Package: piperider
Docs|Discord|BlogCode review for data in dbtPipeRider automatically compares your data to highlight the difference in impacted downstream dbt models so you can
merge your Pull Requests with confidence.How it works:Easy to connect your datasource -> PipeRider leverages
theconnection profiles in your dbt projectto connect
to the data warehouseGenerate profiling statistics of your models to get a high-level overview of your dataCompare target branch changes with the main branch in a HTML reportPost a quick summary of the data changes to your PR, so others can be confident tooCore conceptsEasy to install: Leveraging dbt's configuration settings, PipeRider can be installed within 2 minutesFast comparison: by collecting profiling statistics (e.g. uniqueness, averages, quantiles, histogram) and metric
queries, comparing downstream data impact takes little time, speeding up your team's review timeValuable insights: various profiling statistics displayed in the HTML report give fast insights into your dataQuickstartInstall PipeRiderpipinstallpiperider[<connector>]You can find all supported data source connectorshere.Add PipeRider tag on your model: Go to your dbt project, and add the PipeRider tag on the model you want to
profile.--models/staging/stg_customers.sql{{config(tags=["piperider"])}}select...and show the models would be run by piperiderdbt list -s tag:piperider --resource-type modelRun PipeRiderpiperiderrunTo see the full quick start guide, please refer
toPipeRider documentationFeaturesModel profiling: PipeRider can profile yourdbt modelsand obtain
information such as basic data composition, quantiles, histograms, text length, top categories, and more.Metric queries: PipeRider can integrate withdbt metricsand present
the time-series data of metrics in the report.HTML report: PipeRider generates a static HTML report each time it runs, which can be viewed locally or shared.Report comparison: You can compare two previously generated reports or use a single command to compare the
differences between the current branch and the main branch. The latter is designed specifically for code review
scenarios. In our pull requests on GitHub, we not only want to know which files have been changed, but also the impact
of these changes on the data. PipeRider can easily generate comparison reports with a single command to provide this
information.CI integration: The key to CI is automation, and in the code review process, automating this workflow is even more
meaningful. PipeRider can easily integrate into your CI process. When new commits are pushed to your PR branch,
reports can be automatically generated to provide reviewers with more confidence in the changes made when reviewing.Example Report DemoWe use the example projectgit-repo-analyticsto demonstrate how to
use piperider+dbt+duckdb to analyzedbt-corerepository. Here is the generated
result (daily update)Run ReportComparison ReportComparison Summary in a PRPipeRider Cloud (beta)PipeRider Cloudallows you to upload reports and share them with your team members. For
information on pricing plans, please refer to thepricing page.PipeRider Compare ActionPipeRider provides thePipeRider Compare Actionto
quickly integrate into your Github Actions workflow. It has the following features:Automatically generates a report comparing the PR branch to the main branchUploads the report to GitHub artifacts or PipeRider cloudAdds a comment to the pull request with a comparison summary and a link to the report.You can refer to
exampleworkflow yamland
theexample pull request.DevelopmentSeesetup dev environmentand thecontributing guildlinesto get started.We love chatting with our users!Let us knowif you have any questions, feedback, or
need help trying out PipeRider! :heart: