CI Cleanup pytest warning/errors (#495)

* Clean up deprecation warnings in pyproject.toml

Ran the gha on my fork and all besides 1 is still needed.

* ignore `PassiveAggressiveClassifier`'s `FutureWarning`

Co-authored-by: Adrin Jalali <[email protected]>

* ignore PassiveAgressive(Classifier|Regressor) warnings

* fix SparseCoder test

---------

Co-authored-by: Adrin Jalali <[email protected]>

Author: divakaivan

pyproject.toml

@@ -70,30 +70,11 @@ doctest_optionflags = "NORMALIZE_WHITESPACE ELLIPSIS"
 filterwarnings = [
     "error::DeprecationWarning",
     "error::FutureWarning",
-    # TODO: remove when no longer supporting sklearn v1.0
-    # numpy and scipy deprecation warnings in sklearn:
-    'ignore:\n\n  \`numpy.distutils\` is deprecated since NumPy:DeprecationWarning',
-    # https://github.com/scikit-learn/scikit-learn/issues/24080
-    "ignore:The \\'sym_pos\\' keyword is deprecated and should be replaced:DeprecationWarning",
-    # https://github.com/scikit-learn/scikit-learn/pull/23633
-    "ignore:Unlike other reduction functions:FutureWarning",
-    # https://github.com/scikit-learn/scikit-learn/pull/25157
-    "ignore:\\w+ is deprecated. Use files\\(\\) instead:DeprecationWarning",
     # comes from fairlearn
-    "ignore:DataFrame.applymap has been deprecated. Use DataFrame.map instead:FutureWarning",
     "ignore:DataFrameGroupBy.apply operated on the grouping columns.:DeprecationWarning",
-    # Ignore Pandas 2.2 warning on PyArrow. It might be reverted in a later release.
-    "ignore:\\s*Pyarrow will become a required dependency of pandas.*:DeprecationWarning",
-    # LightGBM sklearn 1.6 deprecation warning, fixed in the next release
-    "ignore:'force_all_finite' was renamed to 'ensure_all_finite' in 1.6 and will be removed in 1.8.:FutureWarning",
-    # RandomForestQuantileRegressor tags deprecation warning in sklearn 1.7
-    "ignore:The RandomForestQuantileRegressor or classes from which it inherits use `_get_tags` and `_more_tags`:FutureWarning",
-    # ExtraTreesQuantileRegressor tags deprecation warning in sklearn 1.7
-    "ignore:The ExtraTreesQuantileRegressor or classes from which it inherits use `_get_tags` and `_more_tags`:FutureWarning",
-    # BaseEstimator._validate_data deprecation warning in sklearn 1.6 #TODO can be removed when a new release of quantile-forest is out
-    "ignore:`BaseEstimator._validate_data` is deprecated in 1.6 and will be removed in 1.7:FutureWarning",
-    # This comes from matplotlib somehow
-    "ignore:'mode' parameter is deprecated and will be removed in Pillow 13:DeprecationWarning",
+    # sklearn1.8 deprecates this class
+    "ignore:Class PassiveAggressiveClassifier is deprecated:FutureWarning",
+    "ignore:Class PassiveAggressiveRegressor is deprecated:FutureWarning",
 ]
 addopts = "--cov=skops --cov-report=term-missing --doctest-modules"
 

skops/io/tests/test_persist.py

@@ -148,6 +148,16 @@ def _tested_estimators(type_filter=None):
                     # default solver will be "highs" from scikit-learn >= 1.4.0.
                     # https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.QuantileRegressor.html
                     estimators = construct_instances(partial(Estimator, solver="highs"))
+                elif name == "SparseCoder":
+                    dictionary = np.random.randint(-2, 3, size=(5, N_FEATURES)).astype(
+                        float
+                    )
+                    estimators = [
+                        SparseCoder(
+                            dictionary=dictionary,
+                            transform_algorithm="lasso_lars",
+                        )
+                    ]
                 else:
                     estimators = construct_instances(Estimator)
 
@@ -247,12 +257,6 @@ def _tested_estimators(type_filter=None):
         n_iter=3,
     )
 
-    dictionary = np.random.randint(-2, 3, size=(5, N_FEATURES)).astype(float)
-    yield SparseCoder(
-        dictionary=dictionary,
-        transform_algorithm="lasso_lars",
-    )
-
 
 def _tested_ufuncs():
     for full_name in SCIPY_UFUNC_TYPE_NAMES + NUMPY_UFUNC_TYPE_NAMES: