def test_good_parquet_file():
path = TEST_DATA_DIR / "good_parquet.ascii"
df = ASCIIDecoder(path=path).dataframe
with NamedTemporaryFile() as f:
w = ParquetPointDataTableWriter(f.name)
w.add_metadata("header", "foo")
w.add_metadata("footer", "bar")
w.append(df.copy())
w.close()
r = ParquetPointDataTableReader(f.name)
metadata = r.metadata
df_pq = r.dataframe
assert metadata == {"header": "foo", "footer": "bar"}
assert df.memory_usage(deep=True).sum() > df_pq.memory_usage(
deep=True).sum()
assert_frame_equal(df_pq, df, check_dtype=False, check_categorical=False)
def test_good_parquet_file_clone(tmp_path):
path = TEST_DATA_DIR / "good_parquet.ascii"
df = ASCIIDecoder(path=path).dataframe
with NamedTemporaryFile() as f:
w = ParquetPointDataTableWriter(f.name)
w.add_columns_chunk(df.copy())
w.close()
r = ParquetPointDataTableReader(f.name)
exclude_cols = ["tp_acc", "cape_wa"]
cloned_path = tmp_path / "good_parquet.parquet"
cols = [col for col in r.columns if col not in exclude_cols]
r.clone(*cols, path=cloned_path)
cloned_data = ParquetPointDataTableReader(cloned_path)
assert_frame_equal(
cloned_data.dataframe,
df.drop(exclude_cols, axis=1),
check_dtype=False,
check_categorical=False,
)