Cares about your project metrics

Metric-Farmer is a Python based command line application to collect and store metrics from different sources to different targets.

It is designed to easily create and maintain complex metric measurements and to painless integrate its functions into continuous integration systems (CI/CD) or local task executions (cron jobs).

The configuration is completely done by JSON-based farm-files in a project folder called .farmer. And no development skills are needed to use Metric-Farmer.

Developers can easily create own Metric-Farmer extensions to provide custom solutions for sources and targets. For instance to measure a company-internal service.


Metric-Farmer is capable to collect metrics from following Sources:

And sends the results to the following Targets:


skinparam defaultTextAlignment center
left to right direction

skinparam cloud {
   FontColor #fff
   Backgroundcolor #483e37

node "**User**\ndefines metrics\n in //.farm files//" as dm #ffcc00
node "**User/CI**\nexecutes Metric-Farmer" as em #ffcc00

node "**Metric-Farmer**\nprepares measurments\nbased on //.farm files// " as pm #abc837
node "**Metric-Farmer**\nmeasures metrics\n from  //sources// " as mm #abc837
node "**Metric-Farmer**\nstores results\n on //targets//" as sr #abc837
node "**User**\nanalyses results" as ar_user #ffcc00
node "**CI**\nanalyses results" as ar_ci #ffcc00

artifact ".farm files" as ff #ffcc00

cloud "Source A" as src_a
cloud "Source B" as src_b

cloud "Target A" as target_a
cloud "Target B" as target_b

dm --> ff
ff --> pm
em -> pm

pm -> mm
mm -> sr

src_a --> mm
src_b --> mm

sr --> target_a
sr --> target_b

target_a --> ar_user
target_b --> ar_ci


Quick start


You need to have an installed Python 3.5 or above environment.

Then install Metric-Farmer by executing pip install metricfarmer. A working internet connection is needed!

First measurements

Execute metricfarmer by following command on your command prompt:


You will see that extensions and configurations got loaded, but no metrics have been measured. That’s because you haven’t defined them yet.

Luckily Metric-Farmer comes with some metric examples, which can be used by asking for all metrics with the tag mf_examples.

So simply execute:

metricfarmer --tags mf_examples print

print is a predefined target and prints out the results of all measured metrics.

Playing with targets

Targets define what shall happen with the measured metric results.

A very basic target is the print target. Other predefined targets are print_json, file_text and file_json.

You are free to combine them during your call:

metricfarmer -t mf_examples print file_json

-t is an abbreviation of --tags and file_json will print the results in a file called metric_results.json on your current working directory.

Take a look into Targets to know how to define easily own, custom targets for your special use cases.

Knowing what is possible

To get a list of all available metrics, tags, sources, targets and more, simply execute:

metricfarmer --list

Own metrics

Metric-Farmer is controlled completely by file-based configurations. Therefore it looks for .farm files at the following locations:

  1. Metric-Farmer installation folder (for basic and example configs)
  2. .farmer folder in user/home directory (e.g. ~/.farmer)
  3. .farmer folder in current working directory (normally your project root)

Metric-Farmer reads in all found .farm-files and combines them to a single configuration object.

Later read configuration parameters overrides previous read configurations. So a project-configuration overrides always configurations coming from the user/home folder.

For a simple example, execute the following steps:

  1. Create a folder .farmer on your project root folder
  2. Create a file inside .farmer called
  3. Add the following content to the file:
   "metrics": {
      "my_metric": {
         "source": {
            "type": "random",
  1. On your project root level execute metricfarmer print.

Congratulations, you have created and measured your first own metric. As we have used the predefined random source-type, new measurements should provide random numbers as result.

Metric-Farmer provides the following predefined source types: static, random and file_count

Take a look into Sources to get details about them or to get information about how to define your own source types for your special needs.


Metric-Farmer is based on the needs of a software development team inside a german automotive company.

The project team was searching for a small and practical way of measuring and analysing metrics related to the ISO 26262 standard for safety critical software.

Metric-Farmer is part of a software bundle, which was designed to support the development of ISO 26262 compliant software. Other tools are: sphinx-needs, sphinx-test-reports and tox-envreport.