def _iterate(self, axis, _hash_key, mult):
keys = self.metrica.choices(axis, self._filter.get(axis, None))
pipe = redis.pipeline(transaction=False)
for key in keys:
fl = dict(self._filter, **{axis: key})
hash_field_id = self.metrica.hash_field_id(**fl)
pipe.hget(_hash_key, hash_field_id)
values = pipe.execute()
return zip(keys, [int(v or 0) / mult for v in values])
def _iterate_on_dateaxis(self, _hash_key_postfix, mult):
prefix = self.metrica.key_prefix()
keys = []
pipe = redis.pipeline(transaction=False)
for key, tp_id in self.metrica.date_axis.iterate(self):
keys.append(key)
hash_key = u'%s:%s' % (prefix, tp_id) + _hash_key_postfix
pipe.hget(hash_key, self._hash_field_id)
values = pipe.execute()
return zip(keys, [int(v or 0) / mult for v in values])
def kick(self, value=1, date=None, **kwargs):
"""Registers an event with parameters (for each of axis)"""
date = date or datetime.datetime.now()
value = int(self.multiplier * value)
hash_key_prefix = self.key_prefix()
choices_sets_to_append = []
hash_field_id_parts = []
for axis_kw, axis in self.axes:
param_value = kwargs.pop(axis_kw, None)
hash_field_id_parts.append(
list(axis.get_field_id_parts(param_value))
)
try:
if axis.store_choice:
set_key = '__choices__:%s' % axis_kw
choices_sets_to_append.append((set_key, param_value))
except AttributeError: # 'duck typing'
pass
if kwargs:
raise TypeError("Invalid kwargs left: %s" % kwargs)
choices_sets_to_append = filter(None, choices_sets_to_append)
# Here we go: bumping all counters out there
pipe = redis.pipeline(transaction=False)
for date_scale in self.date_axis.scales(date):
hash_key = '%s:%s' % (hash_key_prefix, date_scale.id)
for parts in itertools.product(*hash_field_id_parts):
hash_field_id = ':'.join(parts)
self._increment(pipe, hash_key, hash_field_id, value)
if date_scale.expiration:
pipe.expire(hash_key, date_scale.expiration)
if date_scale.store:
choices_sets_to_append.append((date_scale.store, date_scale.value))
for key, s_value in choices_sets_to_append:
pipe.sadd('%s:%s' % (hash_key_prefix, key),
s_value)
pipe.execute()
def _iterate(self, axis, _hash_key, mult):
keys = self.metrica.choices(axis)
pipe = redis.pipeline(transaction=False)
for key in keys:
fl = dict(self._filter, **{axis: key})
hash_field_id = self.metrica.hash_field_id(**fl)
pipe.hget(_hash_key, hash_field_id)
values = pipe.execute()
return zip(keys, [int(v or 0) / mult for v in values])
def kick(self, value=1, date=None, **kwargs):
"""Registers an event with parameters (for each of axis)"""
date = date or datetime.datetime.now()
value = int(self.multiplier * value)
hash_key_prefix = self.key_prefix()
choices_sets_to_append = []
hash_field_id_parts = []
for axis_kw, axis in self.axes:
param_value = kwargs.pop(axis_kw, None)
hash_field_id_parts.append(
list(axis.get_field_id_parts(param_value)))
try:
if axis.store_choice:
set_key = '__choices__:%s' % axis_kw
choices_sets_to_append.append((set_key, param_value))
except AttributeError: # 'duck typing'
pass
if kwargs:
raise TypeError("Invalid kwargs left: %s" % kwargs)
choices_sets_to_append = filter(None, choices_sets_to_append)
# Here we go: bumping all counters out there
pipe = redis.pipeline(transaction=False)
for date_scale in self.date_axis.scales(date):
hash_key = '%s:%s' % (hash_key_prefix, date_scale.id)
for parts in itertools.product(*hash_field_id_parts):
hash_field_id = ':'.join(parts)
self._increment(pipe, hash_key, hash_field_id, value)
if date_scale.expiration:
pipe.expire(hash_key, date_scale.expiration)
if date_scale.store:
choices_sets_to_append.append(
(date_scale.store, date_scale.value))
for key, s_value in choices_sets_to_append:
pipe.sadd('%s:%s' % (hash_key_prefix, key), s_value)
pipe.execute()
def timeserie(self, since, until, scale=None, _hash_key_postfix='', _mult=None):
mult = _mult or self.metrica.multiplier
prefix = self.metrica.key_prefix()
ts_points = self.metrica.date_axis.timeserie(since, until, scale)
points = []
pipe = redis.pipeline(transaction=False)
for point, tp_id in ts_points:
points.append(point)
hash_key = u'%s:%s%s' % (prefix, tp_id, _hash_key_postfix)
pipe.hget(hash_key, self._hash_field_id)
values = pipe.execute()
return zip(points, [int(v or 0) / mult for v in values])
def _iterate_on_dateaxis(self, _hash_key_postfix, mult):
prefix = self.metrica.key_prefix()
keys = []
pipe = redis.pipeline(transaction=False)
for key, tp_id in self.metrica.date_axis.iterate(self):
keys.append(key)
hash_key = '%s:%s' % (prefix, tp_id) + _hash_key_postfix
pipe.hget(hash_key, self._hash_field_id)
values = pipe.execute()
return zip(keys, [int(v or 0) / mult for v in values])
def timeserie(self,
since,
until,
scale=None,
_hash_key_postfix='',
_mult=None):
mult = _mult or self.metrica.multiplier
prefix = self.metrica.key_prefix()
ts_points = self.metrica.date_axis.timeserie(since, until, scale)
points = []
pipe = redis.pipeline(transaction=False)
for point, tp_id in ts_points:
points.append(point)
hash_key = '%s:%s%s' % (prefix, tp_id, _hash_key_postfix)
pipe.hget(hash_key, self._hash_field_id)
values = pipe.execute()
return zip(points, [int(v or 0) / mult for v in values])
