This visualization produces a calendar of project activity over time, similar to developer activity overviews in GitHub and GitLab. This includes statistics per day on number of commits, commits per developer, temperature, and changes to file that have not been changed since a long time. Some statistics are optional.
Copy the file lib/config.json to config.json and adjust environmental
settings in that file. The following configuration items are known:
visualization_url: The URL to the visualization hub. This may include a protocol and domain name, but does not need to in case all the visualizations and the heatmap are hosted on the same domain (for example in a development environment). The remainder is a path to the root of the visualizations, where the dashboard is found and every other visualization has sub-paths below it. The URL may contain the$organizationvariable, which is replaced by the$VISUALIZATION_ORGANIZATIONenvironment variable upon compilation.path: The relative path at which the heatmap is made available on the server. This can remain the default.to work just fine.
The data for the sprint report can be analyzed and output through runs of
scripts from the data-analysis repository upon a collection of Scrum data in
a Grip on Software database as well as external weather data. The
commit_volume and developers analysis reports as well as the weather.r
script in the repository export data in JSON formats that is expected by the
heatmap (for an example, see the Collect step in the Jenkinsfile). Note
that one can also include temperature data from other sources than this script
(which may be specific to certain data providers and data formats). The only
requirement is that the weather.json data file, if available, contains a JSON
object where the keys are dates in ISO 8601 format and the values are
temperature values (assumed to be in degrees Celsius by the locale). If the
weather.json file is not available, then turning on temperature bars is
disabled in the visualization. The entire data collection must be placed in the
public/data directory.
Aside from the two analysis reports mentioned above, the long_waiting_commits
report should also provide per-project JSON files within a subdirectory of the
same name, unless the $VISUALIZATION_ANONYMIZED environment variable is set
to true. In that case, the option to view file changes is disabled.
The visualization can be built using Node.js and npm by running npm install
and then either npm run watch to start a development server that also
refreshes browsers upon code changes, or npm run production to create
a minimized bundle. The resulting HTML, CSS and JavaScript is made available in
the public directory.
This repository also contains a Dockerfile specification for a Docker image
that can perform the installation of the app and dependencies, which allows
building the visualization within there. The Jenkinsfile contains appropriate
steps for a Jenkins CI deployment, including data collection and visualization
building.