revision_count = 0.0
revert_count = 0.0
for rev in rev_data:
if __revert(rev[0], rev[1], rev[2], rev[3], thread_args):
revert_count += 1.0
revision_count += 1.0
return [(revision_count, revert_count)]
# ==========================
# DEFINE METRIC AGGREGATORS
# ==========================
# Build "weighted rate" decorator
revert_rate_avg = weighted_rate
revert_rate_avg = decorator_builder(RevertRate.header())(
revert_rate_avg)
setattr(revert_rate_avg, um.METRIC_AGG_METHOD_FLAG, True)
setattr(revert_rate_avg, um.METRIC_AGG_METHOD_NAME, 'revert_rate_avg')
setattr(revert_rate_avg, um.METRIC_AGG_METHOD_HEAD, ['total_users',
'total_revisions',
'average_rate',])
setattr(revert_rate_avg, um.METRIC_AGG_METHOD_KWARGS, {'val_idx' : 1,
'weight_idx' : 1})
# testing
if __name__ == "__main__":
r = RevertRate()
users = ['17792132', '17797320', '17792130', '17792131', '17792136',
'17792137', '17792134', '17797328', '17797329', '17792138']
for i in xrange(5):
total = 0
pos = 0
for r in metric.__iter__():
try:
if r[1]:
pos += 1
total += 1
except (IndexError, TypeError):
continue
if total:
return [total, pos, float(pos) / total]
else:
return [total, pos, 0.0]
# Build "rate" decorator
live_accounts_agg = boolean_rate
live_accounts_agg = decorator_builder(LiveAccount.header())(live_accounts_agg)
setattr(live_accounts_agg, um.METRIC_AGG_METHOD_FLAG, True)
setattr(live_accounts_agg, um.METRIC_AGG_METHOD_NAME, 'live_accounts_agg')
setattr(live_accounts_agg, um.METRIC_AGG_METHOD_HEAD, ['total_users',
'is_live', 'rate'])
setattr(live_accounts_agg, um.METRIC_AGG_METHOD_KWARGS, {'val_idx': 1})
if __name__ == "__main__":
users = ['17792132', '17797320', '17792130', '17792131', '17792136',
13234584, 156171]
la = LiveAccount()
for r in la.process(users, log=True):
print r
metric_header = RevertRate.header()
field_prefixes = \
{
'reverted_': 1,
'reverts_': 2,
'revisions_': 3,
}
# Build "stats" aggregator
op_list = [sum, mean]
revert_stats_agg = build_numpy_op_agg(build_agg_meta(op_list, field_prefixes),
metric_header,
'revert_stats_agg')
agg_kwargs = getattr(revert_stats_agg, METRIC_AGG_METHOD_KWARGS)
setattr(revert_stats_agg, METRIC_AGG_METHOD_KWARGS, agg_kwargs)
# Build proportion aggregator
revert_prop_agg = boolean_rate
revert_prop_agg = decorator_builder(RevertRate.header())(
revert_prop_agg)
setattr(revert_prop_agg, METRIC_AGG_METHOD_FLAG, True)
setattr(revert_prop_agg, METRIC_AGG_METHOD_NAME, 'revert_prop_agg')
setattr(revert_prop_agg, METRIC_AGG_METHOD_HEAD, ['total_users',
'total_reverted',
'rate', ])
setattr(revert_prop_agg, METRIC_AGG_METHOD_KWARGS, {'val_idx': 1})
self._results = [[user,
rowValues.get(user)['is_blocked'],
rowValues.get(user)['block_count'],
rowValues.get(user)['block_first'],
rowValues.get(user)['block_last']]
for user in rowValues.keys()]
return self
# ==========================
# DEFINE METRIC AGGREGATORS
# ==========================
# Build "rate" decorator
block_rate_agg = weighted_rate
block_rate_agg = decorator_builder(Blocks.header())(block_rate_agg)
setattr(block_rate_agg, METRIC_AGG_METHOD_FLAG, True)
setattr(block_rate_agg, METRIC_AGG_METHOD_NAME, 'b_rate_agg')
setattr(block_rate_agg, METRIC_AGG_METHOD_HEAD, ['total_users',
'total_weight',
'rate'])
setattr(block_rate_agg, METRIC_AGG_METHOD_KWARGS, {
'val_idx': 2,
})
# Build "proportion" decorator
block_prop_agg = boolean_rate
block_prop_agg = decorator_builder(Blocks.header())(block_prop_agg)
setattr(block_prop_agg, METRIC_AGG_METHOD_FLAG, True)
for i in e.__iter__():
new_i = i[:] # Make a copy of the edit count element
new_i.append(new_i[1] / (time_diff * self.time_unit_count))
new_i.append(time_diff)
edit_rate.append(new_i)
self._results = edit_rate
return self
# ==========================
# DEFINE METRIC AGGREGATORS
# ==========================
# Build "rate" decorator
edit_rate_agg = weighted_rate
edit_rate_agg = decorator_builder(EditRate.header())(edit_rate_agg)
setattr(edit_rate_agg, um.METRIC_AGG_METHOD_FLAG, True)
setattr(edit_rate_agg, um.METRIC_AGG_METHOD_NAME, 'edit_rate_agg')
setattr(edit_rate_agg, um.METRIC_AGG_METHOD_HEAD, ['total_users',
'total_weight', 'rate'])
setattr(edit_rate_agg, um.METRIC_AGG_METHOD_KWARGS, {
'val_idx': 2,
})
metric_header = EditRate.header()
field_prefixes = \
{
'count_': 1,
'rate_': 2,
elif first < len(results):
dat_obj_start = date_parse(results[first])
else:
return -1
time_diff = dat_obj_end - dat_obj_start
return int(time_diff.seconds / 60) + abs(time_diff.days) * 24
# ==========================
# DEFINE METRIC AGGREGATORS
# ==========================
# Build "average" aggregator
ttt_avg_agg = weighted_rate
ttt_avg_agg = decorator_builder(TimeToThreshold.header())(ttt_avg_agg)
setattr(ttt_avg_agg, um.METRIC_AGG_METHOD_FLAG, True)
setattr(ttt_avg_agg, um.METRIC_AGG_METHOD_NAME, 'ttt_avg_agg')
setattr(ttt_avg_agg, um.METRIC_AGG_METHOD_HEAD, ['total_users',
'total_weight',
'average'])
setattr(ttt_avg_agg, um.METRIC_AGG_METHOD_KWARGS, {'val_idx': 1})
metric_header = TimeToThreshold.header()
field_prefixes = {
'time_diff_': 1,
}
if metric_params.log_:
logging.info(__name__ + '::Processed PID = %s. '
'Dropped users = %s.' % (
os.getpid(), str(dropped_users)))
return results
# ==========================
# DEFINE METRIC AGGREGATORS
# ==========================
# Build "rate" decorator
threshold_editors_agg = boolean_rate
threshold_editors_agg = decorator_builder(Threshold.header())(
threshold_editors_agg)
setattr(threshold_editors_agg, um.METRIC_AGG_METHOD_FLAG, True)
setattr(threshold_editors_agg, um.METRIC_AGG_METHOD_NAME,
'threshold_editors_agg')
setattr(threshold_editors_agg, um.METRIC_AGG_METHOD_HEAD, ['total_users',
'threshold_reached',
'rate'])
setattr(threshold_editors_agg, um.METRIC_AGG_METHOD_KWARGS, {'val_idx': 1})
# testing
if __name__ == "__main__":
for r in Threshold(namespace=[0, 4]).process([13234584, 156171],
num_threads=0,
log_=True).__iter__():
print r
- **user_handle** - String or Integer (optionally lists).
Value or list of values representing user handle(s).
"""
# Utilize threshold, survival is denoted by making at least one
# revision
kwargs['survival_'] = True
kwargs['n'] = 1
self._results = th.Threshold(**kwargs).\
process(user_handle, **kwargs)._results
return self
# ==========================
# DEFINE METRIC AGGREGATORS
# ==========================
# Build "rate" decorator
survival_editors_agg = boolean_rate
survival_editors_agg = decorator_builder(Survival.header())(
survival_editors_agg)
setattr(survival_editors_agg, METRIC_AGG_METHOD_FLAG, True)
setattr(survival_editors_agg, METRIC_AGG_METHOD_NAME,
'survival_editors_agg')
setattr(survival_editors_agg, METRIC_AGG_METHOD_HEAD, ['total_users',
'has_survived',
'rate'])
setattr(survival_editors_agg, METRIC_AGG_METHOD_KWARGS, {'val_idx': 1})
