https://github.com/metricq/metricq-python
🐍 The MetricQ Python interface
https://github.com/metricq/metricq-python
library metricq python
Last synced: 10 months ago
JSON representation
🐍 The MetricQ Python interface
- Host: GitHub
- URL: https://github.com/metricq/metricq-python
- Owner: metricq
- License: bsd-3-clause
- Created: 2020-04-17T12:37:55.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2025-02-12T21:55:20.000Z (12 months ago)
- Last Synced: 2025-03-27T21:11:10.447Z (10 months ago)
- Topics: library, metricq, python
- Language: Python
- Homepage: https://metricq.github.io/metricq-python/
- Size: 27.6 MB
- Stars: 18
- Watchers: 5
- Forks: 7
- Open Issues: 15
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
Awesome Lists containing this project
README
[](https://pypi.org/project/metricq/)
[](https://hub.docker.com/r/metricq/metricq-python)
[](https://metricq.github.io/metricq-python/)
# metricq - python libraries
This is a python implementation of the MetricQ protocol.
It allows you to write Sources and Sinks to easily send and receive data over
the MetricQ infrastructure.
## Installation
Install the package from PyPI:
```sh
$ pip install metricq
```
## Examples
The [`examples`](/tree/master/examples/) directory contains some basic
examples.
To play around with them, check out a copy of this repository and (in your
favourite venv) install their dependencies:
```sh
$ pip install -e '.[examples]'
```
A simple Source is implemented in `metricq_source.py`, as is a Sink in `metricq_sink.py`.
We will use the former to produce data for a metric called `test.py.dummy`, which we
will then receive and print with the latter.
Assuming a MetricQ instance is reachable at `localhost`, configure a
client(consult the documentation of your favourite config provider on how
to do that) named `source-py-dummy` to produce values with a frequency of
0.5Hz (i.e. every 2 seconds) :
```json
{
"rate": 0.5
}
```
To start the Source, run:
```sh
$ ./examples/metricq_source.py --server 'amqp://localhost/' --token 'source-py-dummy'
```
This should now send values for the metric `test.py.dummy` in 2-second intervals.
To see (in detail) what's going on, add `-v DEBUG` to the arguments above.
On the other side, run
```sh
$ ./examples/metricq_sink.py --server 'amqp://localhost/' --metrics 'test.py.dummy'
```
and you should see new values for the metric `test.py.dummy` appear every 2 seconds.
## Tools and utility scripts
The repository [metricq/metricq-tools](https://github.com/metricq/metricq-tools)
contains a collection of tools and utility scripts to monitor and administrate
a MetricQ network.
Install them from [PyPI](https://pypi.org/project/metricq-tools/):
```
$ pip install metricq-tools
```
## Development setup
Clone the repository, and in a virtual environment run
```sh
$ pip install -e '.[dev]'
```
This will install all tools necessary for testing and linting.
To test code manually, run `pytest`.
Format code using `black` and `isort`, or lint with `flake8`.
To make sure a source distribution (`sdist`) contains the correct files, run `check-manifest`.
Tools are configured in `setup.cfg` respectively `pyproject.toml`.
To test code in a fresh environment, run the `tox` test harness:
```sh
$ tox
```
This runs the same step as our CI does.
If `tox` passes locally there's high chances that CI steps will pass too.
We recommend to install our [pre-commit](https://pre-commit.com) hooks:
```sh
$ pre-commit install
```
This way commits that fail tests or do not comply with our code style are rejected right away.