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