rq-dashboard is a general purpose, lightweight, Flask-based web
front-end to monitor your RQ queues, jobs, and workers in realtime.
$ pip install rq-dashboardRun the dashboard standalone, like this:
$ rq-dashboard
* Running on http://127.0.0.1:9181/
...$ rq-dashboard --help
Usage: rq-dashboard [OPTIONS]
Run the RQ Dashboard Flask server.
All configuration can be set on the command line or through environment
variables of the form RQ_DASHBOARD_*. For example RQ_DASHBOARD_USERNAME.
A subset of the configuration (the configuration parameters used by the
underlying flask blueprint) can also be provided in a Python module
referenced using --config, or with a .cfg file referenced by the
RQ_DASHBOARD_SETTINGS environment variable.
Options:
-b, --bind TEXT IP or hostname on which to bind HTTP server
-p, --port INTEGER Port on which to bind HTTP server
--url-prefix TEXT URL prefix e.g. for use behind a reverse proxy
--username TEXT HTTP Basic Auth username (not used if not set)
--password TEXT HTTP Basic Auth password
-c, --config TEXT Configuration file (Python module on search
path)
-H, --redis-host TEXT IP address or hostname of Redis server
-P, --redis-port INTEGER Port of Redis server
--redis-password TEXT Password for Redis server
-D, --redis-database INTEGER Database of Redis server
-u, --redis-url TEXT Redis URL connection (overrides other
individual settings)
--interval INTEGER Refresh interval in ms
--help Show this message and exit.The dashboard can be integrated in to your own Flask app by accessing the blueprint directly in the normal way, e.g.:
from flask import Flask
import rq_dashboard
app = Flask(__name__)
app.config.from_object(rq_dashboard.default_settings)
app.register_blueprint(rq_dashboard.blueprint)
@app.route("/")
def hello():
return "Hello World!"
if __name__ == "__main__":
app.run()The cli.py:main entry point provides a simple working example.
We use piptools to keep our development dependencies up to date
$ pip install --upgrade pip $ pip install git+https://github.com/nvie/pip-tools.git@future
Now make changes to the requirements.in file, and resolve all the
2nd-level dependencies into requirements.txt like so:
$ pip-compile --annotate requirements.in
Develop in a virtualenv and make sure you have all the necessary build time (and run time) dependencies with
$ pip install -r requirements.txt
Develop in the normal way with
$ python setup.py develop
Then use Fabric to perform various development tasks. For example, to tag, build and upload to testpypi
$ git tag 0.3.5 # no 'v' prefix or anything $ fab build $ fab upload
This requires write access to both the GitHub repo and to the PyPI test site.
See fab -l for more options and fab -d <subcommand> for details.
The RQ dashboard is currently being developed and is in beta stage.
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