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base.py
156 lines | 4.2 KiB | text/x-python | PythonLexer
import re
import random
from collections import deque
from datetime import timedelta
from repoze.lru import lru_cache
from .timer import Timer
TAG_INVALID_CHARS_RE = re.compile(
r"[^\w\d_\-:/\.]",
#re.UNICODE
)
TAG_INVALID_CHARS_SUBS = "_"
# we save and expose methods called by statsd for discovery
buckets_dict = {
}
@lru_cache(maxsize=500)
def _normalize_tags_with_cache(tag_list):
return [TAG_INVALID_CHARS_RE.sub(TAG_INVALID_CHARS_SUBS, tag) for tag in tag_list]
def normalize_tags(tag_list):
# We have to turn our input tag list into a non-mutable tuple for it to
# be hashable (and thus usable) by the @lru_cache decorator.
return _normalize_tags_with_cache(tuple(tag_list))
class StatsClientBase(object):
"""A Base class for various statsd clients."""
def close(self):
"""Used to close and clean up any underlying resources."""
raise NotImplementedError()
def _send(self):
raise NotImplementedError()
def pipeline(self):
raise NotImplementedError()
def timer(self, stat, rate=1, tags=None, auto_send=True):
"""
statsd = StatsdClient.statsd
with statsd.timer('bucket_name', auto_send=True) as tmr:
# This block will be timed.
for i in range(0, 100000):
i ** 2
# you can access time here...
elapsed_ms = tmr.ms
"""
return Timer(self, stat, rate, tags, auto_send=auto_send)
def timing(self, stat, delta, rate=1, tags=None, use_decimals=True):
"""
Send new timing information.
`delta` can be either a number of milliseconds or a timedelta.
"""
if isinstance(delta, timedelta):
# Convert timedelta to number of milliseconds.
delta = delta.total_seconds() * 1000.
if use_decimals:
fmt = '%0.6f|ms'
else:
fmt = '%s|ms'
self._send_stat(stat, fmt % delta, rate, tags)
def incr(self, stat, count=1, rate=1, tags=None):
"""Increment a stat by `count`."""
self._send_stat(stat, '%s|c' % count, rate, tags)
def decr(self, stat, count=1, rate=1, tags=None):
"""Decrement a stat by `count`."""
self.incr(stat, -count, rate, tags)
def gauge(self, stat, value, rate=1, delta=False, tags=None):
"""Set a gauge value."""
if value < 0 and not delta:
if rate < 1:
if random.random() > rate:
return
with self.pipeline() as pipe:
pipe._send_stat(stat, '0|g', 1)
pipe._send_stat(stat, '%s|g' % value, 1)
else:
prefix = '+' if delta and value >= 0 else ''
self._send_stat(stat, '%s%s|g' % (prefix, value), rate, tags)
def set(self, stat, value, rate=1):
"""Set a set value."""
self._send_stat(stat, '%s|s' % value, rate)
def histogram(self, stat, value, rate=1, tags=None):
"""Set a histogram"""
self._send_stat(stat, '%s|h' % value, rate, tags)
def _send_stat(self, stat, value, rate, tags=None):
self._after(self._prepare(stat, value, rate, tags))
def _prepare(self, stat, value, rate, tags=None):
global buckets_dict
buckets_dict[stat] = 1
if rate < 1:
if random.random() > rate:
return
value = '%s|@%s' % (value, rate)
if self._prefix:
stat = '%s.%s' % (self._prefix, stat)
res = '%s:%s%s' % (
stat,
value,
("|#" + ",".join(normalize_tags(tags))) if tags else "",
)
return res
def _after(self, data):
if data:
self._send(data)
class PipelineBase(StatsClientBase):
def __init__(self, client):
self._client = client
self._prefix = client._prefix
self._stats = deque()
def _send(self):
raise NotImplementedError()
def _after(self, data):
if data is not None:
self._stats.append(data)
def __enter__(self):
return self
def __exit__(self, typ, value, tb):
self.send()
def send(self):
if not self._stats:
return
self._send()
def pipeline(self):
return self.__class__(self)