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Project description
mbq.metrics: metrics for the masses
===================================
.. image:: https://img.shields.io/pypi/v/mbq.metrics.svg
:target: https://pypi.python.org/pypi/mbq.metrics
.. image:: https://img.shields.io/pypi/l/mbq.metrics.svg
:target: https://pypi.python.org/pypi/mbq.metrics
.. image:: https://img.shields.io/pypi/pyversions/mbq.metrics.svg
:target: https://pypi.python.org/pypi/mbq.metrics
.. image:: https://img.shields.io/travis/managedbyq/mbq.metrics/master.svg
:target: https://travis-ci.org/managedbyq/mbq.metrics
Installation
------------
.. code-block:: bash
$ pip install mbq.metrics
🚀✨
Guaranteed fresh.
Getting started
---------------
.. code-block:: python
from mbq import metrics
metrics.init(namespace='my-service', constant_tags={'env': ENV_NAME})
metrics.increment('metric.name', 5, tags={'something': 'awesome'})
# show the rest
Testing
-------
We now use `tox` for local testing across multiple python environments. Before this use `pyenv` to install the following python interpreters: cpython{2.7, 3.5, 3.6} and pypy3
install and run tox:
.. code-block:: bash
$ pip install tox
$ tox
$
$ # run a specific environment
$ tox -e py36-django111
$
FAQs
----
**Where do I put the DogStatsd agent configuration?**
You don't! ``mbq.metrics`` is pre-baked with assumptions about how Q runs it's services. Specifically, we assume that each service runs in a Docker container and that that container is running on a VM that's running the DogStatsD agent. In that way we can automatically configure our client to reach outside of the container and easily push metrics to the agent.
Read more in the `datadogpy documentation <http://datadogpy.readthedocs.io/en/latest/index.html#datadog.initialize>`_ or `in the source <https://github.com/DataDog/datadogpy/blob/fd6646a6e8cde1d7a8c2f6e324d04e8d7f8a6f8c/datadog/dogstatsd/route.py#L15>`_.
API Reference
-------------
Contributing
------------
===================================
.. image:: https://img.shields.io/pypi/v/mbq.metrics.svg
:target: https://pypi.python.org/pypi/mbq.metrics
.. image:: https://img.shields.io/pypi/l/mbq.metrics.svg
:target: https://pypi.python.org/pypi/mbq.metrics
.. image:: https://img.shields.io/pypi/pyversions/mbq.metrics.svg
:target: https://pypi.python.org/pypi/mbq.metrics
.. image:: https://img.shields.io/travis/managedbyq/mbq.metrics/master.svg
:target: https://travis-ci.org/managedbyq/mbq.metrics
Installation
------------
.. code-block:: bash
$ pip install mbq.metrics
🚀✨
Guaranteed fresh.
Getting started
---------------
.. code-block:: python
from mbq import metrics
metrics.init(namespace='my-service', constant_tags={'env': ENV_NAME})
metrics.increment('metric.name', 5, tags={'something': 'awesome'})
# show the rest
Testing
-------
We now use `tox` for local testing across multiple python environments. Before this use `pyenv` to install the following python interpreters: cpython{2.7, 3.5, 3.6} and pypy3
install and run tox:
.. code-block:: bash
$ pip install tox
$ tox
$
$ # run a specific environment
$ tox -e py36-django111
$
FAQs
----
**Where do I put the DogStatsd agent configuration?**
You don't! ``mbq.metrics`` is pre-baked with assumptions about how Q runs it's services. Specifically, we assume that each service runs in a Docker container and that that container is running on a VM that's running the DogStatsD agent. In that way we can automatically configure our client to reach outside of the container and easily push metrics to the agent.
Read more in the `datadogpy documentation <http://datadogpy.readthedocs.io/en/latest/index.html#datadog.initialize>`_ or `in the source <https://github.com/DataDog/datadogpy/blob/fd6646a6e8cde1d7a8c2f6e324d04e8d7f8a6f8c/datadog/dogstatsd/route.py#L15>`_.
API Reference
-------------
Contributing
------------
Project details
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