REFACTOR-modin-project#7285: Remove deprecated configs

Signed-off-by: Igoshev, Iaroslav <[email protected]>
YarShev · May 21, 2024 · 8a24845 · 8a24845
1 parent 43eff5b
commit 8a24845
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Showing 8 changed files with 17 additions and 277 deletions.
diff --git a/modin/config/__init__.py b/modin/config/__init__.py
@@ -25,8 +25,6 @@
     DocModule,
     Engine,
     EnvironmentVariable,
-    ExperimentalGroupbyImpl,
-    ExperimentalNumPyAPI,
     GithubCI,
     GpuCount,
     IsDebug,
@@ -43,7 +41,6 @@
     PersistentPickle,
     ProgressBar,
     RangePartitioning,
-    RangePartitioningGroupby,
     RayInitCustomResources,
     RayRedisAddress,
     RayRedisPassword,
@@ -54,7 +51,6 @@
     TestReadFromPostgres,
     TestReadFromSqlServer,
     TrackFileLeaks,
-    use_range_partitioning_groupby,
 )
 from modin.config.pubsub import Parameter, ValueSource, context
 
@@ -91,11 +87,7 @@
     "BenchmarkMode",
     "PersistentPickle",
     "ModinNumpy",
-    "ExperimentalNumPyAPI",
-    "RangePartitioningGroupby",
     "RangePartitioning",
-    "use_range_partitioning_groupby",
-    "ExperimentalGroupbyImpl",
     "AsyncReadMode",
     "ReadSqlEngine",
     "IsExperimental",

diff --git a/modin/config/envvars.py b/modin/config/envvars.py
@@ -683,40 +683,12 @@ class GithubCI(EnvironmentVariable, type=bool):
     default = False
 
 
-class ModinNumpy(EnvWithSibilings, type=bool):
+class ModinNumpy(EnvironmentVariable, type=bool):
     """Set to true to use Modin's implementation of NumPy API."""
 
     varname = "MODIN_NUMPY"
     default = False
 
-    @classmethod
-    def _sibling(cls) -> type[EnvWithSibilings]:
-        """Get a parameter sibling."""
-        return ExperimentalNumPyAPI
-
-
-class ExperimentalNumPyAPI(EnvWithSibilings, type=bool):
-    """
-    Set to true to use Modin's implementation of NumPy API.
-
-    This parameter is deprecated. Use ``ModinNumpy`` instead.
-    """
-
-    varname = "MODIN_EXPERIMENTAL_NUMPY_API"
-    default = False
-
-    @classmethod
-    def _sibling(cls) -> type[EnvWithSibilings]:
-        """Get a parameter sibling."""
-        return ModinNumpy
-
-
-# Let the parameter's handling logic know that this variable is deprecated and that
-# we should raise respective warnings
-ExperimentalNumPyAPI._deprecation_descriptor = DeprecationDescriptor(
-    ExperimentalNumPyAPI, ModinNumpy
-)
-
 
 class RangePartitioning(EnvironmentVariable, type=bool):
     """
@@ -730,72 +702,6 @@ class RangePartitioning(EnvironmentVariable, type=bool):
     default = False
 
 
-class RangePartitioningGroupby(EnvWithSibilings, type=bool):
-    """
-    Set to true to use Modin's range-partitioning group by implementation.
-
-    This parameter is deprecated. Use ``RangePartitioning`` instead.
-    """
-
-    varname = "MODIN_RANGE_PARTITIONING_GROUPBY"
-    default = False
-
-    @classmethod
-    def _sibling(cls) -> type[EnvWithSibilings]:
-        """Get a parameter sibling."""
-        return ExperimentalGroupbyImpl
-
-
-# Let the parameter's handling logic know that this variable is deprecated and that
-# we should raise respective warnings
-RangePartitioningGroupby._deprecation_descriptor = DeprecationDescriptor(
-    RangePartitioningGroupby, RangePartitioning
-)
-
-
-class ExperimentalGroupbyImpl(EnvWithSibilings, type=bool):
-    """
-    Set to true to use Modin's range-partitioning group by implementation.
-
-    This parameter is deprecated. Use ``RangePartitioning`` instead.
-    """
-
-    varname = "MODIN_EXPERIMENTAL_GROUPBY"
-    default = False
-
-    @classmethod
-    def _sibling(cls) -> type[EnvWithSibilings]:
-        """Get a parameter sibling."""
-        return RangePartitioningGroupby
-
-
-# Let the parameter's handling logic know that this variable is deprecated and that
-# we should raise respective warnings
-ExperimentalGroupbyImpl._deprecation_descriptor = DeprecationDescriptor(
-    ExperimentalGroupbyImpl, RangePartitioningGroupby
-)
-
-
-def use_range_partitioning_groupby() -> bool:
-    """
-    Determine whether range-partitioning implementation for groupby was enabled by a user.
-
-    This is a temporary helper function that queries ``RangePartitioning`` and deprecated
-    ``RangePartitioningGroupby`` config variables in order to determine whether to range-part
-    impl for groupby is enabled. Eventially this function should be removed together with
-    ``RangePartitioningGroupby`` variable.
-
-    Returns
-    -------
-    bool
-    """
-    with warnings.catch_warnings():
-        # filter deprecation warning, it was already showed when a user set the variable
-        warnings.filterwarnings("ignore", category=FutureWarning)
-        old_range_part_var = RangePartitioningGroupby.get()
-    return RangePartitioning.get() or old_range_part_var
-
-
 class CIAWSSecretAccessKey(EnvironmentVariable, type=str):
     """Set to AWS_SECRET_ACCESS_KEY when running mock S3 tests for Modin in GitHub CI."""
 

diff --git a/modin/core/storage_formats/pandas/groupby.py b/modin/core/storage_formats/pandas/groupby.py
@@ -17,7 +17,7 @@
 import pandas
 from pandas.core.dtypes.cast import find_common_type
 
-from modin.config import use_range_partitioning_groupby
+from modin.config import RangePartitioning
 from modin.core.dataframe.algebra import GroupByReduce
 from modin.error_message import ErrorMessage
 from modin.utils import hashable
@@ -94,7 +94,7 @@ def build_qc_method(cls, agg_name, finalizer_fn=None):
         )
 
         def method(query_compiler, *args, **kwargs):
-            if use_range_partitioning_groupby():
+            if RangePartitioning.get():
                 try:
                     if finalizer_fn is not None:
                         raise NotImplementedError(

diff --git a/modin/core/storage_formats/pandas/query_compiler.py b/modin/core/storage_formats/pandas/query_compiler.py
@@ -45,7 +45,7 @@
 from pandas.core.indexing import check_bool_indexer
 from pandas.errors import DataError
 
-from modin.config import CpuCount, RangePartitioning, use_range_partitioning_groupby
+from modin.config import CpuCount, RangePartitioning
 from modin.core.dataframe.algebra import (
     Binary,
     Fold,
@@ -3625,7 +3625,7 @@ def groupby_nth(
         return result
 
     def groupby_mean(self, by, axis, groupby_kwargs, agg_args, agg_kwargs, drop=False):
-        if use_range_partitioning_groupby():
+        if RangePartitioning.get():
             try:
                 return self._groupby_shuffle(
                     by=by,
@@ -3696,7 +3696,7 @@ def groupby_size(
         agg_kwargs,
         drop=False,
     ):
-        if use_range_partitioning_groupby():
+        if RangePartitioning.get():
             try:
                 return self._groupby_shuffle(
                     by=by,
@@ -4117,7 +4117,7 @@ def groupby_agg(
         # 'group_wise' means 'groupby.apply()'. We're certain that range-partitioning groupby
         # always works better for '.apply()', so we're using it regardless of the 'RangePartitioning'
         # value
-        if how == "group_wise" or use_range_partitioning_groupby():
+        if how == "group_wise" or RangePartitioning.get():
             try:
                 return self._groupby_shuffle(
                     by=by,
@@ -4138,7 +4138,7 @@ def groupby_agg(
                     + "\nFalling back to a full-axis implementation."
                 )
                 get_logger().info(message)
-                if use_range_partitioning_groupby():
+                if RangePartitioning.get():
                     ErrorMessage.warn(message)
 
         if isinstance(agg_func, dict) and GroupbyReduceImpl.has_impl_for(agg_func):

diff --git a/modin/pandas/io.py b/modin/pandas/io.py
@@ -64,7 +64,7 @@
 from pandas.io.parsers import TextFileReader
 from pandas.io.parsers.readers import _c_parser_defaults
 
-from modin.config import ExperimentalNumPyAPI
+from modin.config import ModinNumpy
 from modin.error_message import ErrorMessage
 from modin.logging import ClassLogger, enable_logging
 from modin.utils import (
@@ -1146,7 +1146,7 @@ def to_numpy(
     if isinstance(modin_obj, SupportsPrivateToNumPy):
         return modin_obj._to_numpy()
     array = modin_obj.to_numpy()
-    if ExperimentalNumPyAPI.get():
+    if ModinNumpy.get():
         array = array._to_numpy()
     return array
 

diff --git a/modin/tests/config/test_envvars.py b/modin/tests/config/test_envvars.py
@@ -12,8 +12,6 @@
 # governing permissions and limitations under the License.
 
 import os
-import unittest.mock
-import warnings
 
 import pytest
 
@@ -121,154 +119,6 @@ def test_ray_cluster_resources():
     assert ray.cluster_resources()["special_hardware"] == 1.0
 
 
-@pytest.mark.parametrize(
-    "deprecated_var, new_var",
-    [
-        (cfg.ExperimentalGroupbyImpl, cfg.RangePartitioning),
-        (cfg.ExperimentalNumPyAPI, cfg.ModinNumpy),
-        (cfg.RangePartitioningGroupby, cfg.RangePartitioning),
-    ],
-)
-def test_deprecated_bool_vars_warnings(deprecated_var, new_var):
-    """Test that deprecated parameters are raising `FutureWarnings` and their replacements don't."""
-    old_depr_val = deprecated_var.get()
-    old_new_var = new_var.get()
-
-    try:
-        reset_vars(deprecated_var, new_var)
-        with pytest.warns(FutureWarning):
-            deprecated_var.get()
-
-        with pytest.warns(FutureWarning):
-            deprecated_var.put(False)
-
-        with unittest.mock.patch.dict(os.environ, {deprecated_var.varname: "1"}):
-            with pytest.warns(FutureWarning):
-                _check_vars()
-
-        # check that the new var doesn't raise any warnings
-        reset_vars(deprecated_var, new_var)
-        with warnings.catch_warnings():
-            warnings.simplefilter("error")
-            new_var.get()
-            new_var.put(False)
-            with unittest.mock.patch.dict(os.environ, {new_var.varname: "1"}):
-                _check_vars()
-    finally:
-        deprecated_var.put(old_depr_val)
-        new_var.put(old_new_var)
-
-
-@pytest.mark.parametrize(
-    "deprecated_var, new_var",
-    [
-        (cfg.ExperimentalGroupbyImpl, cfg.RangePartitioningGroupby),
-        (cfg.ExperimentalNumPyAPI, cfg.ModinNumpy),
-    ],
-)
-@pytest.mark.parametrize("get_depr_first", [True, False])
-def test_deprecated_bool_vars_equals(deprecated_var, new_var, get_depr_first):
-    """
-    Test that deprecated parameters always have values equal to the new replacement parameters.
-
-    Parameters
-    ----------
-    deprecated_var : EnvironmentVariable
-    new_var : EnvironmentVariable
-    get_depr_first : bool
-        Defines an order in which the ``.get()`` method should be called when comparing values.
-        If ``True``: get deprecated value at first ``deprecated_var.get() == new_var.get() == value``.
-        If ``False``: get new value at first ``new_var.get() == deprecated_var.get() == value``.
-        The logic of the ``.get()`` method depends on which parameter was initialized first,
-        that's why it's worth testing both cases.
-    """
-    old_depr_val = deprecated_var.get()
-    old_new_var = new_var.get()
-
-    def get_values():
-        return (
-            (deprecated_var.get(), new_var.get())
-            if get_depr_first
-            else (new_var.get(), deprecated_var.get())
-        )
-
-    try:
-        # case1: initializing the value using 'deprecated_var'
-        reset_vars(deprecated_var, new_var)
-        deprecated_var.put(True)
-        val1, val2 = get_values()
-        assert val1 == val2 == True  # noqa: E712 ('obj == True' comparison)
-
-        new_var.put(False)
-        val1, val2 = get_values()
-        assert val1 == val2 == False  # noqa: E712 ('obj == False' comparison)
-
-        new_var.put(True)
-        val1, val2 = get_values()
-        assert val1 == val2 == True  # noqa: E712 ('obj == True' comparison)
-
-        deprecated_var.put(False)
-        val1, val2 = get_values()
-        assert val1 == val2 == False  # noqa: E712 ('obj == False' comparison)
-
-        # case2: initializing the value using 'new_var'
-        reset_vars(deprecated_var, new_var)
-        new_var.put(True)
-        val1, val2 = get_values()
-        assert val1 == val2 == True  # noqa: E712 ('obj == True' comparison)
-
-        deprecated_var.put(False)
-        val1, val2 = get_values()
-        assert val1 == val2 == False  # noqa: E712 ('obj == False' comparison)
-
-        deprecated_var.put(True)
-        val1, val2 = get_values()
-        assert val1 == val2 == True  # noqa: E712 ('obj == True' comparison)
-
-        new_var.put(False)
-        val1, val2 = get_values()
-        assert val1 == val2 == False  # noqa: E712 ('obj == False' comparison)
-
-        # case3: initializing the value using 'deprecated_var' with env variable
-        reset_vars(deprecated_var, new_var)
-        with unittest.mock.patch.dict(os.environ, {deprecated_var.varname: "True"}):
-            val1, val2 = get_values()
-            assert val1 == val2 == True  # noqa: E712 ('obj == True' comparison)
-
-            new_var.put(False)
-            val1, val2 = get_values()
-            assert val1 == val2 == False  # noqa: E712 ('obj == False' comparison)
-
-            new_var.put(True)
-            val1, val2 = get_values()
-            assert val1 == val2 == True  # noqa: E712 ('obj == True' comparison)
-
-            deprecated_var.put(False)
-            val1, val2 = get_values()
-            assert val1 == val2 == False  # noqa: E712 ('obj == False' comparison)
-
-        # case4: initializing the value using 'new_var' with env variable
-        reset_vars(deprecated_var, new_var)
-        with unittest.mock.patch.dict(os.environ, {new_var.varname: "True"}):
-            val1, val2 = get_values()
-            assert val1 == val2 == True  # noqa: E712 ('obj == True' comparison)
-
-            deprecated_var.put(False)
-            val1, val2 = get_values()
-            assert val1 == val2 == False  # noqa: E712 ('obj == False' comparison)
-
-            deprecated_var.put(True)
-            val1, val2 = get_values()
-            assert val1 == val2 == True  # noqa: E712 ('obj == True' comparison)
-
-            new_var.put(False)
-            val1, val2 = get_values()
-            assert val1 == val2 == False  # noqa: E712 ('obj == False' comparison)
-    finally:
-        deprecated_var.put(old_depr_val)
-        new_var.put(old_new_var)
-
-
 @pytest.mark.parametrize(
     "modify_config",
     [{cfg.RangePartitioning: False, cfg.LazyExecution: "Auto"}],