Package: cimetrics
cimetricscimetricslets you track crucial metrics to avoid unwanted regressions. It is easy to integrate with your existing projects and automatically provides quick feedback in your GitHub Pull Requests. See it in actionhere.InstallpipinstallcimetricsUsing cimetricsSetup storageMetrics data are stored in any MongoDB-compatible database.An easy way to get storage set up is to spin up aCosmos DBinstance in Azure. The connection string should be stored as theMETRICS_MONGO_CONNECTIONsecret variable in your CI system.Pushing metrics from your testsYou can use the simple Python API to push your metrics to your storage:importcimetrics.uploadwithcimetrics.upload.metrics()asmetrics:# Run some tests and collect some datametrics.put("metric1 name (unit)",metric_1)metrics.put("metric2 name (unit)",metric_2)Note thatmetric_1andmetric_2must be instances ofnumbers.Real, for examplefloatorint.If a build publishes metrics from multiple instances of acimetrics.upload.Metrics, for example because
it is running multiple concurrent jobs, it it necessary to publish those as "incomplete",
and to publish a "complete" entry only once they have all run. This is to prevent metrics comparison from
happening against an incomplete set of metrics for a build.For example:# Job 1withcimetrics.upload.metrics(complete=False)asmetrics:metrics.put("metric1 name (unit)",metric_1)# Job 2withcimetrics.upload.metrics(complete=False)asmetrics:metrics.put("metric2 name (unit)",metric_2)# Job running after Job 1 and 2 are completewithcimetrics.upload.metrics()asmetrics:passIt is often convenient to use the same job to mark a set of metrics as complete and to plot them.
A convenience entry-point is supplied to mark the metrics complete for a build:python-mcimetrics.upload_completeSetup the CIYour CI is responsible for rendering the metrics report and posting them to your Pull Requests in GitHub. For this, you should create apersonal authentication tokenwith Write access to the repository for the account you want to post on behalf ofcimetrics. Then, you should set up the token as theGITHUB_TOKENsecret variable in your CI system. Don't forget to add that user as a personal contributor (Write access) to your Github repository as well.Then, you should add the following steps to your CI configuration file, e.g. for Azure Pipelines:# Your application. This step collects and uploads your metrics# to your MongoDB instance.-script:python app/main.pyenv:METRICS_MONGO_CONNECTION:$(METRICS_MONGO_CONNECTION)displayName:'Runappandcollectmetrics'# This step generates a graph reporting the differences between# your branch and the target branch.# Only run on Pull Requests build.-script:python -m cimetrics.plotenv:METRICS_MONGO_CONNECTION:$(METRICS_MONGO_CONNECTION)displayName:'Plotmetrics'condition:eq(variables['Build.Reason'], 'PullRequest')# This step publishes a report comment on the GitHub Pull Request# using GITHUB_TOKEN as authentication (use secret variables!)# Only run on Pull Requests build.-script:python -m cimetrics.github_prenv:GITHUB_TOKEN:$(GITHUB_TOKEN)displayName:'PostmetricsgraphsasPRcomment'condition:eq(variables['Build.Reason'], 'PullRequest')Seeazure-pipelines.ymlfor a full working example.Create themetrics.ymlfileThe last step is to create a newmetrics.ymlconfiguration file at the root of your repository. The file should specify the name of the database and collection used for MongoDB. For example:db:'metrics'collection:'metrics_performance'That's it! The next time you create a Pull Request, your CI will automatically store your metrics and publish a graph comparing your metrics against the same metrics on the branch you are merging to. Note that the cimetrics PR comment is updated for each subsequent build.CaveatsIf the CI has never run on the target branch (e.g.main- likely to happen when you first set upcimetrics), the report will only show the values that have been uploaded, without any comparison.The rendered images are currently hosted in the target GitHub repository itself, under thecimetricsbranch, in thecimetricsdirectory.Supported CI pipelinesCI Metrics currently supportsAzure Pipelines, but it should be very easy to add support for other build pipelines bysubclassing GitEnvand providing the right attributes.