MNT update to mypy=1.3 (scikit-learn#26632)

adrinjalali · web-flow · commit 4655d8b7a606 · 2023-06-20T18:01:38.000+02:00
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
@@ -15,7 +15,7 @@ repos:
     hooks:
     -   id: ruff
 -   repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v0.961
+    rev: v1.3.0
     hooks:
      -  id: mypy
         files: sklearn/
diff --git a/setup.cfg b/setup.cfg
@@ -28,6 +28,8 @@ filterwarnings =
 [mypy]
 ignore_missing_imports = True
 allow_redefinition = True
+exclude=
+    sklearn/externals
 
 [check-manifest]
 # ignore files missing in VCS
diff --git a/sklearn/_min_dependencies.py b/sklearn/_min_dependencies.py
@@ -39,7 +39,7 @@
     "pytest-cov": ("2.9.0", "tests"),
     "ruff": ("0.0.272", "tests"),
     "black": ("23.3.0", "tests"),
-    "mypy": ("0.961", "tests"),
+    "mypy": ("1.3", "tests"),
     "pyamg": ("4.0.0", "tests"),
     "sphinx": ("4.0.1", "docs"),
     "sphinx-gallery": ("0.7.0", "docs"),
diff --git a/sklearn/cluster/_hdbscan/hdbscan.py b/sklearn/cluster/_hdbscan/hdbscan.py
@@ -62,7 +62,7 @@
 # Encodings are arbitrary but must be strictly negative.
 # The current encodings are chosen as extensions to the -1 noise label.
 # Avoided enums so that the end user only deals with simple labels.
-_OUTLIER_ENCODING = {
+_OUTLIER_ENCODING: dict = {
     "infinite": {
         "label": -2,
         # The probability could also be 1, since infinite points are certainly
diff --git a/sklearn/tests/test_metaestimators_metadata_routing.py b/sklearn/tests/test_metaestimators_metadata_routing.py
@@ -171,7 +171,7 @@ def predict_log_proba(self, X, sample_weight="default", metadata="default"):
         # return np.zeros(shape=(len(X), 2))
 
 
-METAESTIMATORS = [
+METAESTIMATORS: list = [
     {
         "metaestimator": MultiOutputRegressor,
         "estimator_name": "estimator",

Original file line number	Diff line number	Diff line change
`@@ -171,7 +171,7 @@ def predict_log_proba(self, X, sample_weight="default", metadata="default"):`
`171`	`171`	`# return np.zeros(shape=(len(X), 2))`
`172`	`172`
`173`	`173`
`174`		`-METAESTIMATORS = [`
	`174`	`+METAESTIMATORS: list = [`
`175`	`175`	`{`
`176`	`176`	`"metaestimator": MultiOutputRegressor,`
`177`	`177`	`"estimator_name": "estimator",`