def get_data_from_csv(csv_reader):
"""Creates a list of StatEntry objects based on data in CSV data.
Input CSV data must be in the format:
Description,timestamp,num_batches,time mean value,time sd
Args:
csv_reader: csv.reader instance.
Returns:
A tuple of datetime timestamp and list of benchmark_util.StatEntry objects.
Raises:
ValueError: if CSV is invalid.
"""
timestamp = None
stat_entries = []
for row in csv_reader:
if len(row) != 5:
raise ValueError('Expected 5 entries per line in the input CSV file, '
'but found %d entries.' % len(row))
if '' in row:
raise ValueError('Found empty entries in row: %s' % row)
# Set timestamp based on the first line in CSV file.
if timestamp is None:
# Example of time formatting: 2017-06-26 02:59:29.325579
timestamp = datetime.strptime(row[1], "%Y-%m-%d %H:%M:%S.%f")
stat_entries.append(
benchmark_util.StatEntry(row[0], float(row[3]), 1))
return timestamp, stat_entries
def testStoreDataWithEntries(self):
with tempfile.TemporaryFile() as temp_file:
timing_entries = [benchmark_util.StatEntry('test', 0.1, 1)]
benchmark_util.store_data_in_json(timing_entries,
datetime.date(2017, 1, 1),
temp_file.name)
json_output = json.loads(open(temp_file.name, 'r').read())
self.assertEquals(1, len(json_output['entries']['entry']))
self.assertEquals('test',
json_output['entries']['entry'][0]['name'])
self.assertEquals(0.1,
json_output['entries']['entry'][0]['wallTime'])
self.assertEquals(u'1',
json_output['entries']['entry'][0]['iters'])
self.assertEquals(u'1483228800', json_output['startTime'])
self.assertEquals('TestBenchmark', json_output['name'])