fix: compatibility with old numpy versions (#364)

.github/workflows/extremes.yml

@@ -29,7 +29,7 @@ jobs:
       - name: install-reqs
         run: python -m pip install --upgrade tox virtualenv setuptools pip -r requirements-dev.txt
       - name: install-modin
-        run: python -m pip install pandas==1.1.5 polars==0.20.3 "numpy<=1.21" "pyarrow==11.0.0" tzdata
+        run: python -m pip install pandas==1.1.5 polars==0.20.3 numpy==1.17.5 pyarrow==11.0.0 scipy==1.5.0 scikit-learn==1.1.0 tzdata
       - name: Run pytest
         run: pytest tests --cov=narwhals --cov=tests --cov-fail-under=50 --runslow
       - name: Run doctests

narwhals/_pandas_like/utils.py

@@ -382,31 +382,48 @@ def translate_dtype(column: Any) -> DType:
     from narwhals import dtypes
 
     dtype = column.dtype
-    if dtype in ("int64", "Int64", "Int64[pyarrow]"):
+    if str(dtype) in ("int64", "Int64", "Int64[pyarrow]", "int64[pyarrow]"):
         return dtypes.Int64()
-    if dtype in ("int32", "Int32", "Int32[pyarrow]"):
+    if str(dtype) in ("int32", "Int32", "Int32[pyarrow]", "int32[pyarrow]"):
         return dtypes.Int32()
-    if dtype in ("int16", "Int16", "Int16[pyarrow]"):
+    if str(dtype) in ("int16", "Int16", "Int16[pyarrow]", "int16[pyarrow]"):
         return dtypes.Int16()
-    if dtype in ("int8", "Int8", "Int8[pyarrow]"):
+    if str(dtype) in ("int8", "Int8", "Int8[pyarrow]", "int8[pyarrow]"):
         return dtypes.Int8()
-    if dtype in ("uint64", "UInt64", "UInt64[pyarrow]"):
+    if str(dtype) in ("uint64", "UInt64", "UInt64[pyarrow]", "uint64[pyarrow]"):
         return dtypes.UInt64()
-    if dtype in ("uint32", "UInt32", "UInt32[pyarrow]"):
+    if str(dtype) in ("uint32", "UInt32", "UInt32[pyarrow]", "uint32[pyarrow]"):
         return dtypes.UInt32()
-    if dtype in ("uint16", "UInt16", "UInt16[pyarrow]"):
+    if str(dtype) in ("uint16", "UInt16", "UInt16[pyarrow]", "uint16[pyarrow]"):
         return dtypes.UInt16()
-    if dtype in ("uint8", "UInt8", "UInt8[pyarrow]"):
+    if str(dtype) in ("uint8", "UInt8", "UInt8[pyarrow]", "uint8[pyarrow]"):
         return dtypes.UInt8()
-    if dtype in ("float64", "Float64", "Float64[pyarrow]"):
+    if str(dtype) in (
+        "float64",
+        "Float64",
+        "Float64[pyarrow]",
+        "float64[pyarrow]",
+        "double[pyarrow]",
+    ):
         return dtypes.Float64()
-    if dtype in ("float32", "Float32", "Float32[pyarrow]"):
+    if str(dtype) in (
+        "float32",
+        "Float32",
+        "Float32[pyarrow]",
+        "float32[pyarrow]",
+        "float[pyarrow]",
+    ):
         return dtypes.Float32()
-    if dtype in ("string", "string[python]", "string[pyarrow]", "large_string[pyarrow]"):
+    if str(dtype) in (
+        "string",
+        "string[python]",
+        "string[pyarrow]",
+        "large_string[pyarrow]",
+    ):
         return dtypes.String()
-    if dtype in ("bool", "boolean", "boolean[pyarrow]"):
+    if str(dtype) in ("bool", "boolean", "boolean[pyarrow]", "bool[pyarrow]"):
         return dtypes.Boolean()
-    if dtype in ("category",) or str(dtype).startswith("dictionary<"):
+    if str(dtype) in ("category",) or str(dtype).startswith("dictionary<"):
         return dtypes.Categorical()
     if str(dtype).startswith("datetime64"):
         # todo: different time units and time zones
@@ -420,7 +437,7 @@ def translate_dtype(column: Any) -> DType:
         return dtypes.Datetime()
     if str(dtype) == "date32[day][pyarrow]":
         return dtypes.Date()
-    if dtype == "object":
+    if str(dtype) == "object":
         if (idx := column.first_valid_index()) is not None and isinstance(
             column.loc[idx], str
         ):

tests/series/test_common.py

@@ -463,7 +463,7 @@ def test_cast_string() -> None:
     s = nw.from_native(s_pd, series_only=True)
     s = s.cast(nw.String)
     result = nw.to_native(s)
-    assert result.dtype in ("string", object)
+    assert str(result.dtype) in ("string", "object", "dtype('O')")
 
 
 df_pandas = pd.DataFrame({"a": [1, 3, 2], "b": [4, 4, 6], "z": [7.0, 8, 9]})