def main():
files = sys.argv[1:]
cache_path = 'geo_counts.csv'
if os.path.exists(cache_path):
counts = load_cache(cache_path)
else:
counts = count_files(files, keepers, criteria)
write_counts(counts, cache_path)
plot_error_vs_time(counts, dates)
plot_country_error_vs_time(counts,dates)
plot_mom_vs_time(counts,dates)
basic_stats(counts)
def main():
opts = parse_args()
criteria = (lambda r : r.site() in ['M', 'Z'], lambda r : r.old_init_request())
fields = ('date', 'lang', 'project', 'site', 'country_code2', 'provider_from_fname')
counts = count_files(opts['glob'],
fields,
criteria,
count_event=10,
fname='carrier.local.all.incremental', limit=10000)
df = pd.DataFrame([v + (c,) for v,c in counts.items()],
columns = ['date', 'lang', 'project', 'site', 'country', 'carrier', 'count'])
df.date = df.date.apply(lambda d : datetime.datetime.strftime(d, '%Y-%m-%d'))
logger.info('carriers: %s', pprint.pformat(df.carrier.unique()))
df.to_csv('carrier.local.all', index=False, sep='\t')
def main():
parser = SquidArgumentParser()
parser.add_argument('--nprocs', default=10)
args = parser.parse_args()
logger.info(pprint.pformat(args.__dict__))
keepers = ['date', 'language', 'project', 'site', 'country', 'na']
criteria = [
lambda r : r.old_init_request(),
lambda r : r.site() == 'M',
lambda r : r.datetime() > args.start,
lambda r : r.datetime() < args.end,
]
counts = count_files(args.squid_files,
keepers,
criteria,
count_event=1000,
limit=args.max_lines,
nproc=15,
fname='country_counts_incremental.csv')
write_counts(counts, 'country_counts.csv')
from squid.mapreduce import count_files
import sys
import pandas as pd
from operator import itemgetter
fields = ["country", "x_cs_str", "provider", "date", "site", "lang", "project"]
counts = count_files([sys.argv[1]], fields)
lines = [key + (count,) for key, count in counts.items()]
lines.sort(key=itemgetter(*range(len(fields) + 1)))
df = pd.DataFrame(lines, columns=fields + ["count"])
df.to_csv("%s.counts.csv" % sys.argv[1], index=False)