FIX-#6022: support lazy import of modin.pandas module (#6023)

Signed-off-by: Anatoly Myachev <anatoly.myachev@intel.com>

Author: anmyachev

.github/workflows/ci.yml

@@ -663,6 +663,9 @@ jobs:
       - run: pip install "dfsql>=0.4.2" "pyparsing<=2.4.7" && mpiexec -n 1 python -m pytest modin/experimental/sql/test/test_sql.py
       - run: mpiexec -n 1 python -m pytest modin/test/interchange/dataframe_protocol/test_general.py
       - run: mpiexec -n 1 python -m pytest modin/test/interchange/dataframe_protocol/pandas/test_protocol.py
+      - run: |
+          python -m pip install lazy_import
+          mpiexec -n 1 python -m pytest modin/pandas/test/integrations/
       - uses: ./.github/workflows/upload-coverage
 
   test-all:
@@ -823,6 +826,10 @@ jobs:
         if: matrix.engine == 'python' || matrix.test_task == 'group_4'
       - run: python -m pytest modin/test/interchange/dataframe_protocol/pandas/test_protocol.py
         if: matrix.engine == 'python' || matrix.test_task == 'group_4'
+      - run: |
+          python -m pip install lazy_import
+          python -m pytest modin/pandas/test/integrations/
+        if: matrix.engine == 'python' || matrix.test_task == 'group_4'
       - uses: ./.github/workflows/upload-coverage
 
   test-experimental:

modin/core/execution/ray/implementations/pandas_on_ray/partitioning/virtual_partition.py

@@ -26,12 +26,6 @@
 from modin.utils import _inherit_docstrings
 
 
-# If Ray has not been initialized yet by Modin,
-# it will be initialized when calling `RayWrapper.put`.
-_DEPLOY_AXIS_FUNC = RayWrapper.put(PandasDataframeAxisPartition.deploy_axis_func)
-_DRAIN = RayWrapper.put(PandasDataframeAxisPartition.drain)
-
-
 class PandasOnRayDataframeVirtualPartition(PandasDataframeAxisPartition):
     """
     The class implements the interface in ``PandasDataframeAxisPartition``.
@@ -58,6 +52,24 @@ class PandasOnRayDataframeVirtualPartition(PandasDataframeAxisPartition):
     instance_type = ray.ObjectRef
     axis = None
 
+    # these variables are intentionally initialized at runtime (see #6023)
+    _DEPLOY_AXIS_FUNC = None
+    _DRAIN_FUNC = None
+
+    @classmethod
+    def _get_deploy_axis_func(cls):  # noqa: GL08
+        if cls._DEPLOY_AXIS_FUNC is None:
+            cls._DEPLOY_AXIS_FUNC = RayWrapper.put(
+                PandasDataframeAxisPartition.deploy_axis_func
+            )
+        return cls._DEPLOY_AXIS_FUNC
+
+    @classmethod
+    def _get_drain_func(cls):  # noqa: GL08
+        if cls._DRAIN_FUNC is None:
+            cls._DRAIN_FUNC = RayWrapper.put(PandasDataframeAxisPartition.drain)
+        return cls._DRAIN_FUNC
+
     def __init__(
         self,
         list_of_partitions,
@@ -200,7 +212,7 @@ def deploy_axis_func(
             num_returns=(num_splits if lengths is None else len(lengths)) * 4,
             **({"max_retries": max_retries} if max_retries is not None else {}),
         ).remote(
-            _DEPLOY_AXIS_FUNC,
+            cls._get_deploy_axis_func(),
             axis,
             func,
             f_args,
@@ -473,7 +485,7 @@ def drain_call_queue(self, num_splits=None):
             _ = self.list_of_blocks
             return
         drained = super(PandasOnRayDataframeVirtualPartition, self).apply(
-            _DRAIN, num_splits=num_splits, call_queue=self.call_queue
+            self._get_drain_func(), num_splits=num_splits, call_queue=self.call_queue
         )
         self._list_of_block_partitions = drained
         self.call_queue = []

modin/core/execution/unidist/implementations/pandas_on_unidist/partitioning/virtual_partition.py

@@ -25,13 +25,6 @@
 from modin.utils import _inherit_docstrings
 
 
-# If unidist has not been initialized yet by Modin,
-# unidist itself handles initialization when calling `unidist.put`,
-# which is called inside of `UnidistWrapper.put`.
-_DEPLOY_AXIS_FUNC = UnidistWrapper.put(PandasDataframeAxisPartition.deploy_axis_func)
-_DRAIN = UnidistWrapper.put(PandasDataframeAxisPartition.drain)
-
-
 class PandasOnUnidistDataframeVirtualPartition(PandasDataframeAxisPartition):
     """
     The class implements the interface in ``PandasDataframeAxisPartition``.
@@ -58,6 +51,24 @@ class PandasOnUnidistDataframeVirtualPartition(PandasDataframeAxisPartition):
     instance_type = unidist.core.base.object_ref.ObjectRef
     axis = None
 
+    # these variables are intentionally initialized at runtime (see #6023)
+    _DEPLOY_AXIS_FUNC = None
+    _DRAIN_FUNC = None
+
+    @classmethod
+    def _get_deploy_axis_func(cls):  # noqa: GL08
+        if cls._DEPLOY_AXIS_FUNC is None:
+            cls._DEPLOY_AXIS_FUNC = UnidistWrapper.put(
+                PandasDataframeAxisPartition.deploy_axis_func
+            )
+        return cls._DEPLOY_AXIS_FUNC
+
+    @classmethod
+    def _get_drain_func(cls):  # noqa: GL08
+        if cls._DRAIN_FUNC is None:
+            cls._DRAIN_FUNC = UnidistWrapper.put(PandasDataframeAxisPartition.drain)
+        return cls._DRAIN_FUNC
+
     def __init__(
         self,
         list_of_partitions,
@@ -199,7 +210,7 @@ def deploy_axis_func(
             num_returns=(num_splits if lengths is None else len(lengths)) * 4,
             **({"max_retries": max_retries} if max_retries is not None else {}),
         ).remote(
-            _DEPLOY_AXIS_FUNC,
+            cls._get_deploy_axis_func(),
             axis,
             func,
             f_args,
@@ -466,7 +477,7 @@ def drain_call_queue(self, num_splits=None):
             _ = self.list_of_blocks
             return
         drained = super(PandasOnUnidistDataframeVirtualPartition, self).apply(
-            _DRAIN, num_splits=num_splits, call_queue=self.call_queue
+            self._get_drain_func(), num_splits=num_splits, call_queue=self.call_queue
         )
         self._list_of_block_partitions = drained
         self.call_queue = []

modin/pandas/test/integrations/__init__.py

@@ -0,0 +1,12 @@
+# Licensed to Modin Development Team under one or more contributor license agreements.
+# See the NOTICE file distributed with this work for additional information regarding
+# copyright ownership.  The Modin Development Team licenses this file to you under the
+# Apache License, Version 2.0 (the "License"); you may not use this file except in
+# compliance with the License.  You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software distributed under
+# the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
+# ANY KIND, either express or implied. See the License for the specific language
+# governing permissions and limitations under the License.

modin/pandas/test/integrations/test_lazy_import.py

@@ -0,0 +1,22 @@
+# Licensed to Modin Development Team under one or more contributor license agreements.
+# See the NOTICE file distributed with this work for additional information regarding
+# copyright ownership.  The Modin Development Team licenses this file to you under the
+# Apache License, Version 2.0 (the "License"); you may not use this file except in
+# compliance with the License.  You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software distributed under
+# the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
+# ANY KIND, either express or implied. See the License for the specific language
+# governing permissions and limitations under the License.
+
+import lazy_import
+
+pandas = lazy_import.lazy_module("pandas")
+pyarrow = lazy_import.lazy_module("pyarrow")
+from modin import pandas as pd  # noqa: E402
+
+
+def test_dataframe_constructor():
+    pd.DataFrame({"col1": [1, 2, 3], "col2": list("abc")})