speedtest-plotter

This is a collection of scripts, which takes internet speedtest measurements against the speedtest.net network with taganaka/SpeedTest and plots them with gnuplot. A crontab schedule is used to automate measurements every couple of minutes and save them to a database. The results can be displayed through a simple Flask webserver.

USAGE

CONTAINER

The main distribution method is the automatically built container at ansemjo/speedtest. Obviously, you need to have a container runtime like docker or podman installed to run the container.

To start the container with default settings run:

docker run -d -p 8000:8000 ansemjo/speedtest

This will take a measurement every 15 minutes, save them to a SQLite database in /data/speedtests.db and run the webserver on port 8000. Visit http://localhost:8000 to look at the plotted results. (Note: The smoothed bezier curves require at least two measurements and the image will stay blank otherwise. So you might have to wait a while first.)

Your local timezone can be set with the TZ environment variable and a string from tzselect. If none is set usually UTC is assumed. For example users in Japan should use:

docker run -d -p 8000:8000 -e TZ=Asia/Tokyo ansemjo/speedtest

For data persistence, either mount a volume at /data to save the database file or set the environment variable DATABASE to an SQLAlchemy-compatible URI. A PostgreSQL URI might look like this:

docker run -d \
  -p 8000:8000 \
  -e TZ=Europe/Berlin \
  -e DATABASE=postgresql://user:password@hostname:5432/database' \
  ansemjo/speedtest

You can modify the measurement schedule with the environment variables MINUTES and SCHEDULE. The former takes a measurement every n minutes and the latter may define an entirely custom cron schedule like "four times a day":

docker run -d -p 8000:8000 -e SCHEDULE="0 3,9,15,21 * * *" ansemjo/speedtest

To add horizontal dashed lines in the plot (e.g. to mark your expected bandwidths) you can use environment variables MARKER_DOWNLOAD and MARKER_UPLOAD. The values are given in MBit/s.

In addition or independently from that you can also set a range scaling for the upload plot relative to the download range with UPLOAD_SCALE. For highly asymmetrical connections this makes it easier to see the upload bandwidth. For example, the above example picture was created with:

docker run -d \
  [...] \
  -e MARKER_DOWNLOAD=800 \
  -e MARKER_UPLOAD=40 \
  -e UPLOAD_SCALE=10 \
  ansemjo/speedtest

The webserver is a single-threaded Flask application and pipes the data to gnuplot in a subprocess, which may not be suitable for production usage. To disable the webserver completely set the PORT environment variable to an empty string. This will only take measurements and save them to the database.

docker run -d -e PORT="" -v speedtests:/data ansemjo/speedtest

To dump the results as CSV from a running container use the dump command:

docker exec $containerid dump > results.csv

To trigger a measurement manually use the measure command:

docker exec $containerid measure

To reimport a previous dump in a fresh container use import:

docker exec $containerid import < results.csv

This can also be used to import results obtained manually with speedtest-cli.

PYTHON SCRIPT

You can use the Python script by itself locally, too. First install the requirements:

pip install -r requirements.txt

Choose a database location and take any number of measurements:

./speedtest-plotter -d sqlite:///$PWD/measurements.db measure
...

Then start the flask webserver to look at the results:

TZ=Europe/Berlin ./speedtest-plotter -d sqlite:///$PWD/measurements.db serve

GNUPLOT SCRIPT

To keep things really simple, you can also take measurements manually with speedtest-cli and only plot an image with gnuplot.

The plotscript expects the format that speedtest-cli outputs when using the --csv flag and a header line from --csv-header. To take some measurements manually with a simple sleep-loop:

speedtest-cli --csv-header > results.csv
while true; do speedtest-cli --csv | tee -a results.csv; sleep 600; done
^C

Afterwards plot the results to an SVG picture with:

gnuplot -c plotscript results.csv plot.svg

LICENSE

Copyright (c) 2019 Anton Semjonov Licensed under the MIT License