def test_csv_only(self):
"""
Ensure only the paths of the csv files
are returned.
"""
input_path = os.path.join(os.path.dirname(__file__),
"test_data",
"things_kinds")
csv_paths = list(i_walk_csv_paths(input_path))
self.assertEqual(2, len(csv_paths))
for path in csv_paths:
self.assertIn('.csv', path)
def main():
"""
Consume many csv files as if one.
"""
import pathlib
input_dir = pathlib.Path('test_data/things_kinds')
# # Use a generator expression
# iterables = (karld.io.i_get_csv_data(data_path)
# for data_path in i_walk_csv_paths(str(input_dir)))
# # or a generator map.
iterables = imap(karld.io.i_get_csv_data,
i_walk_csv_paths(str(input_dir)))
items = chain.from_iterable(iterables)
for item in items:
print(item[0], item[1])
def main():
"""
Merge a number of homogeneous small csv files on a key.
Small means they all together fit in
your computer's memory.
"""
import pathlib
input_dir = pathlib.Path('test_data/things_kinds')
data_items_iter = (karld.io.i_get_csv_data(data_path)
for data_path in i_walk_csv_paths(str(input_dir)))
KINDS = 1
groups = sort_merge_group(data_items_iter, itemgetter(KINDS))
for group in groups:
print(group[0])
for item in group[1]:
print('\t' + item[0])
print()
