fix issues with pandas pylint and flake8

mlem/contrib/pandas.py

@@ -459,7 +459,9 @@ def read_pickle_with_unnamed(*args, **kwargs):
 
 
 def read_json_reset_index(*args, **kwargs):
-    return pd.read_json(*args, **kwargs).reset_index(drop=True)
+    return pd.read_json(  # pylint: disable=no-member
+        *args, **kwargs
+    ).reset_index(drop=True)
 
 
 def read_html(*args, **kwargs):

mlem/utils/module.py

@@ -411,7 +411,10 @@ def wrapper(pickler: "RequirementAnalyzer", obj):
                 else:
                     pickler.save(o)
 
-        if is_from_installable_module(obj):
+        if (
+            is_from_installable_module(obj)
+            or get_object_base_module(obj) is mlem
+        ):
             return f(pickler, obj)
 
         # to add from local imports inside user (non PIP package) code
@@ -514,6 +517,7 @@ def _should_ignore(self, mod: ModuleType):
             or is_private_module(mod)
             or is_pseudo_module(mod)
             or is_builtin_module(mod)
+            or mod in self._modules
         )
 
     def add_requirement(self, obj_or_module):
@@ -533,6 +537,11 @@ def add_requirement(self, obj_or_module):
             module = obj_or_module
 
         if module is not None and not self._should_ignore(module):
+            base_module = get_base_module(module)
+            if is_installable_module(base_module):
+                if base_module in self._modules:
+                    return
+                module = base_module
             self._modules.add(module)
             if is_local_module(module):
                 # add imports of this module
@@ -553,6 +562,8 @@ def save(self, obj, save_persistent_id=True):
         if id(obj) in self.seen or isinstance(obj, IGNORE_TYPES_REQ):
             return None
         self.seen.add(id(obj))
+        if get_object_base_module(obj) in self._modules:
+            return None
         self.add_requirement(obj)
         try:
             return super().save(obj, save_persistent_id)

setup.cfg

@@ -5,8 +5,9 @@ ignore =
     E266, # Too many leading '#' for block comment
     W503, # Line break occurred before a binary operator
     B008, # Do not perform function calls in argument defaults: conflicts with typer
-    P1,  # unindexed parameters in the str.format, see:
+    P1,   # unindexed parameters in the str.format, see:
     B902, # Invalid first argument 'cls' used for instance method.
+    B024, # ABCs without methods
     # https://pypi.org/project/flake8-string-format/
 max_line_length = 79
 max-complexity = 15

tests/contrib/test_catboost.py

@@ -48,7 +48,7 @@ def test_catboost_model(catboost_model_fixture, pandas_data, tmpdir, request):
         ),
     )
 
-    expected_requirements = {"catboost", "pandas", "numpy", "scipy"}
+    expected_requirements = {"catboost", "pandas"}
     reqs = set(cbmw.get_requirements().modules)
     assert all(r in reqs for r in expected_requirements)
     assert cbmw.model is catboost_model

tests/contrib/test_lightgbm.py

@@ -195,7 +195,7 @@ def test_model__predict_not_dataset(model):
 @long
 def test_model__dump_load(tmpdir, model, data_np, local_fs):
     # pandas is not required, but if it is installed, it is imported by lightgbm
-    expected_requirements = {"lightgbm", "numpy", "scipy", "pandas"}
+    expected_requirements = {"lightgbm", "numpy"}
     assert set(model.get_requirements().modules) == expected_requirements
 
     artifacts = model.dump(LOCAL_STORAGE, tmpdir)

tests/contrib/test_pandas.py

@@ -617,7 +617,7 @@ def f(x):
 
     sig = Signature.from_method(f, auto_infer=True, x=data)
 
-    assert set(get_object_requirements(sig).modules) == {"pandas", "numpy"}
+    assert set(get_object_requirements(sig).modules) == {"pandas"}
 
 
 # Copyright 2019 Zyfra

tests/contrib/test_sklearn.py

@@ -140,7 +140,7 @@ def test_model_type__dump_load(tmpdir, model, inp_data, request):
 def test_model_type_lgb__dump_load(tmpdir, lgbm_model, inp_data):
     model_type = ModelAnalyzer.analyze(lgbm_model, sample_data=inp_data)
 
-    expected_requirements = {"sklearn", "lightgbm", "pandas", "numpy", "scipy"}
+    expected_requirements = {"sklearn", "lightgbm", "numpy"}
     reqs = model_type.get_requirements().expanded
     assert set(reqs.modules) == expected_requirements
     assert reqs.of_type(UnixPackageRequirement) == [
@@ -164,11 +164,16 @@ def test_model_type_lgb__dump_load(tmpdir, lgbm_model, inp_data):
     ]
 
 
-def test_pipeline_requirements(lgbm_model):
+def test_pipeline_requirements(lgbm_model, inp_data):
     model = Pipeline(steps=[("model", lgbm_model)])
     meta = MlemModel.from_obj(model)
 
-    expected_requirements = {"sklearn", "lightgbm", "pandas", "numpy", "scipy"}
+    expected_requirements = {"sklearn", "lightgbm"}
+    assert set(meta.requirements.modules) == expected_requirements
+
+    meta = MlemModel.from_obj(model, sample_data=np.array(inp_data))
+
+    expected_requirements = {"sklearn", "lightgbm", "numpy"}
     assert set(meta.requirements.modules) == expected_requirements
 
 

tests/contrib/test_xgboost.py

@@ -132,8 +132,7 @@ def test_model__predict_not_dmatrix(model):
 
 @long
 def test_model__dump_load(tmpdir, model, dmatrix_np, local_fs):
-    # pandas is not required, but it is conditionally imported by some Booster methods
-    expected_requirements = {"xgboost", "numpy", "scipy", "pandas"}
+    expected_requirements = {"xgboost", "numpy"}
     assert set(model.get_requirements().modules) == expected_requirements
 
     artifacts = model.dump(LOCAL_STORAGE, tmpdir)