>=3.7

.github/workflows/python-package.yml

@@ -16,7 +16,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.6.15", "3.7.17", "3.8.18", "3.9", "3.10", "3.11"]
+        python-version: ["3.7", "3.8", "3.9", "3.10", "3.11"]
 
     steps:
     - uses: actions/checkout@v3

osos/_implementations.py

@@ -2,7 +2,7 @@
 import numpy as np
 from pandas.core.groupby.generic import SeriesGroupBy
 from pandas.core.window.rolling import Rolling as RollingWindow
-from typing import Union, Callable, Iterable, Any, overload, Optional
+from typing import Union, Callable, Iterable, Any, overload, Optional,List,Tuple
 from warnings import warn
 
 from .window import EmptyWindow, ConcreteWindowSpec
@@ -568,7 +568,7 @@ def nanvl_func(col1: pd.Series, col2: pd.Series):
 
 def percentile_approx_func(
     col: pd.Series,
-    percentage: Union[pd.Series, float, list[float], tuple[float]],
+    percentage: Union[pd.Series, float, List[float], tuple[float]],
     accuracy: Union[pd.Series, float] = 10000,
 ):
 
@@ -677,7 +677,7 @@ def struct_func(*cols: pd.Series):
 
 @overload
 def struct_func(
-    __cols: Union[list[pd.Series], tuple[pd.Series, ...]]
+    __cols: Union[List[pd.Series], Tuple[pd.Series, ...]]
 ):
     ...
 
@@ -686,7 +686,7 @@ def struct_func(
 def struct_func(
     *cols: Union[
         pd.Series,
-        Union[list[pd.Series], tuple[pd.Series, ...]],
+        Union[List[pd.Series], tuple[pd.Series, ...]],
     ]
 ):
 

osos/column.py

@@ -1,5 +1,5 @@
 from numbers import Number
-from typing import Union, Iterable, TYPE_CHECKING
+from typing import Union, Iterable, TYPE_CHECKING,List
 import operator
 from copy import deepcopy
 import numpy as np
@@ -95,7 +95,7 @@ def alias(self, newname):
 
 
 class ColumnList(Node):
-    def __init__(self, args: list["AbstractColOrLit"]):
+    def __init__(self, args: List["AbstractColOrLit"]):
         def extract_columns(*args):
             return list(args)
 

osos/dataframe.py

@@ -11,7 +11,7 @@
 
 from copy import deepcopy, copy
 import numpy as np
-from typing import Iterable, Union, Optional,cast
+from typing import Iterable, Union, Optional,cast,List
 import pandas as pd
 
 
@@ -200,7 +200,7 @@ def union(self, other: "DataFrame") -> "DataFrame":
     def unionAll(self, other: "DataFrame") -> "DataFrame":
         return self.union(other).dropDuplicates()
 
-    def dropDuplicates(self, subset: Optional[list[str]] = None) -> "DataFrame":
+    def dropDuplicates(self, subset: Optional[List[str]] = None) -> "DataFrame":
         return DataFrame(
             self._data.drop_duplicates(subset, ignore_index=True).reindex()
         )
@@ -211,7 +211,7 @@ def unionByName(self, other: "DataFrame") -> "DataFrame":
         othersort = other._data.sort_index(axis=1)
         return DataFrame(pd.concat([selfsort, othersort]))
 
-    def join(self, other: "DataFrame", by: Union[str, list], how: str):
+    def join(self, other: "DataFrame", by: Union[str, List], how: str):
         by = [by] if isinstance(by, str) else by
 
         assert how in (

osos/functions.py

@@ -15,7 +15,7 @@
 from .dataframe import DataFrame
 
 
-from typing import Any, Optional, Union, List, Tuple, overload, Callable
+from typing import Any, Optional, Union, List, Tuple, overload, Callable,Tuple
 from warnings import warn
 
 # all the public names in _implementations end in "_func"

osos/indexer.py

@@ -1,7 +1,7 @@
 from pandas.api.indexers import BaseIndexer
 import pandas as pd
 import numpy as np
-from typing import Union
+from typing import Union,Tuple
 
 
 from .window import currentRow, unboundedFollowing, unboundedPreceding
@@ -29,7 +29,7 @@ def get_window_bounds(
         min_periods: Union[int, None] = None,
         center: Union[bool, None] = None,
         closed: Union[str, None] = None,
-    ) -> tuple[np.ndarray, np.ndarray]:
+    ) -> Tuple[np.ndarray, np.ndarray]:
 
         # case 1: partitioned by column(s), no range/row spec
         # the partitioning is already done by the groupby,

osos/types.py

@@ -2,6 +2,8 @@
 import pandas as pd
 from decimal import Decimal
 
+from typing import List,Tuple
+
 # integral
 IntegerType = lambda: np.int32
 FloatType = lambda: np.float32
@@ -32,10 +34,10 @@
 DayTimeIntervalType = lambda *args: pd.Timedelta
 
 # complex
-ArrayType = lambda elementType, containsNull=False: list
+ArrayType = lambda elementType, containsNull=False: List
 MapType = lambda keyType, elementType, valueContainsNull=False: dict
 StructType = lambda fields: np.array
-StructField = lambda name,dataType,nullable=False: tuple
+StructField = lambda name,dataType,nullable=False: Tuple
 
 
 

osos/utils.py

@@ -1,5 +1,5 @@
 import itertools
-from typing import Iterable, Union,cast
+from typing import Iterable, Union,cast,List
 import pandas as pd
 from pandas.core.groupby.generic import SeriesGroupBy
 
@@ -39,7 +39,7 @@ def flatten_and_process(cols: Iterable[Union[str,Node]]) -> Iterable[Node]:
         if isinstance(col, str):
             flat_cols[i] = AbstractCol(col)
 
-    return cast(list[Node],flat_cols)
+    return cast(List[Node],flat_cols)
 
 
 def rename_series(series: pd.Series, newname: str, _over=None) -> pd.Series:

osos/window.py

@@ -1,6 +1,6 @@
 from .exceptions import AnalysisException
 from .utils import flatten_cols
-from typing import Union
+from typing import Union,List
 
 from .column import Node, AbstractCol, SimpleContainer, ColumnList, ForwardRef
 
@@ -160,8 +160,8 @@ def __init__(
         rows_between=None,
         range_between=None,
     ) -> None:
-        self.partition_by: list["ColumnType"] = partition_by
-        self.order_by: list["ColumnType"] = order_by
+        self.partition_by: List["ColumnType"] = partition_by
+        self.order_by: List["ColumnType"] = order_by
         self.rows_between: "SimpleContainer" = rows_between
         self.range_between: "SimpleContainer" = range_between
 

requirements.txt

@@ -1,3 +1,3 @@
 numpy>=1.2
-pandas>=1.5.0
-sqlglot>=10.0.0
+pandas>=1.0.0
+sqlglot

setup.py

@@ -1,3 +1,6 @@
 from setuptools import setup, find_packages
 
-setup(packages=find_packages())
+setup(
+    packages=find_packages(),
+    python_requires=">=3.7"
+)