Ruff linting fix (#365)

* ruff fixes for typing

* bump version: v0.16.0

datacompy/__init__.py

@@ -18,7 +18,7 @@
 Then extended to carry that functionality over to Spark Dataframes.
 """
 
-__version__ = "0.15.0"
+__version__ = "0.16.0"
 
 import platform
 from warnings import warn

datacompy/base.py

@@ -22,7 +22,7 @@
 """
 
 from abc import ABC, abstractmethod
-from typing import Any, Optional
+from typing import Any
 
 from ordered_set import OrderedSet
 
@@ -154,7 +154,7 @@ def report(
         self,
         sample_count: int = 10,
         column_count: int = 10,
-        html_file: Optional[str] = None,
+        html_file: str | None = None,
     ) -> str:
         """Return a string representation of a report."""
         pass

datacompy/core.py

@@ -22,7 +22,7 @@
 """
 
 import os
-from typing import Any, Dict, List, Optional, Union, cast
+from typing import Any, Dict, List, cast
 
 import numpy as np
 import pandas as pd
@@ -84,7 +84,7 @@ def __init__(
         self,
         df1: pd.DataFrame,
         df2: pd.DataFrame,
-        join_columns: Optional[Union[List[str], str]] = None,
+        join_columns: List[str] | str | None = None,
         on_index: bool = False,
         abs_tol: float = 0,
         rel_tol: float = 0,
@@ -100,7 +100,7 @@ def __init__(
         elif on_index:
             self.on_index = True
             self.join_columns = []
-        elif isinstance(join_columns, (str, int, float)):
+        elif isinstance(join_columns, str | int | float):
             self.join_columns = [
                 str(join_columns).lower()
                 if self.cast_column_names_lower
@@ -564,7 +564,7 @@ def report(
         self,
         sample_count: int = 10,
         column_count: int = 10,
-        html_file: Optional[str] = None,
+        html_file: str | None = None,
     ) -> str:
         """Return a string representation of a report.
 
@@ -728,7 +728,7 @@ def df_to_str(pdf: pd.DataFrame) -> str:
         return report
 
 
-def render(filename: str, *fields: Union[int, float, str]) -> str:
+def render(filename: str, *fields: int | float | str) -> str:
     """Render out an individual template.
 
     This basically just reads in a

datacompy/fugue.py

@@ -17,7 +17,7 @@
 
 import pickle
 from collections import defaultdict
-from typing import Any, Callable, Dict, Iterable, List, Optional, Tuple, Union, cast
+from typing import Any, Callable, Dict, Iterable, List, Tuple, cast
 
 import pandas as pd
 from ordered_set import OrderedSet
@@ -105,15 +105,15 @@ def all_columns_match(df1: "AnyDataFrame", df2: "AnyDataFrame") -> bool:
 def is_match(
     df1: "AnyDataFrame",
     df2: "AnyDataFrame",
-    join_columns: Union[str, List[str]],
+    join_columns: str | List[str],
     abs_tol: float = 0,
     rel_tol: float = 0,
     df1_name: str = "df1",
     df2_name: str = "df2",
     ignore_spaces: bool = False,
     ignore_case: bool = False,
     cast_column_names_lower: bool = True,
-    parallelism: Optional[int] = None,
+    parallelism: int | None = None,
     strict_schema: bool = False,
 ) -> bool:
     """Check whether two dataframes match.
@@ -204,15 +204,15 @@ def is_match(
 def all_rows_overlap(
     df1: "AnyDataFrame",
     df2: "AnyDataFrame",
-    join_columns: Union[str, List[str]],
+    join_columns: str | List[str],
     abs_tol: float = 0,
     rel_tol: float = 0,
     df1_name: str = "df1",
     df2_name: str = "df2",
     ignore_spaces: bool = False,
     ignore_case: bool = False,
     cast_column_names_lower: bool = True,
-    parallelism: Optional[int] = None,
+    parallelism: int | None = None,
     strict_schema: bool = False,
 ) -> bool:
     """Check if the rows are all present in both dataframes.
@@ -300,15 +300,15 @@ def all_rows_overlap(
 def count_matching_rows(
     df1: "AnyDataFrame",
     df2: "AnyDataFrame",
-    join_columns: Union[str, List[str]],
+    join_columns: str | List[str],
     abs_tol: float = 0,
     rel_tol: float = 0,
     df1_name: str = "df1",
     df2_name: str = "df2",
     ignore_spaces: bool = False,
     ignore_case: bool = False,
     cast_column_names_lower: bool = True,
-    parallelism: Optional[int] = None,
+    parallelism: int | None = None,
     strict_schema: bool = False,
 ) -> int:
     """Count the number of rows match (on overlapping fields).
@@ -395,7 +395,7 @@ def count_matching_rows(
 def report(
     df1: "AnyDataFrame",
     df2: "AnyDataFrame",
-    join_columns: Union[str, List[str]],
+    join_columns: str | List[str],
     abs_tol: float = 0,
     rel_tol: float = 0,
     df1_name: str = "df1",
@@ -405,8 +405,8 @@ def report(
     cast_column_names_lower: bool = True,
     sample_count: int = 10,
     column_count: int = 10,
-    html_file: Optional[str] = None,
-    parallelism: Optional[int] = None,
+    html_file: str | None = None,
+    parallelism: int | None = None,
 ) -> str:
     """Return a string representation of a report.
 
@@ -648,7 +648,7 @@ def _any(col: str) -> int:
 def _distributed_compare(
     df1: "AnyDataFrame",
     df2: "AnyDataFrame",
-    join_columns: Union[str, List[str]],
+    join_columns: str | List[str],
     return_obj_func: Callable[[Compare], Any],
     abs_tol: float = 0,
     rel_tol: float = 0,
@@ -657,7 +657,7 @@ def _distributed_compare(
     ignore_spaces: bool = False,
     ignore_case: bool = False,
     cast_column_names_lower: bool = True,
-    parallelism: Optional[int] = None,
+    parallelism: int | None = None,
     strict_schema: bool = False,
 ) -> List[Any]:
     """Compare the data distributively using the core Compare class.

datacompy/polars.py

@@ -23,7 +23,7 @@
 
 import os
 from copy import deepcopy
-from typing import Any, Dict, List, Optional, Union, cast
+from typing import Any, Dict, List, cast
 
 import numpy as np
 import polars as pl
@@ -85,7 +85,7 @@ def __init__(
         self,
         df1: "pl.DataFrame",
         df2: "pl.DataFrame",
-        join_columns: Union[List[str], str],
+        join_columns: List[str] | str,
         abs_tol: float = 0,
         rel_tol: float = 0,
         df1_name: str = "df1",
@@ -327,8 +327,8 @@ def _intersect_compare(self, ignore_spaces: bool, ignore_case: bool) -> None:
         creates a column column_match which is True for matches, False
         otherwise.
         """
-        match_cnt: Union[int, float]
-        null_diff: Union[int, float]
+        match_cnt: int | float
+        null_diff: int | float
 
         LOG.debug("Comparing intersection")
         row_cnt = len(self.intersect_rows)
@@ -571,7 +571,7 @@ def report(
         self,
         sample_count: int = 10,
         column_count: int = 10,
-        html_file: Optional[str] = None,
+        html_file: str | None = None,
     ) -> str:
         """Return a string representation of a report.
 
@@ -734,7 +734,7 @@ def df_to_str(pdf: "pl.DataFrame") -> str:
         return report
 
 
-def render(filename: str, *fields: Union[int, float, str]) -> str:
+def render(filename: str, *fields: int | float | str) -> str:
     """Render out an individual template.
 
     This basically just reads in a

datacompy/snowflake.py

@@ -24,7 +24,7 @@
 import os
 from concurrent.futures import ThreadPoolExecutor, as_completed
 from copy import deepcopy
-from typing import Any, Dict, List, Optional, Union, cast
+from typing import Any, Dict, List, Union, cast
 
 import pandas as pd
 from ordered_set import OrderedSet
@@ -115,11 +115,11 @@ def __init__(
         session: "sp.Session",
         df1: Union[str, "sp.DataFrame"],
         df2: Union[str, "sp.DataFrame"],
-        join_columns: Optional[Union[List[str], str]],
+        join_columns: List[str] | str | None,
         abs_tol: float = 0,
         rel_tol: float = 0,
-        df1_name: Optional[str] = None,
-        df2_name: Optional[str] = None,
+        df1_name: str | None = None,
+        df2_name: str | None = None,
         ignore_spaces: bool = False,
     ) -> None:
         if join_columns is None:
@@ -128,7 +128,7 @@ def __init__(
         elif not join_columns:
             errmsg = "join_columns is empty"
             raise ValueError(errmsg)
-        elif isinstance(join_columns, (str, int, float)):
+        elif isinstance(join_columns, str | int | float):
             self.join_columns = [str(join_columns).replace('"', "").upper()]
         else:
             self.join_columns = [
@@ -155,7 +155,7 @@ def df1(self) -> "sp.DataFrame":
         return self._df1
 
     @df1.setter
-    def df1(self, df1: tuple[Union[str, "sp.DataFrame"], Optional[str]]) -> None:
+    def df1(self, df1: tuple[Union[str, "sp.DataFrame"], str | None]) -> None:
         """Check that df1 is either a Snowpark DF or the name of a valid Snowflake table."""
         (df, df_name) = df1
         if isinstance(df, str):
@@ -176,7 +176,7 @@ def df2(self) -> "sp.DataFrame":
         return self._df2
 
     @df2.setter
-    def df2(self, df2: tuple[Union[str, "sp.DataFrame"], Optional[str]]) -> None:
+    def df2(self, df2: tuple[Union[str, "sp.DataFrame"], str | None]) -> None:
         """Check that df2 is either a Snowpark DF or the name of a valid Snowflake table."""
         (df, df_name) = df2
         if isinstance(df, str):
@@ -215,6 +215,7 @@ def _validate_dataframe(self, df_name: str, index: str) -> None:
                 zip(
                     self._df1.columns,
                     [str(c).replace('"', "").upper() for c in self._df1.columns],
+                    strict=False,
                 )
             )
             self._df1 = self._df1.rename(col_map)
@@ -223,6 +224,7 @@ def _validate_dataframe(self, df_name: str, index: str) -> None:
                 zip(
                     self._df2.columns,
                     [str(c).replace('"', "").upper() for c in self._df2.columns],
+                    strict=False,
                 )
             )
             self._df2 = self._df2.rename(dict(col_map))
@@ -711,7 +713,7 @@ def report(
         self,
         sample_count: int = 10,
         column_count: int = 10,
-        html_file: Optional[str] = None,
+        html_file: str | None = None,
     ) -> str:
         """Return a string representation of a report.
 
@@ -876,7 +878,7 @@ def report(
         return report
 
 
-def render(filename: str, *fields: Union[int, float, str]) -> str:
+def render(filename: str, *fields: int | float | str) -> str:
     """Render out an individual template.
 
     This basically just reads in a

datacompy/spark/legacy.py

@@ -17,7 +17,7 @@
 import sys
 from enum import Enum
 from itertools import chain
-from typing import Any, Dict, List, Optional, Set, TextIO, Tuple, Union
+from typing import Any, Dict, List, Optional, Set, TextIO, Tuple
 from warnings import warn
 
 try:
@@ -160,10 +160,10 @@ def __init__(
         spark_session: "pyspark.sql.SparkSession",
         base_df: "pyspark.sql.DataFrame",
         compare_df: "pyspark.sql.DataFrame",
-        join_columns: List[Union[str, Tuple[str, str]]],
-        column_mapping: Optional[List[Tuple[str, str]]] = None,
+        join_columns: List[str | Tuple[str, str]],
+        column_mapping: List[Tuple[str, str]] | None = None,
         cache_intermediates: bool = False,
-        known_differences: Optional[List[Dict[str, Any]]] = None,
+        known_differences: List[Dict[str, Any]] | None = None,
         rel_tol: float = 0,
         abs_tol: float = 0,
         show_all_columns: bool = False,
@@ -198,14 +198,14 @@ def __init__(
 
         self.spark = spark_session
         self.base_unq_rows = self.compare_unq_rows = None
-        self._base_row_count: Optional[int] = None
-        self._compare_row_count: Optional[int] = None
-        self._common_row_count: Optional[int] = None
-        self._joined_dataframe: Optional[pyspark.sql.DataFrame] = None
-        self._rows_only_base: Optional[pyspark.sql.DataFrame] = None
-        self._rows_only_compare: Optional[pyspark.sql.DataFrame] = None
-        self._all_matched_rows: Optional[pyspark.sql.DataFrame] = None
-        self._all_rows_mismatched: Optional[pyspark.sql.DataFrame] = None
+        self._base_row_count: int | None = None
+        self._compare_row_count: int | None = None
+        self._common_row_count: int | None = None
+        self._joined_dataframe: pyspark.sql.DataFrame | None = None
+        self._rows_only_base: pyspark.sql.DataFrame | None = None
+        self._rows_only_compare: pyspark.sql.DataFrame | None = None
+        self._all_matched_rows: pyspark.sql.DataFrame | None = None
+        self._all_rows_mismatched: pyspark.sql.DataFrame | None = None
         self.columns_match_dict: Dict[str, Any] = {}
 
         # drop the duplicates before actual comparison made.
@@ -219,7 +219,7 @@ def __init__(
             self._compare_row_count = self.compare_df.count()
 
     def _tuplizer(
-        self, input_list: List[Union[str, Tuple[str, str]]]
+        self, input_list: List[str | Tuple[str, str]]
     ) -> List[Tuple[str, str]]:
         join_columns: List[Tuple[str, str]] = []
         for val in input_list: