blob: f39432c8bc9dddd8f955000b64ade65e4179c123 [file] [log] [blame]
#!/usr/bin/env python2.7
from __future__ import print_function
desc = '''Generate the difference of two YAML files into a new YAML file (works on
pair of directories too). A new attribute 'Added' is set to True or False
depending whether the entry is added or removed from the first input to the
next.
The tools requires PyYAML.'''
import yaml
# Try to use the C parser.
try:
from yaml import CLoader as Loader
except ImportError:
from yaml import Loader
import optrecord
import argparse
from collections import defaultdict
from multiprocessing import cpu_count, Pool
if __name__ == '__main__':
parser = argparse.ArgumentParser(description=desc)
parser.add_argument(
'yaml_dir_or_file_1',
help='An optimization record file or a directory searched for optimization '
'record files that are used as the old version for the comparison')
parser.add_argument(
'yaml_dir_or_file_2',
help='An optimization record file or a directory searched for optimization '
'record files that are used as the new version for the comparison')
parser.add_argument(
'--jobs',
'-j',
default=cpu_count(),
type=int,
help='Max job count (defaults to %(default)s, the current CPU count)')
parser.add_argument(
'--no-progress-indicator',
'-n',
action='store_true',
default=False,
help='Do not display any indicator of how many YAML files were read.')
parser.add_argument('--output', '-o', default='diff.opt.yaml')
args = parser.parse_args()
files1 = optrecord.find_opt_files([args.yaml_dir_or_file_1])
files2 = optrecord.find_opt_files([args.yaml_dir_or_file_2])
print_progress = not args.no_progress_indicator
all_remarks1, _, _ = optrecord.gather_results(files1, args.jobs, print_progress)
all_remarks2, _, _ = optrecord.gather_results(files2, args.jobs, print_progress)
added = set(all_remarks2.values()) - set(all_remarks1.values())
removed = set(all_remarks1.values()) - set(all_remarks2.values())
for r in added:
r.Added = True
for r in removed:
r.Added = False
with open(args.output, 'w') as stream:
yaml.dump_all(added | removed, stream)