def test_row_filter(tempdir):
fn = os.path.join(tempdir, 'test.parquet')
df = pd.DataFrame({'a': ['o'] * 10 + ['i'] * 5, 'b': range(15)})
write(fn, df, row_group_offsets=8)
pf = ParquetFile(fn)
assert pf.count(filters=[["a", "==", "o"]]) == 15
assert pf.count(filters=[["a", "==", "o"]], row_filter=True) == 10
assert pf.count(filters=[["a", "==", "i"]], row_filter=True) == 5
assert pf.count(filters=[["b", "in", [1, 3, 4]]]) == 8
assert pf.count(filters=[["b", "in", [1, 3, 4]]], row_filter=True) == 3
assert pf.to_pandas(filters=[["b", "in", [1, 3, 4]]],
row_filter=True).b.tolist() == [1, 3, 4]
assert pf.to_pandas(filters=[["a", "<", "o"]],
row_filter=True).b.tolist() == [10, 11, 12, 13, 14]
def test_groups_roundtrip(tempdir, scheme):
df = pd.DataFrame({'a': np.random.choice(['a', 'b', None], size=1000),
'b': np.random.randint(0, 64000, size=1000),
'c': np.random.choice([True, False], size=1000)})
writer.write(tempdir, df, partition_on=['a', 'c'], file_scheme=scheme)
r = ParquetFile(tempdir)
assert r.columns == ['b']
out = r.to_pandas()
if scheme == 'drill':
assert set(r.cats) == {'dir0', 'dir1'}
assert set(out.columns) == {'b', 'dir0', 'dir1'}
out.rename(columns={'dir0': 'a', 'dir1': 'c'}, inplace=True)
for i, row in out.iterrows():
assert row.b in list(df[(df.a == row.a) & (df.c == row.c)].b)
writer.write(tempdir, df, row_group_offsets=[0, 50], partition_on=['a', 'c'],
file_scheme=scheme)
r = ParquetFile(tempdir)
assert r.fmd.num_rows == r.count() == sum(~df.a.isnull())
assert len(r.row_groups) == 8
out = r.to_pandas()
if scheme == 'drill':
assert set(out.columns) == {'b', 'dir0', 'dir1'}
out.rename(columns={'dir0': 'a', 'dir1': 'c'}, inplace=True)
for i, row in out.iterrows():
assert row.b in list(df[(df.a==row.a)&(df.c==row.c)].b)
def test_roundtrip(tempdir, scheme, row_groups, comp):
data = pd.DataFrame({'i32': np.arange(1000, dtype=np.int32),
'i64': np.arange(1000, dtype=np.int64),
'u64': np.arange(1000, dtype=np.uint64),
'f': np.arange(1000, dtype=np.float64),
'bhello': np.random.choice([b'hello', b'you',
b'people'], size=1000).astype("O")})
data['a'] = np.array([b'a', b'b', b'c', b'd', b'e']*200, dtype="S1")
data['aa'] = data['a'].map(lambda x: 2*x).astype("S2")
data['hello'] = data.bhello.str.decode('utf8')
data['bcat'] = data.bhello.astype('category')
data['cat'] = data.hello.astype('category')
fname = os.path.join(tempdir, 'test.parquet')
write(fname, data, file_scheme=scheme, row_group_offsets=row_groups,
compression=comp)
r = ParquetFile(fname)
assert r.fmd.num_rows == r.count() == 1000
df = r.to_pandas()
assert data.cat.dtype == 'category'
for col in r.columns:
assert (df[col] == data[col]).all()
# tests https://github.com/dask/fastparquet/issues/250
assert isinstance(data[col][0], type(df[col][0]))
def test_empty_dataframe(tempdir):
df = pd.DataFrame({'a': [], 'b': []}, dtype=int)
fn = os.path.join(str(tempdir), 'test.parquet')
write(fn, df)
pf = ParquetFile(fn)
out = pf.to_pandas()
assert pf.count() == 0
assert len(out) == 0
assert (out.columns == df.columns).all()
assert pf.statistics
def test_append_empty(tempdir, scheme):
fn = os.path.join(str(tempdir), 'test.parq')
df = pd.DataFrame({'a': [1, 2, 3, 0],
'b': ['a', 'a', 'b', 'b']})
write(fn, df.head(0), write_index=False, file_scheme=scheme)
pf = ParquetFile(fn)
assert pf.count() == 0
assert pf.file_scheme == 'empty'
write(fn, df, append=True, write_index=False, file_scheme=scheme)
pf = ParquetFile(fn)
pd.testing.assert_frame_equal(
pf.to_pandas(), df, check_categorical=False, check_dtype=False)
def test_empty_groupby(tempdir):
df = pd.DataFrame({'a': np.random.choice(['a', 'b', None], size=1000),
'b': np.random.randint(0, 64000, size=1000),
'c': np.random.choice([True, False], size=1000)})
df.loc[499:, 'c'] = True # no False in second half
writer.write(tempdir, df, partition_on=['a', 'c'], file_scheme='hive',
row_group_offsets=[0, 500])
r = ParquetFile(tempdir)
assert r.count() == sum(~df.a.isnull())
assert len(r.row_groups) == 6
out = r.to_pandas()
for i, row in out.iterrows():
assert row.b in list(df[(df.a==row.a)&(df.c==row.c)].b)
def test_attributes(tempdir):
df = pd.DataFrame({
'x': [1, 2, 3, 4],
'y': [1.0, 2.0, 1.0, 2.0],
'z': ['a', 'b', 'c', 'd']
})
fn = os.path.join(tempdir, 'foo.parquet')
write(fn, df, row_group_offsets=[0, 2])
pf = ParquetFile(fn)
assert pf.columns == ['x', 'y', 'z']
assert len(pf.row_groups) == 2
assert pf.count() == 4
assert join_path(fn).replace("\\", "/") == pf.info['name']
assert join_path(fn).replace("\\", "/") in str(pf)
for col in df:
assert getattr(pf.dtypes[col], "numpy_dtype",
pf.dtypes[col]) == df.dtypes[col]
