def test_read_csv_glob_4373(self):
columns, filename = ["col0"], "1x1.csv"
pd.DataFrame([[1]], columns=columns).to_csv(filename)
kwargs = {"filepath_or_buffer": filename, "usecols": columns}
modin_df = pd.read_csv_glob(**kwargs)
pandas_df = pandas.read_csv(**kwargs)
df_equals(modin_df, pandas_df)
def test_distributed_pickling(filename, compression):
data = test_data["int_data"]
df = pd.DataFrame(data)
if compression:
filename = f"{filename}.gz"
df.to_pickle_distributed(filename, compression=compression)
pickled_df = pd.read_pickle_distributed(filename, compression=compression)
df_equals(pickled_df, df)
pickle_files = glob.glob(filename)
teardown_test_files(pickle_files)
def test_distributed_pickling(filename, compression):
data = test_data["int_data"]
df = pd.DataFrame(data)
filename_param = filename
if compression:
filename = f"{filename}.gz"
with (warns_that_defaulting_to_pandas() if filename_param
== test_default_to_pickle_filename else nullcontext()):
df.to_pickle_distributed(filename, compression=compression)
pickled_df = pd.read_pickle_distributed(filename,
compression=compression)
df_equals(pickled_df, df)
pickle_files = glob.glob(filename)
teardown_test_files(pickle_files)