py-timeexecution 1.2.0

Python project

Features

• Sending data to multiple backends

• Custom backends

• Hooks

Backends

• InfluxDB 0.8

Installation

$ pip install py-timeexecution

Usage

To use this package you decorate the functions you want to time its execution. Every wrapped function will create a metric consisting of 3 default values:

• name - The name of the series the metric will be stored in

• value - The time it took in ms for the wrapped function to complete

• hostname - The hostname of the machine the code is running on

See the following example

from time_execution import configure, time_execution
from time_execution.backends.influxdb import InfluxBackend

# Setup the desired backend
influx = InfluxBackend(host='localhost', database='metrics', use_udp=False)

# Configure the time_execution decorator
configure(backends=[influx])

# Wrap the methods where u want the metrics
@time_execution
def hello():
    return 'World'

# Now when we call hello() and we will get metrics in our backends
hello()

This will result in an entry in the influxdb

[
    {
        "name": "__main__.hello",
        "columns": [
            "time",
            "sequence_number",
            "value",
            "hostname",
        ],
        "points": [
            [
                1449739813939,
                1111950001,
                312,
                "machine.name",
            ]
        ]
    }
]

Hooks

time_execution supports hooks where you can change the metric before its being send to the backend.

With a hook you can add additional and change existing fields. This can be useful for cases where you would like to add a column to the metric based on the response of the wrapped function.

A hook will always get 3 arguments:

• response - The returned value of the wrapped function

• exception - The raised exception of the wrapped function

• metric - A dict containing the data to be send to the backend

From within a hook you can change the name if you want the metrics to be split into multiple series.

See the following example how to setup hooks.

# Now lets create a hook
def my_hook(response, exception, metric):
    status_code = getattr(response, 'status_code', None)
    if status_code:
        return dict(
            name='{}.{}'.format(metric['name'], status_code),
            extra_field='foo bar'
        )

# Configure the time_execution decorator, but now with hooks
configure(backends=[influx], hooks=[my_hook])

Manually sending metrics

You can also send any metric you have manually to the backend. These will not add the default values and will not hit the hooks.

See the following example.

loadavg = os.getloadavg()
write_metric('cpu.load.1m', value=loadavg[0])
write_metric('cpu.load.5m', value=loadavg[1])
write_metric('cpu.load.15m', value=loadavg[2])