zulip/zerver/lib/utils.py

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# -*- coding: utf-8 -*-
from typing import Any, Callable, List, Optional, Sequence, TypeVar, Iterable, Set, Tuple, Text
import base64
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import errno
import hashlib
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import heapq
import itertools
import os
import sys
from time import sleep
from itertools import zip_longest
from django.conf import settings
T = TypeVar('T')
def statsd_key(val, clean_periods=False):
# type: (Any, bool) -> str
if not isinstance(val, str):
val = str(val)
if ':' in val:
val = val.split(':')[0]
val = val.replace('-', "_")
if clean_periods:
val = val.replace('.', '_')
return val
class StatsDWrapper:
"""Transparently either submit metrics to statsd
or do nothing without erroring out"""
# Backported support for gauge deltas
# as our statsd server supports them but supporting
# pystatsd is not released yet
def _our_gauge(self, stat, value, rate=1, delta=False):
# type: (str, float, float, bool) -> None
"""Set a gauge value."""
from django_statsd.clients import statsd
if delta:
value_str = '%+g|g' % (value,)
else:
value_str = '%g|g' % (value,)
statsd._send(stat, value_str, rate)
def __getattr__(self, name):
# type: (str) -> Any
# Hand off to statsd if we have it enabled
# otherwise do nothing
if name in ['timer', 'timing', 'incr', 'decr', 'gauge']:
if settings.STATSD_HOST != '':
from django_statsd.clients import statsd
if name == 'gauge':
return self._our_gauge
else:
return getattr(statsd, name)
else:
return lambda *args, **kwargs: None
raise AttributeError
statsd = StatsDWrapper()
# Runs the callback with slices of all_list of a given batch_size
def run_in_batches(all_list, batch_size, callback, sleep_time = 0, logger = None):
# type: (Sequence[T], int, Callable[[Sequence[T]], None], int, Optional[Callable[[str], None]]) -> None
if len(all_list) == 0:
return
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limit = (len(all_list) // batch_size) + 1
for i in range(limit):
start = i*batch_size
end = (i+1) * batch_size
if end >= len(all_list):
end = len(all_list)
batch = all_list[start:end]
if logger:
logger("Executing %s in batch %s of %s" % (end-start, i+1, limit))
callback(batch)
if i != limit - 1:
sleep(sleep_time)
def make_safe_digest(string, hash_func=hashlib.sha1):
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# type: (Text, Callable[[bytes], Any]) -> Text
"""
return a hex digest of `string`.
"""
# hashlib.sha1, md5, etc. expect bytes, so non-ASCII strings must
# be encoded.
return hash_func(string.encode('utf-8')).hexdigest()
def log_statsd_event(name):
# type: (str) -> None
"""
Sends a single event to statsd with the desired name and the current timestamp
This can be used to provide vertical lines in generated graphs,
for example when doing a prod deploy, bankruptcy request, or
other one-off events
Note that to draw this event as a vertical line in graphite
you can use the drawAsInfinite() command
"""
event_name = "events.%s" % (name,)
statsd.incr(event_name)
def generate_random_token(length):
# type: (int) -> str
return str(base64.b16encode(os.urandom(length // 2)).decode('utf-8').lower())
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def query_chunker(queries, id_collector=None, chunk_size=1000, db_chunk_size=None):
# type: (List[Any], Set[int], int, int) -> Iterable[Any]
'''
This merges one or more Django ascending-id queries into
a generator that returns chunks of chunk_size row objects
during each yield, preserving id order across all results..
Queries should satisfy these conditions:
- They should be Django filters.
- They should return Django objects with "id" attributes.
- They should be disjoint.
The generator also populates id_collector, which we use
internally to enforce unique ids, but which the caller
can pass in to us if they want the side effect of collecting
all ids.
'''
if db_chunk_size is None:
db_chunk_size = chunk_size // len(queries)
assert db_chunk_size >= 2
assert chunk_size >= 2
if id_collector is not None:
assert(len(id_collector) == 0)
else:
id_collector = set()
def chunkify(q, i):
# type: (Any, int) -> Iterable[Tuple[int, int, Any]]
q = q.order_by('id')
min_id = -1
while True:
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assert db_chunk_size is not None # Hint for mypy, but also workaround for mypy bug #3442.
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rows = list(q.filter(id__gt=min_id)[0:db_chunk_size])
if len(rows) == 0:
break
for row in rows:
yield (row.id, i, row)
min_id = rows[-1].id
iterators = [chunkify(q, i) for i, q in enumerate(queries)]
merged_query = heapq.merge(*iterators)
while True:
tup_chunk = list(itertools.islice(merged_query, 0, chunk_size))
if len(tup_chunk) == 0:
break
# Do duplicate-id management here.
tup_ids = set([tup[0] for tup in tup_chunk])
assert len(tup_ids) == len(tup_chunk)
assert len(tup_ids.intersection(id_collector)) == 0
id_collector.update(tup_ids)
yield [row for row_id, i, row in tup_chunk]
def split_by(array, group_size, filler):
# type: (List[Any], int, Any) -> List[List[Any]]
"""
Group elements into list of size `group_size` and fill empty cells with
`filler`. Recipe from https://docs.python.org/3/library/itertools.html
"""
args = [iter(array)] * group_size
return list(map(list, zip_longest(*args, fillvalue=filler)))
def is_remote_server(identifier):
# type: (Text) -> bool
"""
This function can be used to identify the source of API auth
request. We can have two types of sources, Remote Zulip Servers
and UserProfiles.
"""
return "@" not in identifier