本文整理汇总了Python中sentry.app.buffer.incr函数的典型用法代码示例。如果您正苦于以下问题：Python incr函数的具体用法？Python incr怎么用？Python incr使用的例子？那么恭喜您, 这里精选的函数代码示例或许可以为您提供帮助。
在下文中一共展示了incr函数的15个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: add_tags
def add_tags(self, group, tags):
from sentry.models import TagValue, GroupTagValue
project_id = group.project_id
date = group.last_seen
for tag_item in tags:
if len(tag_item) == 2:
(key, value), data = tag_item, None
else:
key, value, data = tag_item
buffer.incr(TagValue, {
'times_seen': 1,
}, {
'project_id': project_id,
'key': key,
'value': value,
}, {
'last_seen': date,
'data': data,
})
buffer.incr(GroupTagValue, {
'times_seen': 1,
}, {
'group_id': group.id,
'project_id': project_id,
'key': key,
'value': value,
}, {
'last_seen': date,
})示例2: add_tags
def add_tags(self, group, tags):
from sentry.models import TagValue, GroupTagValue
project_id = group.project_id
date = group.last_seen
for tag_item in tags:
if len(tag_item) == 2:
(key, value), data = tag_item, None
else:
key, value, data = tag_item
buffer.incr(
TagValue,
{"times_seen": 1},
{"project_id": project_id, "key": key, "value": value},
{"last_seen": date, "data": data},
)
buffer.incr(
GroupTagValue,
{"times_seen": 1},
{"group_id": group.id, "project_id": project_id, "key": key, "value": value},
{"last_seen": date},
)示例3: _process_existing_aggregate
def _process_existing_aggregate(self, group, event, data, release):
date = max(event.datetime, group.last_seen)
extra = {
'last_seen': date,
'score': ScoreClause(group),
'data': data['data'],
}
if event.message and event.message != group.message:
extra['message'] = event.message
if group.level != data['level']:
extra['level'] = data['level']
if group.culprit != data['culprit']:
extra['culprit'] = data['culprit']
is_regression = self._handle_regression(group, event, release)
group.last_seen = extra['last_seen']
update_kwargs = {
'times_seen': 1,
}
buffer.incr(Group, update_kwargs, {
'id': group.id,
}, extra)
return is_regression示例4: add_tags
def add_tags(self, group, tags):
from sentry.models import TagValue, GroupTagValue
project = group.project
date = group.last_seen
tsdb_keys = []
for tag_item in tags:
if len(tag_item) == 2:
(key, value), data = tag_item, None
else:
key, value, data = tag_item
if not value:
continue
value = six.text_type(value)
if len(value) > MAX_TAG_VALUE_LENGTH:
continue
tsdb_id = u'%s=%s' % (key, value)
tsdb_keys.extend([
(tsdb.models.project_tag_value, tsdb_id),
])
buffer.incr(TagValue, {
'times_seen': 1,
}, {
'project': project,
'key': key,
'value': value,
}, {
'last_seen': date,
'data': data,
})
buffer.incr(GroupTagValue, {
'times_seen': 1,
}, {
'group': group,
'project': project,
'key': key,
'value': value,
}, {
'last_seen': date,
})
if tsdb_keys:
tsdb.incr_multi(tsdb_keys)示例5: _process_existing_aggregate
def _process_existing_aggregate(self, group, event, data):
date = max(event.datetime, group.last_seen)
extra = {
'last_seen': date,
'score': ScoreClause(group),
}
if event.message and event.message != group.message:
extra['message'] = event.message
if group.level != data['level']:
extra['level'] = data['level']
if group.culprit != data['culprit']:
extra['culprit'] = data['culprit']
is_regression = False
if group.is_resolved() and plugin_is_regression(group, event):
is_regression = bool(Group.objects.filter(
id=group.id,
# ensure we cant update things if the status has been set to
# muted
status__in=[GroupStatus.RESOLVED, GroupStatus.UNRESOLVED],
).exclude(
# add to the regression window to account for races here
active_at__gte=date - timedelta(seconds=5),
).update(
active_at=date,
# explicitly set last_seen here as ``is_resolved()`` looks
# at the value
last_seen=date,
status=GroupStatus.UNRESOLVED
))
group.active_at = date
group.status = GroupStatus.UNRESOLVED
group.last_seen = extra['last_seen']
update_kwargs = {
'times_seen': 1,
}
if event.time_spent:
update_kwargs.update({
'time_spent_total': event.time_spent,
'time_spent_count': 1,
})
buffer.incr(Group, update_kwargs, {
'id': group.id,
}, extra)
return is_regression示例6: _process_existing_aggregate
def _process_existing_aggregate(self, group, event, data):
date = max(event.datetime, group.last_seen)
extra = {
'last_seen': date,
'score': ScoreClause(group),
}
if event.message and event.message != group.message:
extra['message'] = event.message
if group.level != data['level']:
extra['level'] = data['level']
if group.culprit != data['culprit']:
extra['culprit'] = data['culprit']
if group.status == STATUS_RESOLVED or group.is_over_resolve_age():
# Making things atomic
is_regression = bool(Group.objects.filter(
id=group.id,
status=STATUS_RESOLVED,
).exclude(
active_at__gte=date,
).update(active_at=date, status=STATUS_UNRESOLVED))
transaction.commit_unless_managed(using=group._state.db)
group.active_at = date
group.status = STATUS_UNRESOLVED
else:
is_regression = False
group.last_seen = extra['last_seen']
update_kwargs = {
'times_seen': 1,
}
if event.time_spent:
update_kwargs.update({
'time_spent_total': event.time_spent,
'time_spent_count': 1,
})
buffer.incr(Group, update_kwargs, {
'id': group.id,
}, extra)
return is_regression示例7: _process_existing_aggregate
def _process_existing_aggregate(self, group, event, data):
date = max(event.datetime, group.last_seen)
extra = {
'last_seen': date,
'score': ScoreClause(group),
}
if event.message and event.message != group.message:
extra['message'] = event.message
if group.level != data['level']:
extra['level'] = data['level']
if group.culprit != data['culprit']:
extra['culprit'] = data['culprit']
is_regression = False
if group.is_resolved() and plugin_is_regression(group, event):
is_regression = bool(Group.objects.filter(
id=group.id,
).exclude(
# add 30 seconds to the regression window to account for
# races here
active_at__gte=date - timedelta(seconds=5),
).update(active_at=date, status=STATUS_UNRESOLVED))
transaction.commit_unless_managed(using=group._state.db)
group.active_at = date
group.status = STATUS_UNRESOLVED
group.last_seen = extra['last_seen']
update_kwargs = {
'times_seen': 1,
}
if event.time_spent:
update_kwargs.update({
'time_spent_total': event.time_spent,
'time_spent_count': 1,
})
buffer.incr(Group, update_kwargs, {
'id': group.id,
}, extra)
return is_regression示例8: add_tags
def add_tags(self, group, tags):
from sentry.models import TagValue, GroupTagValue
project_id = group.project_id
date = group.last_seen
tsdb_keys = []
for tag_item in tags:
if len(tag_item) == 2:
(key, value), data = tag_item, None
else:
key, value, data = tag_item
tsdb_id = u'%s=%s' % (key, value)
tsdb_keys.extend([
(tsdb.models.project_tag_value, tsdb_id),
])
buffer.incr(TagValue, {
'times_seen': 1,
}, {
'project_id': project_id,
'key': key,
'value': value,
}, {
'last_seen': date,
'data': data,
})
buffer.incr(GroupTagValue, {
'times_seen': 1,
}, {
'group_id': group.id,
'project_id': project_id,
'key': key,
'value': value,
}, {
'last_seen': date,
})
if tsdb_keys:
tsdb.incr_multi(tsdb_keys)示例9: _process_existing_aggregate
def _process_existing_aggregate(self, group, event, data, release):
date = max(event.datetime, group.last_seen)
extra = {"last_seen": date, "score": ScoreClause(group), "data": data["data"]}
if event.message and event.message != group.message:
extra["message"] = event.message
if group.level != data["level"]:
extra["level"] = data["level"]
if group.culprit != data["culprit"]:
extra["culprit"] = data["culprit"]
is_regression = self._handle_regression(group, event, release)
group.last_seen = extra["last_seen"]
update_kwargs = {"times_seen": 1}
buffer.incr(Group, update_kwargs, {"id": group.id}, extra)
return is_regression示例10: add_tags
def add_tags(self, group, tags):
from sentry.models import TagValue, GroupTagValue
project = group.project
date = group.last_seen
tsdb_keys = []
for tag_item in tags:
if len(tag_item) == 2:
(key, value), data = tag_item, None
else:
key, value, data = tag_item
if not value:
continue
value = six.text_type(value)
if len(value) > MAX_TAG_VALUE_LENGTH:
continue
tsdb_id = u"%s=%s" % (key, value)
tsdb_keys.extend([(tsdb.models.project_tag_value, tsdb_id)])
buffer.incr(
TagValue,
{"times_seen": 1},
{"project": project, "key": key, "value": value},
{"last_seen": date, "data": data},
)
buffer.incr(
GroupTagValue,
{"times_seen": 1},
{"group": group, "project": project, "key": key, "value": value},
{"last_seen": date},
)
if tsdb_keys:
tsdb.incr_multi(tsdb_keys)示例11: save
#.........这里部分代码省略.........
project=project, group=group, event_id=event_id)
except IntegrityError:
self.logger.info('duplicate.found', extra={'event_id': event.id}, exc_info=True)
return event
environment = Environment.get_or_create(
project=project,
name=environment,
)
if release:
ReleaseEnvironment.get_or_create(
project=project,
release=release,
environment=environment,
datetime=date,
)
grouprelease = GroupRelease.get_or_create(
group=group,
release=release,
environment=environment,
datetime=date,
)
counters = [
(tsdb.models.group, group.id),
(tsdb.models.project, project.id),
]
if release:
counters.append((tsdb.models.release, release.id))
tsdb.incr_multi(counters, timestamp=event.datetime)
frequencies = [
# (tsdb.models.frequent_projects_by_organization, {
# project.organization_id: {
# project.id: 1,
# },
# }),
# (tsdb.models.frequent_issues_by_project, {
# project.id: {
# group.id: 1,
# },
# })
(tsdb.models.frequent_environments_by_group, {
group.id: {
environment.id: 1,
},
})
]
if release:
frequencies.append(
(tsdb.models.frequent_releases_by_group, {
group.id: {
grouprelease.id: 1,
},
})
)
tsdb.record_frequency_multi(frequencies, timestamp=event.datetime)
UserReport.objects.filter(
project=project, event_id=event_id,示例12: save
#.........这里部分代码省略.........
hashes = [checksum]
else:
hashes = map(md5_from_hash, get_hashes_for_event(event))
group_kwargs = kwargs.copy()
group_kwargs.update({
'culprit': culprit,
'logger': logger_name,
'level': level,
'last_seen': date,
'first_seen': date,
'time_spent_total': time_spent or 0,
'time_spent_count': time_spent and 1 or 0,
})
if release:
release = Release.get_or_create(
project=project,
version=release,
date_added=date,
)
group_kwargs['first_release'] = release
Activity.objects.create(
type=Activity.RELEASE,
project=project,
ident=release,
data={'version': release},
datetime=date,
)
group, is_new, is_regression, is_sample = self._save_aggregate(
event=event,
hashes=hashes,
release=release,
**group_kwargs
)
event.group = group
event.group_id = group.id
# store a reference to the group id to guarantee validation of isolation
event.data.bind_ref(event)
try:
with transaction.atomic():
EventMapping.objects.create(
project=project, group=group, event_id=event_id)
except IntegrityError:
self.logger.info('Duplicate EventMapping found for event_id=%s', event_id)
return event
UserReport.objects.filter(
project=project, event_id=event_id,
).update(group=group)
# save the event unless its been sampled
if not is_sample:
try:
with transaction.atomic():
event.save()
except IntegrityError:
self.logger.info('Duplicate Event found for event_id=%s', event_id)
return event
if event_user:
tsdb.record_multi((
(tsdb.models.users_affected_by_group, group.id, (event_user.tag_value,)),
(tsdb.models.users_affected_by_project, project.id, (event_user.tag_value,)),
), timestamp=event.datetime)
if is_new and release:
buffer.incr(Release, {'new_groups': 1}, {
'id': release.id,
})
safe_execute(Group.objects.add_tags, group, tags,
_with_transaction=False)
if not raw:
if not project.first_event:
project.update(first_event=date)
post_process_group.delay(
group=group,
event=event,
is_new=is_new,
is_sample=is_sample,
is_regression=is_regression,
)
else:
self.logger.info('Raw event passed; skipping post process for event_id=%s', event_id)
index_event.delay(event)
# TODO: move this to the queue
if is_regression and not raw:
regression_signal.send_robust(sender=Group, instance=group)
return event示例13: save
#.........这里部分代码省略.........
"level": level,
"last_seen": date,
"first_seen": date,
"data": {
"last_received": event.data.get("received") or float(event.datetime.strftime("%s")),
"type": event_type.key,
# we cache the events metadata on the group to ensure its
# accessible in the stream
"metadata": event_metadata,
},
}
)
if release:
release = Release.get_or_create(project=project, version=release, date_added=date)
group_kwargs["first_release"] = release
group, is_new, is_regression, is_sample = self._save_aggregate(
event=event, hashes=hashes, release=release, **group_kwargs
)
event.group = group
# store a reference to the group id to guarantee validation of isolation
event.data.bind_ref(event)
try:
with transaction.atomic(using=router.db_for_write(EventMapping)):
EventMapping.objects.create(project=project, group=group, event_id=event_id)
except IntegrityError:
self.logger.info("Duplicate EventMapping found for event_id=%s", event_id, exc_info=True)
return event
if release:
grouprelease = GroupRelease.get_or_create(
group=group, release=release, environment=environment, datetime=date
)
tsdb.incr_multi([(tsdb.models.group, group.id), (tsdb.models.project, project.id)], timestamp=event.datetime)
frequencies = [
# (tsdb.models.frequent_projects_by_organization, {
# project.organization_id: {
# project.id: 1,
# },
# }),
# (tsdb.models.frequent_issues_by_project, {
# project.id: {
# group.id: 1,
# },
# })
]
if release:
frequencies.append((tsdb.models.frequent_releases_by_groups, {group.id: {grouprelease.id: 1}}))
tsdb.record_frequency_multi(frequencies, timestamp=event.datetime)
UserReport.objects.filter(project=project, event_id=event_id).update(group=group)
# save the event unless its been sampled
if not is_sample:
try:
with transaction.atomic(using=router.db_for_write(Event)):
event.save()
except IntegrityError:
self.logger.info("Duplicate Event found for event_id=%s", event_id, exc_info=True)
return event
index_event_tags.delay(project_id=project.id, group_id=group.id, event_id=event.id, tags=tags)
if event_user:
tsdb.record_multi(
(
(tsdb.models.users_affected_by_group, group.id, (event_user.tag_value,)),
(tsdb.models.users_affected_by_project, project.id, (event_user.tag_value,)),
),
timestamp=event.datetime,
)
if is_new and release:
buffer.incr(Release, {"new_groups": 1}, {"id": release.id})
safe_execute(Group.objects.add_tags, group, tags, _with_transaction=False)
if not raw:
if not project.first_event:
project.update(first_event=date)
first_event_received.send(project=project, group=group, sender=Project)
post_process_group.delay(
group=group, event=event, is_new=is_new, is_sample=is_sample, is_regression=is_regression
)
else:
self.logger.info("Raw event passed; skipping post process for event_id=%s", event_id)
# TODO: move this to the queue
if is_regression and not raw:
regression_signal.send_robust(sender=Group, instance=group)
return event示例14: save
#.........这里部分代码省略.........
group_kwargs = kwargs.copy()
group_kwargs.update({
'culprit': culprit,
'logger': logger_name,
'level': level,
'last_seen': date,
'first_seen': date,
'data': {
'last_received': event.data.get('received') or float(event.datetime.strftime('%s')),
'type': event_type.key,
# we cache the events metadata on the group to ensure its
# accessible in the stream
'metadata': event_metadata,
},
})
if release:
release = Release.get_or_create(
project=project,
version=release,
date_added=date,
)
group_kwargs['first_release'] = release
group, is_new, is_regression, is_sample = self._save_aggregate(
event=event,
hashes=hashes,
release=release,
**group_kwargs
)
event.group = group
# store a reference to the group id to guarantee validation of isolation
event.data.bind_ref(event)
try:
with transaction.atomic(using=router.db_for_write(EventMapping)):
EventMapping.objects.create(
project=project, group=group, event_id=event_id)
except IntegrityError:
self.logger.info('Duplicate EventMapping found for event_id=%s', event_id,
exc_info=True)
return event
UserReport.objects.filter(
project=project, event_id=event_id,
).update(group=group)
# save the event unless its been sampled
if not is_sample:
try:
with transaction.atomic(using=router.db_for_write(Event)):
event.save()
except IntegrityError:
self.logger.info('Duplicate Event found for event_id=%s', event_id,
exc_info=True)
return event
index_event_tags.delay(
project_id=project.id,
group_id=group.id,
event_id=event.id,
tags=tags,
)
if event_user:
tsdb.record_multi((
(tsdb.models.users_affected_by_group, group.id, (event_user.tag_value,)),
(tsdb.models.users_affected_by_project, project.id, (event_user.tag_value,)),
), timestamp=event.datetime)
if is_new and release:
buffer.incr(Release, {'new_groups': 1}, {
'id': release.id,
})
safe_execute(Group.objects.add_tags, group, tags,
_with_transaction=False)
if not raw:
if not project.first_event:
project.update(first_event=date)
first_event_received.send(project=project, group=group, sender=Project)
post_process_group.delay(
group=group,
event=event,
is_new=is_new,
is_sample=is_sample,
is_regression=is_regression,
)
else:
self.logger.info('Raw event passed; skipping post process for event_id=%s', event_id)
# TODO: move this to the queue
if is_regression and not raw:
regression_signal.send_robust(sender=Group, instance=group)
return event示例15: save
#.........这里部分代码省略.........
if added_tags:
tags.extend(added_tags)
# XXX(dcramer): we're relying on mutation of the data object to ensure
# this propagates into Event
data['tags'] = tags
# Calculate the checksum from the first highest scoring interface
if checksum:
hashes = [checksum]
elif fingerprint:
hashes = map(md5_from_hash, get_hashes_from_fingerprint(event, fingerprint))
else:
hashes = map(md5_from_hash, get_hashes_for_event(event))
group_kwargs = kwargs.copy()
group_kwargs.update({
'culprit': culprit,
'logger': logger_name,
'level': level,
'last_seen': date,
'first_seen': date,
'time_spent_total': time_spent or 0,
'time_spent_count': time_spent and 1 or 0,
})
if release:
release = Release.get_or_create(
project=project,
version=release,
date_added=date,
)
group_kwargs['first_release'] = release
Activity.objects.create(
type=Activity.RELEASE,
project=project,
ident=release,
data={'version': release},
datetime=date,
)
group, is_new, is_regression, is_sample = safe_execute(
self._save_aggregate,
event=event,
hashes=hashes,
**group_kwargs
)
using = group._state.db
event.group = group
try:
with transaction.atomic():
EventMapping.objects.create(
project=project, group=group, event_id=event_id)
except IntegrityError:
self.logger.info('Duplicate EventMapping found for event_id=%s', event_id)
return event
UserReport.objects.filter(
project=project, event_id=event_id,
).update(group=group)
# save the event unless its been sampled
if not is_sample:
try:
with transaction.atomic():
event.save()
except IntegrityError:
self.logger.info('Duplicate Event found for event_id=%s', event_id)
return event
if is_new and release:
buffer.incr(Release, {'new_groups': 1}, {
'id': release.id,
})
safe_execute(Group.objects.add_tags, group, tags,
_with_transaction=False)
if not raw:
post_process_group.delay(
group=group,
event=event,
is_new=is_new,
is_sample=is_sample,
is_regression=is_regression,
)
else:
self.logger.info('Raw event passed; skipping post process for event_id=%s', event_id)
index_event.delay(event)
# TODO: move this to the queue
if is_regression and not raw:
regression_signal.send_robust(sender=Group, instance=group)
return event