def user_agg(si=None):
'''
Loads search.gl and aggregates it by UserID to get some features.
NB: this did not help.
'''
start = datetime.now()
if si is None:
si = load('search.gl')
D = 2**20
si['SQexists'] = si['SearchQuery'].apply(lambda s : s != '')
si['SQhash'] = si['SearchQuery'].apply(lambda s : abs(hash(s)) % D)
si['SPexists'] = si['SearchParams'].apply(lambda d : d is not None)
f = {'pctSQE' : agg.AVG('SQexists'),
'pctSPE' : agg.AVG('SPexists'),
'numSearches' : agg.COUNT(),
'allCat' : agg.CONCAT('CategoryID'),
'allSQ' : agg.CONCAT('SQhash')}
si = si[['UserID',
'CategoryID',
'SearchParams',
'SQexists',
'SPexists',
'SQhash']]
usr = si.groupby('UserID', f)
usr['allSQ'] = usr['allSQ'].apply(lambda l : list(set(l)))
usr['allCat'] = usr['allCat'].apply(lambda l : list(set(l)))
usr_dict = sframe_to_dict('UserID', usr)
avito2_io.put_artifact(usr_dict, 'user_si.pkl')
print('elapsed time: %s' % (datetime.now() - start))
def user_agg(si=None):
'''
Loads search.gl and aggregates it by UserID to get some features.
NB: this did not help.
'''
start = datetime.now()
if si is None:
si = load('search.gl')
D = 2**20
si['SQexists'] = si['SearchQuery'].apply(lambda s : s != '')
si['SQhash'] = si['SearchQuery'].apply(lambda s : abs(hash(s)) % D)
si['SPexists'] = si['SearchParams'].apply(lambda d : d is not None)
f = {'pctSQE' : agg.AVG('SQexists'),
'pctSPE' : agg.AVG('SPexists'),
'numSearches' : agg.COUNT(),
'allCat' : agg.CONCAT('CategoryID'),
'allSQ' : agg.CONCAT('SQhash')}
si = si[['UserID',
'CategoryID',
'SearchParams',
'SQexists',
'SPexists',
'SQhash']]
usr = si.groupby('UserID', f)
usr['allSQ'] = usr['allSQ'].apply(lambda l : list(set(l)))
usr['allCat'] = usr['allCat'].apply(lambda l : list(set(l)))
usr_dict = sframe_to_dict('UserID', usr)
avito2_io.put_artifact(usr_dict, 'user_si.pkl')
print 'elapsed time: %s' % (datetime.now() - start)
def make_user_dict():
'''
Loads user.gl and creates a dict-of-dicts {int: dict} like:
{UserID: {other_fields:other_values}}
Saves result at artifacts/user_dict.pkl. It can be loaded with
avito2_io.get_artifact.
'''
start = datetime.now()
user = load('user.gl')
user_dict = sframe_to_dict('UserID', user)
avito2_io.put_artifact(user_dict, 'user_dict.pkl')
print('elapsed time: %s' % (datetime.now() - start))
def make_user_dict():
'''
Loads user.gl and creates a dict-of-dicts {int: dict} like:
{UserID: {other_fields:other_values}}
Saves result at artifacts/user_dict.pkl. It can be loaded with
avito2_io.get_artifact.
'''
start = datetime.now()
user = load('user.gl')
user_dict = sframe_to_dict('UserID', user)
avito2_io.put_artifact(user_dict, 'user_dict.pkl')
print 'elapsed time: %s' % (datetime.now() - start)
for (k, line) in enumerate(reader):
user_id = int(line['UserID'])
if user_id in out:
vis_ct = out[user_id].setdefault('vis_ct', 0)
out[user_id]['vis_ct'] = vis_ct + 1
if (k + 1) % 1000000 == 0:
print 'read %d lines from VisitsStream.tsv.gz' % (k + 1)
for k in out:
out[k].setdefault('vis_ct', 0)
return out
if __name__ == '__main__':
start = datetime.now()
print 'running at: ' + str(start)
parser = argparse.ArgumentParser(description =
'Collects counts of UserID from several data files.')
parser.add_argument('--min_ct', type=int, default=None)
parser.add_argument('--max_lines', type=int, default=None)
args = parser.parse_args()
user_counts = user_counts(args.min_ct)
avito2_io.put_artifact(user_counts, 'user_counts.pkl')
print 'elapsed time: %s' % (datetime.now() - start)
'''
out = {}
with open(avito2_io.ADS_INFO) as f:
reader = csv.DictReader(f, delimiter='\t')
for (k, line) in enumerate(reader):
if k == maxlines:
break
if (int(line['IsContext']) == 1):
if line['Price'] == '':
line['Price'] = -1
if line['CategoryID'] == '':
line['CategoryID'] = -1
values = [int(line['CategoryID']),
int(float(line['Price'])),
line['Title'],
line['Params']]
out[int(line['AdID'])] = values
if (k + 1) % 1000000 == 0:
print 'read %d lines' % (k + 1)
return out
if __name__=='__main__':
start = datetime.now()
print 'parsing AdsInfo.tsv'
out = parse_ads()
print 'saving context ads to ARTIFACTS/'
avito2_io.put_artifact(out, 'context_ads.pkl')
print 'Finished, elapsed time: %s' % (datetime.now() - start)
(k + 1))
for k in out:
out[k].setdefault('ph_ct', 0)
with gzip.open(avito2_io.VISIT) as f_vis:
reader = csv.DictReader(f_vis, delimiter='\t')
for (k, line) in enumerate(reader):
user_id = int(line['UserID'])
if user_id in out:
vis_ct = out[user_id].setdefault('vis_ct', 0)
out[user_id]['vis_ct'] = vis_ct + 1
if (k + 1) % 1000000 == 0:
print('read %d lines from VisitsStream.tsv.gz' % (k + 1))
for k in out:
out[k].setdefault('vis_ct', 0)
return out
if __name__ == '__main__':
start = datetime.now()
print('running at: ' + str(start))
parser = argparse.ArgumentParser(
description='Collects counts of UserID from several data files.')
parser.add_argument('--min_ct', type=int, default=None)
parser.add_argument('--max_lines', type=int, default=None)
args = parser.parse_args()
user_counts = user_counts(args.min_ct)
avito2_io.put_artifact(user_counts, 'user_counts.pkl')
print('elapsed time: %s' % (datetime.now() - start))