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PipeRider

PipeRider: Data Reliability Automated

What is PipeRider?

PipeRider is an open-source toolkit for detecting data issues across pipelines that work with CI systems for continuous data quality assessment. PipeRider makes it easy for teams to have visibility about how data are being tested, and ensure errors are caught before they cause outages of downstream data applications like business intelligence dashboards or ML systems.

Why PipeRider?

Ensuring consistent quality of data used to be difficult. Missing values, schema changes and data drift (to name just a few) could be introduced to your data at any time. Without effective data quality tools, these errors will affect downstream operations and result in countless lost hours of debugging and missed revenue opportunities from unexpected downtime. PipeRider allows you to define the shape of your data once, and then use the data checking functionality to alert you to changes in your data quality.

Read more about why we created PipeRider.

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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

Key Features

Instant quality assessment in HTML report

Example of single run report

Report Comparison

Example of comparison report

Extensible custom assertions

Refer to custom assertions

Works with existing dbt projects

Automatic Test Recommendations (Coming Soon)

Getting started

Install PipeRider

pip install piperider

By default, PipeRider supports built-in SQLite connector, extra connectors are available:

connectors install
snowflake pip install 'piperider[snowflake]'
postgres pip install 'piperider[postgres]'

Use comma to install multiple connectors in one line:

pip install 'piperider[postgres,snowflake]'

Attach PipeRider to a dbt project

piperider_init

This command creates /.piperider under a dbt project root and generates necessary configurations.

Scan data quality from models

piperider_run

This command scans the models from data sources and creates assessment results in /.piperider/output

Generate reports

piperider_report

generate a static HTML report under the current path.

Generate comparison view

piperider_compare

The generated report in HTML will be placed in the path shown in the console.

Get involved

Contributions

We welcome contributions. See the Set up dev environment and the Contributing guildline to get started.

Metadata

Release files for piperider 0.4.0a27205

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Source distribution (sdist)

Source distribution for piperider 0.4.0a27205
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Built distribution (wheel)

Table of built distributions (wheels) for piperider 0.4.0a27205
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piperider-0.4.0a27205-py3-none-any.whl Python 3 none any Details

Total release size: 1.3 MB

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