REFACTOR-modin-project#6845: Fix import issues found by CodeQL

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

modin/conftest.py

@@ -80,7 +80,6 @@ def _saving_make_api_url(token, _make_api_url=modin.utils._make_api_url):
     make_default_file,
     teardown_test_files,
 )
-from modin.utils import get_current_execution  # noqa: E402
 
 
 def pytest_addoption(parser):
@@ -275,7 +274,7 @@ def pytest_runtest_call(item):
             if not isinstance(executions, list):
                 executions = [executions]
 
-            current_execution = get_current_execution()
+            current_execution = modin.utils.get_current_execution()
             reason = marker.kwargs.pop("reason", "")
 
             item.add_marker(

modin/experimental/core/execution/native/implementations/hdk_on_native/dataframe/dataframe.py

@@ -1887,7 +1887,7 @@ def filter(self, key):
         )
 
         if self is base:
-            exprs = OrderedDict()
+            exprs = dict()
             for col in filtered_base._table_cols:
                 exprs[col] = filtered_base.ref(col)
         else:
@@ -1899,7 +1899,8 @@ def filter(self, key):
             if base._index_cols is None:
                 idx_name = mangle_index_names([None])[0]
                 exprs[idx_name] = filtered_base.ref(idx_name)
-                exprs.move_to_end(idx_name, last=False)
+                # `idx_name` should be first
+                exprs = {idx_name: filtered_base.ref(idx_name)} | exprs
 
         return self.__constructor__(
             columns=self.columns,

modin/experimental/core/execution/native/implementations/hdk_on_native/dataframe/utils.py

@@ -14,15 +14,12 @@
 """Utilities for internal use by the ``HdkOnNativeDataframe``."""
 
 import re
-import typing
-from collections import OrderedDict
 from functools import lru_cache
-from typing import Any, List, Tuple, Union
+from typing import Any, Dict, List, Tuple, Union
 
 import numpy as np
 import pandas
 import pyarrow as pa
-from pandas import Timestamp
 from pandas.core.arrays.arrow.extension_types import ArrowIntervalType
 from pandas.core.dtypes.common import _get_dtype, is_string_dtype
 from pyarrow.types import is_dictionary
@@ -40,7 +37,7 @@ class ColNameCodec:
 
     _IDX_NAME_PATTERN = re.compile(f"{IDX_COL_NAME}\\d+_(.*)")
     _RESERVED_NAMES = (MODIN_UNNAMED_SERIES_LABEL, ROWID_COL_NAME)
-    _COL_TYPES = Union[str, int, float, Timestamp, None]
+    _COL_TYPES = Union[str, int, float, pandas.Timestamp, None]
     _COL_NAME_TYPE = Union[_COL_TYPES, Tuple[_COL_TYPES, ...]]
 
     def _encode_tuple(values: Tuple[_COL_TYPES, ...]) -> str:  # noqa: GL08
@@ -73,7 +70,7 @@ def _decode_tuple(encoded: str) -> Tuple[_COL_TYPES, ...]:  # noqa: GL08
         str: lambda v: "_E" if len(v) == 0 else "_S" + v[1:] if v[0] == "_" else v,
         int: lambda v: f"_I{v}",
         float: lambda v: f"_F{v}",
-        Timestamp: lambda v: f"_D{v.timestamp()}_{v.tz}",
+        pandas.Timestamp: lambda v: f"_D{v.timestamp()}_{v.tz}",
     }
 
     _DECODERS = {
@@ -83,7 +80,7 @@ def _decode_tuple(encoded: str) -> Tuple[_COL_TYPES, ...]:  # noqa: GL08
         "S": lambda v: "_" + v[2:],
         "I": lambda v: int(v[2:]),
         "F": lambda v: float(v[2:]),
-        "D": lambda v: Timestamp.fromtimestamp(
+        "D": lambda v: pandas.Timestamp.fromtimestamp(
             float(v[2 : (idx := v.index("_", 2))]), tz=v[idx + 1 :]
         ),
     }
@@ -225,7 +222,7 @@ def demangle_index_name(col: str) -> _COL_NAME_TYPE:
         return col
 
     @staticmethod
-    def concat_index_names(frames) -> typing.OrderedDict[str, Any]:
+    def concat_index_names(frames) -> Dict[str, Any]:
         """
         Calculate the index names and dtypes.
 
@@ -238,10 +235,10 @@ def concat_index_names(frames) -> typing.OrderedDict[str, Any]:
 
         Returns
         -------
-        typing.OrderedDict[str, Any]
+        Dict[str, Any]
         """
         first = frames[0]
-        names = OrderedDict()
+        names = {}
         if first._index_width() > 1:
             # When we're dealing with a MultiIndex case the resulting index
             # inherits the levels from the first frame in concatenation.
@@ -413,7 +410,7 @@ def to_empty_pandas_df(df):
         return pandas.DataFrame(columns=df.columns, index=idx)
 
     new_dtypes = []
-    exprs = OrderedDict()
+    exprs = {}
     merged = to_empty_pandas_df(left).merge(
         to_empty_pandas_df(right),
         how=how,
@@ -586,8 +583,7 @@ class _CategoricalDtypeMapper:  # noqa: GL08
     @staticmethod
     def __from_arrow__(arr):  # noqa: GL08
         values = []
-        # Using OrderedDict as an ordered set to preserve the categories order
-        categories = OrderedDict()
+        categories = {}
         chunks = arr.chunks if isinstance(arr, pa.ChunkedArray) else (arr,)
         for chunk in chunks:
             assert isinstance(chunk, pa.DictionaryArray)

modin/experimental/core/execution/native/implementations/hdk_on_native/df_algebra.py

@@ -14,8 +14,6 @@
 """Module provides classes for lazy DataFrame algebra operations."""
 
 import abc
-import typing
-from collections import OrderedDict
 from typing import TYPE_CHECKING, Dict, List, Union
 
 import numpy as np
@@ -971,7 +969,7 @@ def execute_arrow(self, tables: Union[pa.Table, List[pa.Table]]) -> pa.Table:
         except pa.lib.ArrowInvalid:
             # Probably, some tables have different column types.
             # Trying to find a common type and cast the columns.
-            fields: typing.OrderedDict[str, pa.Field] = OrderedDict()
+            fields: Dict[str, pa.Field] = {}
             for table in tables:
                 for col_name in table.column_names:
                     field = table.field(col_name)
@@ -1178,7 +1176,7 @@ def translate_exprs_to_base(exprs, base):
         new_frames.discard(base)
         frames = new_frames
 
-    res = OrderedDict()
+    res = {}
     for col in exprs.keys():
         res[col] = new_exprs[col]
     return res
@@ -1205,7 +1203,7 @@ def replace_frame_in_exprs(exprs, old_frame, new_frame):
     mapper = InputMapper()
     mapper.add_mapper(old_frame, FrameMapper(new_frame))
 
-    res = OrderedDict()
+    res = {}
     for col in exprs.keys():
         res[col] = exprs[col].translate_input(mapper)
     return res