Skip to content

TST:replace ensure_clean with temp_file in test_errors.py #63198

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
mroeschke merged 4 commits into from
Nov 25, 2025
Merged

TST:replace ensure_clean with temp_file in test_errors.py #63198

Changes from all commits
Commits
Show all changes
4 commits
Select commit Hold shift + click to select a range
d090db7
Add tests for groupby dropna=False behavior
AnonToky Nov 2, 2025
877ecd9
Delete tests/groupby directory
AnonToky Nov 2, 2025
9343882
Merge branch 'pandas-dev:main' into tests/groupby-dropna-preserve-nan
AnonToky Nov 25, 2025
32b6ee8
Refactor tests to use HDFStore with tmp_path
AnonToky Nov 25, 2025
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
21 changes: 10 additions & 11 deletions pandas/tests/io/pytables/test_errors.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -14,7 +14,6 @@
date_range,
read_hdf,
)
from pandas.tests.io.pytables.common import ensure_clean_store

from pandas.io.pytables import (
Term,
Expand All @@ -24,14 +23,14 @@
pytestmark = [pytest.mark.single_cpu]


def test_pass_spec_to_storer(setup_path):
def test_pass_spec_to_storer(tmp_path, setup_path):
df = DataFrame(
1.1 * np.arange(120).reshape((30, 4)),
columns=Index(list("ABCD"), dtype=object),
index=Index([f"i-{i}" for i in range(30)], dtype=object),
)

with ensure_clean_store(setup_path) as store:
with HDFStore(tmp_path / setup_path) as store:
store.put("df", df)
msg = (
"cannot pass a column specification when reading a Fixed format "
Expand All @@ -47,19 +46,19 @@ def test_pass_spec_to_storer(setup_path):
store.select("df", where=["columns=A"])


def test_table_index_incompatible_dtypes(setup_path):
def test_table_index_incompatible_dtypes(tmp_path, setup_path):
df1 = DataFrame({"a": [1, 2, 3]})
df2 = DataFrame({"a": [4, 5, 6]}, index=date_range("1/1/2000", periods=3))

with ensure_clean_store(setup_path) as store:
with HDFStore(tmp_path / setup_path) as store:
store.put("frame", df1, format="table")
msg = re.escape("incompatible kind in col [integer - datetime64[ns]]")
with pytest.raises(TypeError, match=msg):
store.put("frame", df2, format="table", append=True)


def test_unimplemented_dtypes_table_columns(setup_path):
with ensure_clean_store(setup_path) as store:
def test_unimplemented_dtypes_table_columns(tmp_path, setup_path):
with HDFStore(tmp_path / setup_path) as store:
dtypes = [("date", datetime.date(2001, 1, 2))]

# currently not supported dtypes ####
Expand All @@ -85,7 +84,7 @@ def test_unimplemented_dtypes_table_columns(setup_path):
df["datetime1"] = datetime.date(2001, 1, 2)
df = df._consolidate()

with ensure_clean_store(setup_path) as store:
with HDFStore(tmp_path / setup_path) as store:
# this fails because we have a date in the object block......
msg = "|".join(
[
Expand All @@ -101,7 +100,7 @@ def test_unimplemented_dtypes_table_columns(setup_path):


def test_invalid_terms(tmp_path, setup_path):
with ensure_clean_store(setup_path) as store:
with HDFStore(tmp_path / setup_path) as store:
df = DataFrame(
np.random.default_rng(2).standard_normal((10, 4)),
columns=Index(list("ABCD"), dtype=object),
Expand Down Expand Up @@ -162,14 +161,14 @@ def test_invalid_terms(tmp_path, setup_path):
read_hdf(path, "dfq", where="A>0 or C>0")


def test_append_with_diff_col_name_types_raises_value_error(setup_path):
def test_append_with_diff_col_name_types_raises_value_error(tmp_path, setup_path):
df = DataFrame(np.random.default_rng(2).standard_normal((10, 1)))
df2 = DataFrame({"a": np.random.default_rng(2).standard_normal(10)})
df3 = DataFrame({(1, 2): np.random.default_rng(2).standard_normal(10)})
df4 = DataFrame({("1", 2): np.random.default_rng(2).standard_normal(10)})
df5 = DataFrame({("1", 2, object): np.random.default_rng(2).standard_normal(10)})

with ensure_clean_store(setup_path) as store:
with HDFStore(tmp_path / setup_path) as store:
name = "df_diff_valerror"
store.append(name, df)

Expand Down
Loading