Quick Start

Integrate PipeRider with your dbt project in 5 mins

Install PipeRider

Navigate to your dbt folder, and install PipeRider.
pip install 'piperider[<connector>]'
PipeRider supports the following data connectors
pip install 'piperider[snowflake]'
pip install 'piperider[postgres]'
pip install 'piperider[bigquery]'
pip install 'piperider[redshift]'
pip install 'piperider[parquet]'
pip install 'piperider[csv]'
pip install 'piperider[duckdb]'
PipeRider requires python 3.7+

Initialize a project

Go to your dbt project, and initalize PipeRider.
piperider init
PipeRider will automatically find the dbt project file dbt_project.yml and initiate PipeRider.
The init command creates a .piperider directory inside the current directory. This is where all of the piperider project files will be stored, including data source configuration, data quality assertions, data profiling information, and generated report files.
After initialization, you can verify the configuration by running piperider diagnose. It will use the dbt profile file profiles.yml to connect to the data warehouse.

Run PipeRider

Collect profiling statistics by using
piperider run
The run command will generate profiling statistics for your table models, such as row_count, non_nulls, min, max, distinct, quantiles, topk and more.

Compare two branches

PipeRider is designed for code review. You can initiate the comparison in your local environment.
  1. 1.
    Run in the base branch. Usually, it's the main branch.
    git switch main
    dbt build
    piperider run
  2. 2.
    Run in the target branch. Usually, it's the PR branch for code review.
    git switch features/my-awesome-feature
    dbt build
    piperider run
  3. 3.
    Generate the comparison report. You then can compare the branch of your new Pull Request against the main branch and explore the impact of your changes by opening the generated HTML comparison report\
    piperider compare-reports --last
    The --last option automatically selects the last two data profiles for comparison. Omit this option to manually select the profiles you would like to compare.
  4. 4.
    Post the markdown summary to the PR comment. Aside from an HTML report, PipeRider generate a Markdown summary. You can add this summary of the data changes to your Pull Request comment so that your reviewer can review with impact information and merge with confidence

What's next