vcsserver/lib/_vendor/statsd/base.py

from __future__ import absolute_import, division, unicode_literals

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 xrange(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)