def test_basics_without_type_check(self):
# Run the workflow without --pipeline_type_check option. This will make sure
# the typehints associated with all transforms will have default values and
# therefore any custom coders will not be used. The default coder (pickler)
# will be used instead.
temp_path = self.create_temp_file(self.SAMPLE_RECORDS)
group_with_coder.run([
'--no_pipeline_type_check',
'--input=%s*' % temp_path,
'--output=%s.result' % temp_path])
# Parse result file and compare.
results = []
with open(temp_path + '.result') as result_file:
for line in result_file:
name, points = line.split(',')
results.append((name, int(points)))
logging.info('result: %s', results)
self.assertEqual(
sorted(results),
sorted([('ann', 15), ('fred', 9), ('joe', 60), ('mary', 8)]))
def test_basics_with_type_check(self):
# Run the workflow with --pipeline_type_check option. This will make sure
# the typehints associated with all transforms will have non-default values
# and therefore any custom coders will be used. In our case we want to make
# sure the coder for the Player class will be used.
temp_path = self.create_temp_file(self.SAMPLE_RECORDS)
group_with_coder.run([
'--pipeline_type_check',
'--input=%s*' % temp_path,
'--output=%s.result' % temp_path])
# Parse result file and compare.
results = []
with open(temp_path + '.result') as result_file:
for line in result_file:
name, points = line.split(',')
results.append((name, int(points)))
logging.info('result: %s', results)
self.assertEqual(
sorted(results),
sorted([('x:ann', 15), ('x:fred', 9), ('x:joe', 60), ('x:mary', 8)]))
