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TST: Replace ensure_clean_store with tmp_path in tests/io/pytables/te… #63106

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TST: Replace ensure_clean_store with tmp_path in tests/io/pytables/te…
jeffreykenneth Nov 13, 2025
6128d91
Merge branch 'pandas-dev:main' into test/ensure-clean-append
jeffreykenneth Nov 17, 2025
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118 changes: 70 additions & 48 deletions pandas/tests/io/pytables/test_append.py
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Original file line number Diff line number Diff line change
Expand Up @@ -11,6 +11,7 @@
import pandas as pd
from pandas import (
DataFrame,
HDFStore,
Index,
Series,
_testing as tm,
Expand All @@ -20,7 +21,6 @@
)
from pandas.tests.io.pytables.common import (
_maybe_remove,
ensure_clean_store,
)

pytestmark = [pytest.mark.single_cpu]
Expand All @@ -29,8 +29,9 @@


@pytest.mark.filterwarnings("ignore::tables.NaturalNameWarning")
def test_append(setup_path):
with ensure_clean_store(setup_path) as store:
def test_append(tmp_path):
path = tmp_path / "test_append.h5"
with HDFStore(path) as store:
# this is allowed by almost always don't want to do it
# tables.NaturalNameWarning):
df = DataFrame(
Expand Down Expand Up @@ -101,8 +102,9 @@ def test_append(setup_path):
tm.assert_frame_equal(store["uints"], uint_data, check_index_type=True)


def test_append_series(setup_path):
with ensure_clean_store(setup_path) as store:
def test_append_series(tmp_path):
path = tmp_path / "test_append_series.h5"
with HDFStore(path) as store:
# basic
ss = Series(range(20), dtype=np.float64, index=[f"i_{i}" for i in range(20)])
ts = Series(
Expand Down Expand Up @@ -150,8 +152,9 @@ def test_append_series(setup_path):
tm.assert_series_equal(store["mi"], s, check_index_type=True)


def test_append_some_nans(setup_path):
with ensure_clean_store(setup_path) as store:
def test_append_some_nans(tmp_path):
path = tmp_path / "test_append_some_nans.h5"
with HDFStore(path) as store:
df = DataFrame(
{
"A": Series(np.random.default_rng(2).standard_normal(20)).astype(
Expand Down Expand Up @@ -198,8 +201,9 @@ def test_append_some_nans(setup_path):
tm.assert_frame_equal(store["df3"], df3, check_index_type=True)


def test_append_all_nans(setup_path, using_infer_string):
with ensure_clean_store(setup_path) as store:
def test_append_all_nans(tmp_path, using_infer_string):
path = tmp_path / "test_append_all_nans.h5"
with HDFStore(path) as store:
df = DataFrame(
{
"A1": np.random.default_rng(2).standard_normal(20),
Expand Down Expand Up @@ -290,8 +294,9 @@ def test_append_all_nans(setup_path, using_infer_string):
tm.assert_frame_equal(store["df2"], df, check_index_type=True)


def test_append_frame_column_oriented(setup_path, request):
with ensure_clean_store(setup_path) as store:
def test_append_frame_column_oriented(tmp_path, request):
path = tmp_path / "test_append_frame_column_oriented.h5"
with HDFStore(path) as store:
# column oriented
df = DataFrame(
np.random.default_rng(2).standard_normal((10, 4)),
Expand Down Expand Up @@ -330,9 +335,10 @@ def test_append_frame_column_oriented(setup_path, request):
store.select("df1", "columns=A and index>df.index[4]")


def test_append_with_different_block_ordering(setup_path):
def test_append_with_different_block_ordering(tmp_path):
# GH 4096; using same frames, but different block orderings
with ensure_clean_store(setup_path) as store:
path = tmp_path / "test_append_with_different_block_ordering.h5"
with HDFStore(path) as store:
for i in range(10):
df = DataFrame(
np.random.default_rng(2).standard_normal((10, 2)), columns=list("AB")
Expand All @@ -355,14 +361,15 @@ def test_append_with_different_block_ordering(setup_path):

# test a different ordering but with more fields (like invalid
# combinations)
with ensure_clean_store(setup_path) as store:
with HDFStore(path) as store:
df = DataFrame(
np.random.default_rng(2).standard_normal((10, 2)),
columns=list("AB"),
dtype="float64",
)
df["int64"] = Series([1] * len(df), dtype="int64")
df["int16"] = Series([1] * len(df), dtype="int16")
_maybe_remove(store, "df")
store.append("df", df)

# store additional fields in different blocks
Expand All @@ -382,8 +389,9 @@ def test_append_with_different_block_ordering(setup_path):
store.append("df", df)


def test_append_with_strings(setup_path):
with ensure_clean_store(setup_path) as store:
def test_append_with_strings(tmp_path):
path = tmp_path / "test_append_with_strings.h5"
with HDFStore(path) as store:

def check_col(key, name, size):
assert (
Expand Down Expand Up @@ -467,7 +475,7 @@ def check_col(key, name, size):
result = store.select("df")
tm.assert_frame_equal(result, df)

with ensure_clean_store(setup_path) as store:
with HDFStore(path) as store:
df = DataFrame({"A": "foo", "B": "bar"}, index=range(10))

# a min_itemsize that creates a data_column
Expand Down Expand Up @@ -505,17 +513,19 @@ def check_col(key, name, size):
store.append("df", df, min_itemsize={"foo": 20, "foobar": 20})


def test_append_with_empty_string(setup_path):
with ensure_clean_store(setup_path) as store:
def test_append_with_empty_string(tmp_path):
path = tmp_path / "test_append_with_empty_string.h5"
with HDFStore(path) as store:
# with all empty strings (GH 12242)
df = DataFrame({"x": ["a", "b", "c", "d", "e", "f", ""]})
store.append("df", df[:-1], min_itemsize={"x": 1})
store.append("df", df[-1:], min_itemsize={"x": 1})
tm.assert_frame_equal(store.select("df"), df)


def test_append_with_data_columns(setup_path):
with ensure_clean_store(setup_path) as store:
def test_append_with_data_columns(tmp_path):
path = tmp_path / "test_append_with_data_columns.h5"
with HDFStore(path) as store:
df = DataFrame(
np.random.default_rng(2).standard_normal((10, 4)),
columns=Index(list("ABCD")),
Expand Down Expand Up @@ -559,7 +569,7 @@ def check_col(key, name, size):
getattr(store.get_storer(key).table.description, name).itemsize == size
)

with ensure_clean_store(setup_path) as store:
with HDFStore(path) as store:
_maybe_remove(store, "df")
store.append("df", df_new, data_columns=["string"], min_itemsize={"string": 30})
check_col("df", "string", 30)
Expand All @@ -570,7 +580,7 @@ def check_col(key, name, size):
store.append("df", df_new, data_columns=["string"], min_itemsize={"values": 30})
check_col("df", "string", 30)

with ensure_clean_store(setup_path) as store:
with HDFStore(path) as store:
df_new["string2"] = "foobarbah"
df_new["string_block1"] = "foobarbah1"
df_new["string_block2"] = "foobarbah2"
Expand All @@ -585,7 +595,7 @@ def check_col(key, name, size):
check_col("df", "string2", 40)
check_col("df", "values_block_1", 50)

with ensure_clean_store(setup_path) as store:
with HDFStore(path) as store:
# multiple data columns
df_new = df.copy()
df_new.iloc[0, df_new.columns.get_loc("A")] = 1.0
Expand Down Expand Up @@ -617,7 +627,7 @@ def check_col(key, name, size):
expected = df_new[(df_new.string == "foo") & (df_new.string2 == "cool")]
tm.assert_frame_equal(result, expected)

with ensure_clean_store(setup_path) as store:
with HDFStore(path) as store:
# doc example
df_dc = df.copy()
df_dc["string"] = "foo"
Expand All @@ -642,7 +652,7 @@ def check_col(key, name, size):
# FIXME: 2020-12-07 intermittent build failures here with freq of
# None instead of BDay(4)

with ensure_clean_store(setup_path) as store:
with HDFStore(path) as store:
# doc example part 2

index = date_range("1/1/2000", periods=8)
Expand All @@ -658,6 +668,7 @@ def check_col(key, name, size):
df_dc["string2"] = "cool"

# on-disk operations
_maybe_remove(store, "df_dc")
store.append("df_dc", df_dc, data_columns=["B", "C", "string", "string2"])

result = store.select("df_dc", "B>0")
Expand All @@ -669,11 +680,12 @@ def check_col(key, name, size):
tm.assert_frame_equal(result, expected)


def test_append_hierarchical(tmp_path, setup_path, multiindex_dataframe_random_data):
def test_append_hierarchical(tmp_path, multiindex_dataframe_random_data):
df = multiindex_dataframe_random_data
df.columns.name = None

with ensure_clean_store(setup_path) as store:
path = tmp_path / "test_append_hierarchical.h5"
with HDFStore(path) as store:
store.append("mi", df)
result = store.select("mi")
tm.assert_frame_equal(result, df)
Expand All @@ -690,8 +702,9 @@ def test_append_hierarchical(tmp_path, setup_path, multiindex_dataframe_random_d
tm.assert_frame_equal(result, expected)


def test_append_misc(setup_path):
with ensure_clean_store(setup_path) as store:
def test_append_misc(tmp_path):
path = tmp_path / "test_append_misc.h5"
with HDFStore(path) as store:
df = DataFrame(
1.1 * np.arange(120).reshape((30, 4)),
columns=Index(list("ABCD")),
Expand All @@ -707,7 +720,7 @@ def test_append_misc(setup_path):


@pytest.mark.parametrize("chunksize", [10, 200, 1000])
def test_append_misc_chunksize(setup_path, chunksize):
def test_append_misc_chunksize(tmp_path, chunksize):
# more chunksize in append tests
df = DataFrame(
1.1 * np.arange(120).reshape((30, 4)),
Expand All @@ -720,15 +733,17 @@ def test_append_misc_chunksize(setup_path, chunksize):
df["bool"] = df["float322"] > 0
df["time1"] = Timestamp("20130101").as_unit("ns")
df["time2"] = Timestamp("20130102").as_unit("ns")
with ensure_clean_store(setup_path, mode="w") as store:
path = tmp_path / "test_append_misc_chunksize.h5"
with HDFStore(path) as store:
store.append("obj", df, chunksize=chunksize)
result = store.select("obj")
tm.assert_frame_equal(result, df)


def test_append_misc_empty_frame(setup_path):
def test_append_misc_empty_frame(tmp_path):
path = tmp_path / "test_append_misc_empty_frame.h5"
# empty frame, GH4273
with ensure_clean_store(setup_path) as store:
with HDFStore(path) as store:
# 0 len
df_empty = DataFrame(columns=list("ABC"))
store.append("df", df_empty)
Expand All @@ -748,8 +763,9 @@ def test_append_misc_empty_frame(setup_path):
tm.assert_frame_equal(store.select("df2"), df)


def test_append_raise(setup_path, using_infer_string):
with ensure_clean_store(setup_path) as store:
def test_append_raise(tmp_path, using_infer_string):
path = tmp_path / "test_append_raise.h5"
with HDFStore(path) as store:
# test append with invalid input to get good error messages

# list in column
Expand Down Expand Up @@ -832,7 +848,7 @@ def test_append_raise(setup_path, using_infer_string):
store.append("df", df)


def test_append_with_timedelta(setup_path):
def test_append_with_timedelta(tmp_path):
# GH 3577
# append timedelta

Expand All @@ -846,7 +862,8 @@ def test_append_with_timedelta(setup_path):
df["C"] = df["A"] - df["B"]
df.loc[3:5, "C"] = np.nan

with ensure_clean_store(setup_path) as store:
path = tmp_path / "test_append_with_timedelta.h5"
with HDFStore(path) as store:
# table
_maybe_remove(store, "df")
store.append("df", df, data_columns=True)
Expand Down Expand Up @@ -879,7 +896,7 @@ def test_append_with_timedelta(setup_path):
tm.assert_frame_equal(result, df)


def test_append_to_multiple(setup_path):
def test_append_to_multiple(tmp_path):
df1 = DataFrame(
np.random.default_rng(2).standard_normal((10, 4)),
columns=Index(list("ABCD")),
Expand All @@ -889,7 +906,8 @@ def test_append_to_multiple(setup_path):
df2["foo"] = "bar"
df = concat([df1, df2], axis=1)

with ensure_clean_store(setup_path) as store:
path = tmp_path / "test_append_to_multiple.h5"
with HDFStore(path) as store:
# exceptions
msg = "append_to_multiple requires a selector that is in passed dict"
with pytest.raises(ValueError, match=msg):
Expand All @@ -916,7 +934,7 @@ def test_append_to_multiple(setup_path):
tm.assert_frame_equal(result, expected)


def test_append_to_multiple_dropna(setup_path):
def test_append_to_multiple_dropna(tmp_path):
df1 = DataFrame(
np.random.default_rng(2).standard_normal((10, 4)),
columns=Index(list("ABCD")),
Expand All @@ -930,7 +948,8 @@ def test_append_to_multiple_dropna(setup_path):
df1.iloc[1, df1.columns.get_indexer(["A", "B"])] = np.nan
df = concat([df1, df2], axis=1)

with ensure_clean_store(setup_path) as store:
path = tmp_path / "test_append_to_multiple_dropna.h5"
with HDFStore(path) as store:
# dropna=True should guarantee rows are synchronized
store.append_to_multiple(
{"df1": ["A", "B"], "df2": None}, df, selector="df1", dropna=True
Expand All @@ -941,7 +960,7 @@ def test_append_to_multiple_dropna(setup_path):
tm.assert_index_equal(store.select("df1").index, store.select("df2").index)


def test_append_to_multiple_dropna_false(setup_path):
def test_append_to_multiple_dropna_false(tmp_path):
df1 = DataFrame(
np.random.default_rng(2).standard_normal((10, 4)),
columns=Index(list("ABCD")),
Expand All @@ -951,8 +970,9 @@ def test_append_to_multiple_dropna_false(setup_path):
df1.iloc[1, df1.columns.get_indexer(["A", "B"])] = np.nan
df = concat([df1, df2], axis=1)

path = tmp_path / "test_append_to_multiple_dropna_false.h5"
with (
ensure_clean_store(setup_path) as store,
HDFStore(path) as store,
pd.option_context("io.hdf.dropna_table", True),
):
# dropna=False shouldn't synchronize row indexes
Expand All @@ -967,7 +987,7 @@ def test_append_to_multiple_dropna_false(setup_path):
assert not store.select("df1a").index.equals(store.select("df2a").index)


def test_append_to_multiple_min_itemsize(setup_path):
def test_append_to_multiple_min_itemsize(tmp_path):
# GH 11238
df = DataFrame(
{
Expand All @@ -982,7 +1002,8 @@ def test_append_to_multiple_min_itemsize(setup_path):
# Reading/writing RangeIndex info is not supported yet
expected.index = Index(list(range(len(expected.index))))

with ensure_clean_store(setup_path) as store:
path = tmp_path / "test_append_to_multiple_min_itemsize.h5"
with HDFStore(path) as store:
store.append_to_multiple(
{
"index": ["IX"],
Expand All @@ -997,14 +1018,15 @@ def test_append_to_multiple_min_itemsize(setup_path):
tm.assert_frame_equal(result, expected, check_index_type=True)


def test_append_string_nan_rep(setup_path):
def test_append_string_nan_rep(tmp_path):
# GH 16300
df = DataFrame({"A": "a", "B": "foo"}, index=np.arange(10))
df_nan = df.copy()
df_nan.loc[0:4, :] = np.nan
msg = "NaN representation is too large for existing column size"

with ensure_clean_store(setup_path) as store:
path = tmp_path / "test_append_string_nan_rep.h5"
with HDFStore(path) as store:
# string column too small
store.append("sa", df["A"])
with pytest.raises(ValueError, match=msg):
Expand Down
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