Timing Helpers

Classes to help measure time and send metrics.Timer metrics using any client.

client.timing – Timing helpers

class client.timing.Chronometer(client, rate=1)

Chronometer calculates duration (of function calls, etc.) and sends them with provided metric names. Normally these is no need to instantiate this class directly, but you can call client.Client.chronometer() on any client, to get a configured Chronometer.

client

The client used to send the timing metrics. This can be any client from client package.

rate

the default sample rate for metrics to send. Should be a float between 0 and 1. This is the same as used in all clients.

since(name, timestamp, rate=None)

Calculate the time passed since the given timestamp, and send a Timer metric with the provided name. The timestamp can be a float (seconds passed from epoch, as returned by time.time(), or a datetime.datetime instance. Rate is the sample rate to use, or None to use the default sample rate of the Chronometer.

time_callable(name, target, rate=None, args=(), kwargs={})

Calculate the time it takes to run the callable target (with provided args and kwargs) and send the a Timer metric with the specific name. Rate is the sample rate to use, or None to use the default sample rate of the Chronometer.

wrap(name, rate=None)

Used as a function decorator, to calculate the time it takes to run the decorated function, and send a Timer metric with the specified name. Rate is the sample rate to use, or None to use the default sample rate of the Chronometer.

Examples

from time import time, sleep
from statsdmetrics.client import Client
from statsdmetrics.client.timing import Chronometer

start_time = time()
client = Client("stats.example.org")
chronometer = Chronometer(client)
chronometer.since("instantiate", start_time)

def wait(secs):
    sleep(secs) # or any timed operation

chronometer.time_callable("waited", wait, args=(0.56,))

@chronometer.wrap("wait_decorated")
def another_wait(secs):
    sleep(secs) # or any timed operation

another_wait(0.23) # sends the "wait_decorated" Timer metric
chronometer.since("overall", start_time)

If a batch client (like client.BatchClient or client.tcp.TCPBatchClient) is used, then the behavior of the client requires an explicit flush() call.

from datetime import datetime
from statsdmetrics.client.tcp import TCPBatchCPClient
from statsdmetrics.client.timing import Chronometer

start_time = datetime.now()
client = TCPBatchClient("stats.example.org")
chronometer = Chronometer(client)
chronometer.since("instantiate", start_time)

def wait_with_kwargs(name, key=val):
    sleep(1) # or any timed operation

chronometer.time_callable("waited", wait_with_kwargs, kwargs=dict(name="foo", key="bar"))
client.flush()

class client.timing.Stopwatch(client, name, rate=1, reference=None)

Stopwatch calculates duration passed from a given reference time (by default uses the instantiation time) for a specific metric name. So time passed since the reference time can be sent multiple times. Normally these is no need to instantiate this class directly, but you can call client.Client.stopwatch() on any client, to get a configured Chronometer.

client

The client used to send the timing metrics. This can be any client from client package.

name

The name for the metric sent by the stopwatch.

rate

The default sample rate for metrics to send. Should be a float between 0 and 1. This is the same as used in all clients.

reference

The time reference that duration is calculated from. It’s a float value of seconds passed since epoch, same as time.time().

reset()

Reset the stopwatch, updating the reference with current time. Returns a self reference for method chaining.

send(rate=None)

Calculate time passed since reference and send the metric. A sampling rate can be specified, or None (default) uses the default sampling rate of the stopwatch. Returns a self reference for method chaining.

Examples

from time import time, sleep
from statsdmetrics.client import Client
from statsdmetrics.client.timing import Stopwatch

start_time = time()
client = Client("stats.example.org")
stopwatch = Stopwatch(client, "process", start_time)

sleep(2) # do stuff
stopwatch.send()
sleep(1) # do other stuff
stopwatch.send()

If a batch client (like client.BatchClient or client.tcp.TCPBatchClient) is used, then the behavior of the client requires an explicit flush() call.

from datetime import datetime
from statsdmetrics.client.tcp import TCPBatchCPClient
from statsdmetrics.client.timing import Stopwatch

start_time = time()
client = TCPBatchClient("stats.example.org")
stopwatch = Stopwatch(client, "process", start_time)

sleep(3) # do stuff
stopwatch.send()
sleep(1) # do other stuff
stopwatch.send()

client.flush()

Stopwatch is a context manager, so can be used to measure duration of a with block

from time import time, sleep
from statsdmetrics.client import Client
from statsdmetrics.client.timing import Stopwatch

client = Client("stats.example.org")
with client.stopwatch("some_block"):
    sleep(3) # do stuff in the context

# now a Timer metric named "some_block" is sent, whose value is the duration of the block