def main(self):
if self.args.names_only:
self.print_column_names()
return
#Read in header and rows
reader = CSVKitReader(self.input_file, **self.reader_kwargs)
column_names = reader.next()
if self.args.columns is None:
grouped_columns_ids = []
else:
grouped_columns_ids = parse_column_identifiers(self.args.columns,
column_names,
self.args.zero_based)
aggregations = []
try:
for (fun, cols) in map(lambda (f, cols): (
f, parse_column_identifiers(cols, column_names, self.args.zero_based)),
self.args.aggregations):
for col in cols:
aggregations.append(aggregate_functions[fun](col))
except KeyError:
self.argparser.error("Wrong aggregator function. Available: " + ', '.join(aggregate_functions.keys()))
#Determine columns to group by, default to all columns
#Write the output
output = CSVKitWriter(self.output_file, **self.writer_kwargs)
for row in group_rows(column_names, reader, grouped_columns_ids,
aggregations):
output.writerow(row)
def test_group_two(self):
output = list(group_rows(test_header, test_data, [1, 2],
[MaxAggregator(3), MinAggregator(4),
CountAggregator(4), ]))
self.assertEqual(len(output), 3)
self.assertEqual(output[1], ['a', 'a', 3, 2, 2])
self.assertEqual(output[2], ['b', 'a', 6, 0, 2])
def test_group_zero(self):
output = list(group_rows(test_header, test_data, [],
[MaxAggregator(3), MinAggregator(4),
CountAggregator(4), ]))
self.assertEqual(len(output), 2)
self.assertEqual(output[1], [6, 0, 4])
def test_header(self):
output = list(group_rows(test_header, test_data, [1],
[MaxAggregator(3), MinAggregator(4)]))
self.assertEqual(output[0], ['h2', 'max(h4)', 'min(h5)'])
