def test_to_csv_compression(self, df, encoding, compression):
with tm.ensure_clean() as filename:
df.to_csv(filename, compression=compression, encoding=encoding)
# test the round trip - to_csv -> read_csv
result = read_csv(
filename, compression=compression, index_col=0, encoding=encoding
)
tm.assert_frame_equal(df, result)
# test the round trip using file handle - to_csv -> read_csv
handles = get_handle(
filename, "w", compression=compression, encoding=encoding
)
df.to_csv(handles.handle, encoding=encoding)
assert not handles.handle.closed
handles.close()
result = pd.read_csv(
filename,
compression=compression,
encoding=encoding,
index_col=0,
squeeze=True,
)
tm.assert_frame_equal(df, result)
# explicitly make sure file is compressed
with tm.decompress_file(filename, compression) as fh:
text = fh.read().decode(encoding or "utf8")
for col in df.columns:
assert col in text
with tm.decompress_file(filename, compression) as fh:
tm.assert_frame_equal(df, read_csv(fh, index_col=0, encoding=encoding))
def test_write_infer(self, ext, get_random_path):
base = get_random_path
path1 = base + ext
path2 = base + ".raw"
compression = None
for c in self._compression_to_extension:
if self._compression_to_extension[c] == ext:
compression = c
break
with tm.ensure_clean(path1) as p1, tm.ensure_clean(path2) as p2:
df = tm.makeDataFrame()
# write to compressed file by inferred compression method
df.to_pickle(p1)
# decompress
with tm.decompress_file(p1, compression=compression) as f:
with open(p2, "wb") as fh:
fh.write(f.read())
# read decompressed file
df2 = pd.read_pickle(p2, compression=None)
tm.assert_frame_equal(df, df2)
def test_to_csv_compression(self, s, encoding, compression):
with tm.ensure_clean() as filename:
s.to_csv(filename,
compression=compression,
encoding=encoding,
header=True)
# test the round trip - to_csv -> read_csv
result = pd.read_csv(
filename,
compression=compression,
encoding=encoding,
index_col=0,
squeeze=True,
)
tm.assert_series_equal(s, result)
# test the round trip using file handle - to_csv -> read_csv
f, _handles = get_handle(filename,
"w",
compression=compression,
encoding=encoding)
with f:
s.to_csv(f, encoding=encoding, header=True)
result = pd.read_csv(
filename,
compression=compression,
encoding=encoding,
index_col=0,
squeeze=True,
)
tm.assert_series_equal(s, result)
# explicitly ensure file was compressed
with tm.decompress_file(filename, compression) as fh:
text = fh.read().decode(encoding or "utf8")
assert s.name in text
with tm.decompress_file(filename, compression) as fh:
tm.assert_series_equal(
s,
pd.read_csv(fh,
index_col=0,
squeeze=True,
encoding=encoding))
def test_gz_lineend(self):
# GH 25311
df = DataFrame({"a": [1, 2]})
expected_rows = ["a", "1", "2"]
expected = tm.convert_rows_list_to_csv_str(expected_rows)
with tm.ensure_clean("__test_gz_lineend.csv.gz") as path:
df.to_csv(path, index=False)
with tm.decompress_file(path, compression="gzip") as f:
result = f.read().decode("utf-8")
assert result == expected
def test_compression_roundtrip(compression):
df = pd.DataFrame(
[[0.123456, 0.234567, 0.567567], [12.32112, 123123.2, 321321.2]],
index=["A", "B"],
columns=["X", "Y", "Z"],
)
with tm.ensure_clean() as path:
df.to_json(path, compression=compression)
tm.assert_frame_equal(df, pd.read_json(path, compression=compression))
# explicitly ensure file was compressed.
with tm.decompress_file(path, compression) as fh:
result = fh.read().decode("utf8")
tm.assert_frame_equal(df, pd.read_json(result))
def test_write_explicit(self, compression, get_random_path):
base = get_random_path
path1 = base + ".compressed"
path2 = base + ".raw"
with tm.ensure_clean(path1) as p1, tm.ensure_clean(path2) as p2:
df = tm.makeDataFrame()
# write to compressed file
df.to_pickle(p1, compression=compression)
# decompress
with tm.decompress_file(p1, compression=compression) as f:
with open(p2, "wb") as fh:
fh.write(f.read())
# read decompressed file
df2 = pd.read_pickle(p2, compression=None)
tm.assert_frame_equal(df, df2)
