Skip to main content
Pre-release

This release is a pre-release and may not be stable for production use.

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.

ci-tests release pipy python downloads license InfuseAI Discord Invite

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-nightly 0.3.0.20220628a102

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for piperider-nightly 0.3.0.20220628a102
File Size Uploaded
piperider-nightly-0.3.0.20220628a102.tar.gz 613.1 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for piperider-nightly 0.3.0.20220628a102
File Interpreter ABI Platform
piperider_nightly-0.3.0.20220628a102-py3-none-any.whl Python 3 none any Details

Total release size: 1.3 MB

Release files / piperider-nightly-0.3.0.20220628a102.tar.gz

Download URL piperider-nightly-0.3.0.20220628a102.tar.gz
Size 613.1 kB
Tags Source
SHA-256 checksum
How to use checksums
e094029c7dee7fc8d21e61871b045130a8ba458bcd80dc8b273b7adcba870edc
BLAKE2b-256 checksum
How to use checksums
6861fa996f2be57fbe3d18094fe0f8a898166b00d46c528f7c5f2ef8e80401e3
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.8.12

Release files / piperider_nightly-0.3.0.20220628a102-py3-none-any.whl

Download URL piperider_nightly-0.3.0.20220628a102-py3-none-any.whl
Size 663.0 kB
Tags Python 3
SHA-256 checksum
How to use checksums
82b7e4b5ab5aca44cef708bec73e575d73f51fb5c28abff5cd650d47848f1e34
BLAKE2b-256 checksum
How to use checksums
817f47a4ea7ea4bc6c7ae6c9cec24f32653a45597b1ed302f2a37d1a3d3bb07c
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.8.12

Release history Release notifications | RSS feed

This release
Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page