def test_dataset(version):
num_values = (100, 100)
num_files = 5
paths = [random_path() for i in range(num_files)]
data = {
"col_" + str(i): np.random.randn(num_values[0])
for i in range(num_values[1])
}
table = pa.table(data)
TEST_FILES.extend(paths)
for index, path in enumerate(paths):
rows = (
index * (num_values[0] // num_files),
(index + 1) * (num_values[0] // num_files),
)
write_feather(table[rows[0]:rows[1]], path, version=version)
data = FeatherDataset(paths).read_table()
assert data.equals(table)
def test_dataset(version):
num_values = (100, 100)
num_files = 5
paths = [random_path() for i in range(num_files)]
df = pd.DataFrame(np.random.randn(*num_values),
columns=['col_' + str(i) for i in range(num_values[1])])
TEST_FILES.extend(paths)
for index, path in enumerate(paths):
rows = (index * (num_values[0] // num_files),
(index + 1) * (num_values[0] // num_files))
write_feather(df.iloc[rows[0]:rows[1]], path, version=version)
data = FeatherDataset(paths).read_pandas()
assert_frame_equal(data, df)
def test_dataset(self):
num_values = (100, 100)
num_files = 5
paths = [random_path() for i in range(num_files)]
df = pd.DataFrame(
np.random.randn(*num_values),
columns=['col_' + str(i) for i in range(num_values[1])])
self.test_files.extend(paths)
for index, path in enumerate(paths):
rows = (index * (num_values[0] // num_files),
(index + 1) * (num_values[0] // num_files))
writer = FeatherWriter()
writer.open(path)
for col in range(num_values[1]):
writer.write_array(df.columns[col], df.iloc[rows[0]:rows[1],
col])
writer.close()
data = FeatherDataset(paths).read_pandas()
assert_frame_equal(data, df)