_directory=directory.name,

src/openultrasast/hunt/rounds.py

@@ -21,7 +21,8 @@ def _fold_changes(pool_manifest: Path, table: FeatureTable, load_changes: Any) -
     from benchmarks.unseen.replay import load_slice
 
     runner.refuse_pilot(pool_manifest, pilot_report=False)
-    folds, repo_folds = {}, {}
+    folds: dict[str, tuple[str, int]] = {}
+    repo_folds: dict[str, int] = {}
     for row in table.rows:
         key, repo, fold = row["change_id"], row["repo"], row.get("fold")
         if type(fold) is not int or fold < 0:
@@ -183,7 +184,8 @@ def fold_results(
     if len({c["id"] for c in changes}) != len(changes):
         raise ValueError("change IDs must be unique")
     directories = {"a": Path(current_dir), "b": Path(candidate_dir)}
-    studies, repeats = {}, set()
+    studies: dict[str, Any] = {}
+    repeats: set[int] = set()
     for arm, directory in directories.items():
         path = directory / "study.json"
         if path.exists():
@@ -291,7 +293,7 @@ def round_trip(
                 )
             )
         results[scope] = fold_results(
-            *paths, [c for c in changes if c["fold"] in folds], scope=scope, tolerance=tolerance, seed=seed, resamples=resamples
+            paths[0], paths[1], [c for c in changes if c["fold"] in folds], scope=scope, tolerance=tolerance, seed=seed, resamples=resamples
         )
     decision = accept.decide(current_id, candidate, results["compile"], results["holdout"], rule)
     if not decision.accepted:

src/openultrasast/hunter_tools.py

@@ -4,6 +4,7 @@ import os
 import re
 from collections.abc import Iterator
 from pathlib import Path
+from typing import NotRequired, TypedDict
 
 from .preprocess import enumerate_source_files
 from .source import callers_of, product_files
@@ -67,11 +68,19 @@ def _mtime(path: Path) -> int:
         return -1
 
 
-def grep_repo(root: Path, pattern: str, *, max_matches: int) -> list[dict[str, object]]:
+class ToolMatch(TypedDict):
+    path: str
+    line: int
+    text: str
+    name: NotRequired[str]
+    source: NotRequired[str]
+
+
+def grep_repo(root: Path, pattern: str, *, max_matches: int) -> list[ToolMatch]:
     if max_matches <= 0:
         return []
     compiled = re.compile(pattern)
-    matches: list[dict[str, object]] = []
+    matches: list[ToolMatch] = []
     for relative, lines in _source_lines(root):
         for line_no, line in enumerate(lines, start=1):
             if compiled.search(line):
@@ -81,7 +90,7 @@ def grep_repo(root: Path, pattern: str, *, max_matches: int) -> list[dict[str, o
     return matches
 
 
-def find_refs(root: Path, symbol: str) -> list[dict[str, object]]:
+def find_refs(root: Path, symbol: str) -> list[ToolMatch]:
     if not symbol:
         return []
     lines = dict(_source_lines(root))

src/openultrasast/learn/labels.py

@@ -752,8 +752,11 @@ class LabelBuilder:
                 if not function:
                     lines = self._clone(population, str(case["id"])).lines(str(case["vulnerable"]), site_path)
                     language = detect_language(Path(site_path))
-                    covered = lines and language in DECLARATION and line <= len(lines)
-                    function = enclosing(lines, line - 1, language) if covered else MODULE_FUNCTION
+                    function = (
+                        enclosing(lines, line - 1, language)
+                        if lines and language in DECLARATION and line <= len(lines)
+                        else MODULE_FUNCTION
+                    )
                 self._row(
                     candidate=f"{site_path}::{function}", family=str(row.get("family") or case["family"]), label=label, source=source.id,
                     source_ref=f"{Path(path).name}#{key}[{index}]", unit="pin", weight=1.0, split=population.id,

src/openultrasast/model/candidates.py

@@ -20,7 +20,7 @@ from dataclasses import dataclass, field
 from pathlib import Path
 from typing import TYPE_CHECKING, Literal
 
-from ..source import canonical_language
+from ..source import FunctionRange, canonical_language
 
 if TYPE_CHECKING:
     from .taxonomy import FamilyTaxonomy
@@ -368,7 +368,7 @@ def labeled_family(case: object, taxonomy: FamilyTaxonomy | None = None) -> str:
 
 
 def labeled_spans(
-    case: object, ranges: Mapping[str, Sequence[tuple[str, int, int]]], *, function: str = ""
+    case: object, ranges: Mapping[str, Sequence[tuple[str, int, int] | FunctionRange]], *, function: str = ""
 ) -> tuple[tuple[str, int, int], ...]:
     """The (path, start, end) spans of the labeled functions; ``function`` overrides the label for the fixed side.
 
@@ -378,6 +378,7 @@ def labeled_spans(
     wanted = {function} if function else {str(getattr(row, "function", "") or "") for row in getattr(case, "expected", ()) or ()}
     wanted.discard("")
     found: list[tuple[str, int, int]] = []
+    _kind: list[str]
     for path, entries in ranges.items():
         for name, start, end, *_kind in entries:
             if name in wanted:

src/openultrasast/plane/runner.py

@@ -704,7 +704,7 @@ def safe_url(url: str) -> str:
 def deliver(
     url: str,
     payload: bytes,
-    headers: Mapping[str, str],
+    headers: MutableMapping[str, str],
     *,
     attempts: int = DELIVERY_ATTEMPTS,
     backoff: float = 1.0,
@@ -732,7 +732,7 @@ def deliver(
     raise DeliveryError(f"{last} after {attempts} attempts to {safe_url(url)}")
 
 
-def fetch(url: str, headers: Mapping[str, str], dest: Path, *, attempts: int = DELIVERY_ATTEMPTS, backoff: float = 1.0) -> int:
+def fetch(url: str, headers: MutableMapping[str, str], dest: Path, *, attempts: int = DELIVERY_ATTEMPTS, backoff: float = 1.0) -> int:
     """GET ``url`` into ``dest`` (streamed to a sibling temp file, then renamed); retried like :func:`deliver`.
 
     Returns the byte count; :class:`DeliveryError` names the last cause when every attempt failed."""

src/openultrasast/search/verify.py

@@ -409,9 +409,11 @@ def _side(side: Side, demo: Path, family: str, timeout: int, browser: BrowserExe
                     if task_boundary:
                         # Files are app data, so resolve their paths before writing;
                         # the task runner only translates argv and environment.
+                        def fixture_path(_: re.Match[str], path: str = str(canary.root)) -> str:
+                            return path
+
                         file_bindings = {
-                            key: re.sub(r"/(?:fixture|scratch)(?=/|$)", lambda _, path=str(canary.root): path, value)
-                            for key, value in bindings.items()
+                            key: re.sub(r"/(?:fixture|scratch)(?=/|$)", fixture_path, value) for key, value in bindings.items()
                         }
                     private_values.extend((*bindings.values(), *file_bindings.values()))
                     write_start_files(checkout, start_spec, file_bindings)

src/openultrasast/source.py

@@ -307,6 +307,7 @@ _HEAD = re.compile(
 def _regex_ranges(text: str, language: str) -> tuple[FunctionRange, ...]:
     lines, code = text.splitlines(), _code_lines(text)
     result = []
+    end: int | None
     for index, line in enumerate(code):
         name = declarator_name(line, language)
         if language == "python":

src/openultrasast/stats.py

@@ -167,7 +167,7 @@ def separation(frame: Any, label: str, columns: Iterable[str]) -> Any:
     import pandas as pd
     from sklearn.metrics import roc_auc_score
 
-    rows = []
+    rows: list[dict[str, str | float | None]] = []
     labelled = frame[frame[label].isin([0, 1])]
     for column in columns:
         series = pd.to_numeric(labelled[column], errors="coerce") if column in labelled else None