piperider
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InfuseAI
Code review for data in dbt
PipeRider: Data Reliability Automated
PipeRider ensures data reliability through automating constant data testing and monitoring.
Key Features:
- Instant quality assessment in HTML report: sample report
- Report comparison: sample comparsion report
- Extensible custom assertions
- Works with existing dbt projects
- Automatic test recommendations
Read more about why we created PipeRider.
Getting started
Install PipeRider
pip install piperider
By default, PipeRider supports built-in SQLite connector, extra connectors are available:
| connectors | install | supported since |
|---|---|---|
| snowflake | pip install 'piperider[snowflake]' | |
| postgres | pip install 'piperider[postgres]' | |
| bigquery | pip install 'piperider[bigquery]' | PipeRider v0.7.0 |
| redshift | pip install 'piperider[redshift]' | PipeRider v0.7.0 |
Use comma to install multiple connectors in one line:
pip install 'piperider[postgres,snowflake]'
You can follow the quick start guide to learn more about PipeRider.
Attach PipeRider to a dbt project
piperider init creates /.piperider under a dbt project root and generates necessary configurations.
Scan data quality from models
piperider run scans the models from data sources and creates assessment results in /.piperider/output
Generate reports
piperider generate-report generate a static HTML report.
Generate comparison view
You can use piperider compare-report to compare 2 reports.
Learn More
| PipeRider Resources | Description |
|---|---|
| Documentation | PipeRider Main Doc Site |
| Sample_Project | Sample Project with with sqlite |
| dbt_Sample_Project | Sample Project with dbt |
| Roadmap | PipeRider Roadmap |
Get involved
Contributions
We welcome contributions. See the Set up dev environment and the Contributing guildline to get started.
InfuseAI