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287 lines
10 KiB
Python
287 lines
10 KiB
Python
""" test feather-format compat """
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import numpy as np
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import pytest
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from pandas.compat.pyarrow import (
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pa_version_under18p0,
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pa_version_under19p0,
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)
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import pandas as pd
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import pandas._testing as tm
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from pandas.io.feather_format import read_feather, to_feather # isort:skip
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pytestmark = pytest.mark.filterwarnings(
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"ignore:Passing a BlockManager to DataFrame:DeprecationWarning"
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)
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pa = pytest.importorskip("pyarrow")
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@pytest.mark.single_cpu
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class TestFeather:
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def check_error_on_write(self, df, exc, err_msg):
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# check that we are raising the exception
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# on writing
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with pytest.raises(exc, match=err_msg):
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with tm.ensure_clean() as path:
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to_feather(df, path)
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def check_external_error_on_write(self, df):
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# check that we are raising the exception
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# on writing
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with tm.external_error_raised(Exception):
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with tm.ensure_clean() as path:
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to_feather(df, path)
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def check_round_trip(self, df, expected=None, write_kwargs={}, **read_kwargs):
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if expected is None:
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expected = df.copy()
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with tm.ensure_clean() as path:
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to_feather(df, path, **write_kwargs)
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result = read_feather(path, **read_kwargs)
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tm.assert_frame_equal(result, expected)
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def test_error(self):
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msg = "feather only support IO with DataFrames"
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for obj in [
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pd.Series([1, 2, 3]),
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1,
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"foo",
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pd.Timestamp("20130101"),
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np.array([1, 2, 3]),
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]:
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self.check_error_on_write(obj, ValueError, msg)
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def test_basic(self):
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df = pd.DataFrame(
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{
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"string": list("abc"),
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"int": list(range(1, 4)),
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"uint": np.arange(3, 6).astype("u1"),
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"float": np.arange(4.0, 7.0, dtype="float64"),
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"float_with_null": [1.0, np.nan, 3],
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"bool": [True, False, True],
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"bool_with_null": [True, np.nan, False],
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"cat": pd.Categorical(list("abc")),
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"dt": pd.DatetimeIndex(
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list(pd.date_range("20130101", periods=3)), freq=None
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),
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"dttz": pd.DatetimeIndex(
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list(pd.date_range("20130101", periods=3, tz="US/Eastern")),
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freq=None,
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),
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"dt_with_null": [
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pd.Timestamp("20130101"),
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pd.NaT,
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pd.Timestamp("20130103"),
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],
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"dtns": pd.DatetimeIndex(
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list(pd.date_range("20130101", periods=3, freq="ns")), freq=None
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),
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}
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)
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df["periods"] = pd.period_range("2013", freq="M", periods=3)
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df["timedeltas"] = pd.timedelta_range("1 day", periods=3)
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df["intervals"] = pd.interval_range(0, 3, 3)
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assert df.dttz.dtype.tz.zone == "US/Eastern"
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expected = df.copy()
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expected.loc[1, "bool_with_null"] = None
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self.check_round_trip(df, expected=expected)
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def test_duplicate_columns(self):
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# https://github.com/wesm/feather/issues/53
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# not currently able to handle duplicate columns
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df = pd.DataFrame(np.arange(12).reshape(4, 3), columns=list("aaa")).copy()
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self.check_external_error_on_write(df)
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def test_read_columns(self):
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# GH 24025
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df = pd.DataFrame(
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{
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"col1": list("abc"),
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"col2": list(range(1, 4)),
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"col3": list("xyz"),
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"col4": list(range(4, 7)),
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}
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)
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columns = ["col1", "col3"]
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self.check_round_trip(df, expected=df[columns], columns=columns)
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def test_read_columns_different_order(self):
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# GH 33878
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df = pd.DataFrame({"A": [1, 2], "B": ["x", "y"], "C": [True, False]})
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expected = df[["B", "A"]]
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self.check_round_trip(df, expected, columns=["B", "A"])
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def test_unsupported_other(self):
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# mixed python objects
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df = pd.DataFrame({"a": ["a", 1, 2.0]})
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self.check_external_error_on_write(df)
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def test_rw_use_threads(self):
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df = pd.DataFrame({"A": np.arange(100000)})
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self.check_round_trip(df, use_threads=True)
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self.check_round_trip(df, use_threads=False)
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def test_path_pathlib(self):
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df = pd.DataFrame(
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1.1 * np.arange(120).reshape((30, 4)),
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columns=pd.Index(list("ABCD")),
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index=pd.Index([f"i-{i}" for i in range(30)]),
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).reset_index()
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result = tm.round_trip_pathlib(df.to_feather, read_feather)
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tm.assert_frame_equal(df, result)
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def test_path_localpath(self):
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df = pd.DataFrame(
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1.1 * np.arange(120).reshape((30, 4)),
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columns=pd.Index(list("ABCD")),
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index=pd.Index([f"i-{i}" for i in range(30)]),
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).reset_index()
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result = tm.round_trip_localpath(df.to_feather, read_feather)
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tm.assert_frame_equal(df, result)
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def test_passthrough_keywords(self):
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df = pd.DataFrame(
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1.1 * np.arange(120).reshape((30, 4)),
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columns=pd.Index(list("ABCD")),
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index=pd.Index([f"i-{i}" for i in range(30)]),
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).reset_index()
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self.check_round_trip(df, write_kwargs={"version": 1})
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@pytest.mark.network
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@pytest.mark.single_cpu
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def test_http_path(self, feather_file, httpserver):
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# GH 29055
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expected = read_feather(feather_file)
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with open(feather_file, "rb") as f:
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httpserver.serve_content(content=f.read())
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res = read_feather(httpserver.url)
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tm.assert_frame_equal(expected, res)
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def test_read_feather_dtype_backend(
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self, string_storage, dtype_backend, using_infer_string
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):
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# GH#50765
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df = pd.DataFrame(
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{
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"a": pd.Series([1, np.nan, 3], dtype="Int64"),
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"b": pd.Series([1, 2, 3], dtype="Int64"),
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"c": pd.Series([1.5, np.nan, 2.5], dtype="Float64"),
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"d": pd.Series([1.5, 2.0, 2.5], dtype="Float64"),
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"e": [True, False, None],
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"f": [True, False, True],
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"g": ["a", "b", "c"],
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"h": ["a", "b", None],
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}
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)
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with tm.ensure_clean() as path:
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to_feather(df, path)
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with pd.option_context("mode.string_storage", string_storage):
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result = read_feather(path, dtype_backend=dtype_backend)
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if dtype_backend == "pyarrow":
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pa = pytest.importorskip("pyarrow")
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if using_infer_string:
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string_dtype = pd.ArrowDtype(pa.large_string())
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else:
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string_dtype = pd.ArrowDtype(pa.string())
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else:
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string_dtype = pd.StringDtype(string_storage)
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expected = pd.DataFrame(
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{
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"a": pd.Series([1, np.nan, 3], dtype="Int64"),
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"b": pd.Series([1, 2, 3], dtype="Int64"),
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"c": pd.Series([1.5, np.nan, 2.5], dtype="Float64"),
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"d": pd.Series([1.5, 2.0, 2.5], dtype="Float64"),
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"e": pd.Series([True, False, pd.NA], dtype="boolean"),
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"f": pd.Series([True, False, True], dtype="boolean"),
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"g": pd.Series(["a", "b", "c"], dtype=string_dtype),
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"h": pd.Series(["a", "b", None], dtype=string_dtype),
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}
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)
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if dtype_backend == "pyarrow":
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from pandas.arrays import ArrowExtensionArray
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expected = pd.DataFrame(
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{
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col: ArrowExtensionArray(pa.array(expected[col], from_pandas=True))
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for col in expected.columns
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}
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)
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if using_infer_string:
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expected.columns = expected.columns.astype(
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pd.StringDtype(string_storage, na_value=np.nan)
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)
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tm.assert_frame_equal(result, expected)
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def test_int_columns_and_index(self):
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df = pd.DataFrame({"a": [1, 2, 3]}, index=pd.Index([3, 4, 5], name="test"))
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self.check_round_trip(df)
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def test_invalid_dtype_backend(self):
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msg = (
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"dtype_backend numpy is invalid, only 'numpy_nullable' and "
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"'pyarrow' are allowed."
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)
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df = pd.DataFrame({"int": list(range(1, 4))})
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with tm.ensure_clean("tmp.feather") as path:
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df.to_feather(path)
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with pytest.raises(ValueError, match=msg):
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read_feather(path, dtype_backend="numpy")
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def test_string_inference(self, tmp_path, using_infer_string):
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# GH#54431
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path = tmp_path / "test_string_inference.p"
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df = pd.DataFrame(data={"a": ["x", "y"]})
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df.to_feather(path)
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with pd.option_context("future.infer_string", True):
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result = read_feather(path)
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dtype = pd.StringDtype(na_value=np.nan)
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expected = pd.DataFrame(
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data={"a": ["x", "y"]}, dtype=pd.StringDtype(na_value=np.nan)
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)
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expected = pd.DataFrame(
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data={"a": ["x", "y"]},
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dtype=dtype,
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columns=pd.Index(
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["a"],
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dtype=object
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if pa_version_under19p0 and not using_infer_string
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else dtype,
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),
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)
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tm.assert_frame_equal(result, expected)
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@pytest.mark.skipif(pa_version_under18p0, reason="not supported before 18.0")
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def test_string_inference_string_view_type(self, tmp_path):
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# GH#54798
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import pyarrow as pa
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from pyarrow import feather
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path = tmp_path / "string_view.parquet"
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table = pa.table({"a": pa.array([None, "b", "c"], pa.string_view())})
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feather.write_feather(table, path)
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with pd.option_context("future.infer_string", True):
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result = read_feather(path)
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expected = pd.DataFrame(
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data={"a": [None, "b", "c"]}, dtype=pd.StringDtype(na_value=np.nan)
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)
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tm.assert_frame_equal(result, expected)
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