# databricks-labs-dqx

> Data Quality eXtended (DQX) is a Python library for data quality checks and data quality monitoring

- **URL**: https://www.freshcrate.ai/projects/databricks-labs-dqx
- **Author**: pypi
- **Category**: Frameworks
- **Latest version**: `v0.14.0` (2026-05-05)
- **License**: Unknown
- **Source**: https://github.com/databrickslabs/dqx/issues
- **Homepage**: https://pypi.org/project/databricks-labs-dqx/
- **Language**: Python
- **GitHub**: 397 stars, 108 forks
- **Registry**: pypi (`databricks-labs-dqx`)
- **Tags**: `databricks`, `pypi`

## Description

DQX by Databricks Labs
===

<p align="center">
    <a href="https://github.com/databrickslabs/dqx">
        <img src="https://raw.githubusercontent.com/databrickslabs/dqx/refs/heads/main/docs/dqx/static/img/logo.svg" class="align-center" width="200" height="200" alt="logo" />
    </a>
</p>

Simplified Data Quality checking at Scale for PySpark Workloads on streaming and standard DataFrames.

[![build](https://github.com/databrickslabs/dqx/actions/workflows/push.yml/badge.svg)](https://github.com/databrickslabs/dqx/actions/workflows/push.yml) 
[![codecov](https://codecov.io/github/databrickslabs/dqx/graph/badge.svg)](https://codecov.io/github/databrickslabs/dqx) 
![linesofcode](https://aschey.tech/tokei/github/databrickslabs/dqx?category=code)
[![PyPI](https://img.shields.io/pypi/v/databricks-labs-dqx?label=pypi%20package&cacheSeconds=3600)](https://pypi.org/project/databricks-labs-dqx/) 
![PyPI Downloads](https://static.pepy.tech/personalized-badge/databricks-labs-dqx?period=month&units=international_system&left_color=grey&right_color=orange&left_text=PyPI%20downloads&cacheSeconds=3600)

# 📖 Documentation

The complete documentation is available at: [https://databrickslabs.github.io/dqx/](https://databrickslabs.github.io/dqx/)

# 🛠️ Contribution

Please see the contribution guidance [here](https://databrickslabs.github.io/dqx/docs/dev/contributing/) on how to contribute to the project (build, test, and submit a PR).

# 💬 Project Support

Please note that this project is provided for your exploration only and is not 
formally supported by Databricks with Service Level Agreements (SLAs). They are 
provided AS-IS, and we do not make any guarantees. Please do not 
submit a support ticket relating to any issues arising from the use of this project.

Any issues discovered through the use of this project should be filed as GitHub 
[Issues on this repository](https://github.com/databrickslabs/dqx/issues). 
They will be reviewed as time permits, but no formal SLAs for support exist.

## Recent releases

| Version | Date | Urgency | Changes |
| --- | --- | --- | --- |
| `v0.14.0` | 2026-05-05 | High | ## What's Changed  * ML-based row-level anomaly detection ([#990](https://github.com/databrickslabs/dqx/issues/990), [#1055](https://github.com/databrickslabs/dqx/issues/1055), [#1062](https://github.com/databrickslabs/dqx/issues/1062)). DQX now offers ML-based row anomaly detection that automatically identifies unusual rows in data without requiring manually specified thresholds, enabling the detection of issues missed by rule-based checks. Users provide recent representative data, and DQX tr |
| `0.13.0` | 2026-04-21 | Low | Imported from PyPI (0.13.0) |
| `v0.13.0` | 2026-02-09 | Low | ## What's Changed * New DQX Data Quality Dashboard ([#1019](https://github.com/databrickslabs/dqx/issues/1019)). The data quality dashboard has been significantly enhanced to provide a centralized view of data quality metrics across all tables, allowing users to monitor and track data quality issues with greater ease. The dashboard now consists of three tabs - Data Quality Summary, Data Quality by Table (Time Series), and Data Quality by Table (Full Snapshot) - each catering to different monito |
| `v0.13.0` | 2026-02-09 | Low | ## What's Changed * New DQX Data Quality Dashboard ([#1019](https://github.com/databrickslabs/dqx/issues/1019)). The data quality dashboard has been significantly enhanced to provide a centralized view of data quality metrics across all tables, allowing users to monitor and track data quality issues with greater ease. The dashboard now consists of three tabs - Data Quality Summary, Data Quality by Table (Time Series), and Data Quality by Table (Full Snapshot) - each catering to different monito |
| `v0.13.0` | 2026-02-09 | Low | ## What's Changed * New DQX Data Quality Dashboard ([#1019](https://github.com/databrickslabs/dqx/issues/1019)). The data quality dashboard has been significantly enhanced to provide a centralized view of data quality metrics across all tables, allowing users to monitor and track data quality issues with greater ease. The dashboard now consists of three tabs - Data Quality Summary, Data Quality by Table (Time Series), and Data Quality by Table (Full Snapshot) - each catering to different monito |
| `v0.13.0` | 2026-02-09 | Low | ## What's Changed * New DQX Data Quality Dashboard ([#1019](https://github.com/databrickslabs/dqx/issues/1019)). The data quality dashboard has been significantly enhanced to provide a centralized view of data quality metrics across all tables, allowing users to monitor and track data quality issues with greater ease. The dashboard now consists of three tabs - Data Quality Summary, Data Quality by Table (Time Series), and Data Quality by Table (Full Snapshot) - each catering to different monito |
| `v0.13.0` | 2026-02-09 | Low | ## What's Changed * New DQX Data Quality Dashboard ([#1019](https://github.com/databrickslabs/dqx/issues/1019)). The data quality dashboard has been significantly enhanced to provide a centralized view of data quality metrics across all tables, allowing users to monitor and track data quality issues with greater ease. The dashboard now consists of three tabs - Data Quality Summary, Data Quality by Table (Time Series), and Data Quality by Table (Full Snapshot) - each catering to different monito |
| `v0.13.0` | 2026-02-09 | Low | ## What's Changed * New DQX Data Quality Dashboard ([#1019](https://github.com/databrickslabs/dqx/issues/1019)). The data quality dashboard has been significantly enhanced to provide a centralized view of data quality metrics across all tables, allowing users to monitor and track data quality issues with greater ease. The dashboard now consists of three tabs - Data Quality Summary, Data Quality by Table (Time Series), and Data Quality by Table (Full Snapshot) - each catering to different monito |
| `v0.13.0` | 2026-02-09 | Low | ## What's Changed * New DQX Data Quality Dashboard ([#1019](https://github.com/databrickslabs/dqx/issues/1019)). The data quality dashboard has been significantly enhanced to provide a centralized view of data quality metrics across all tables, allowing users to monitor and track data quality issues with greater ease. The dashboard now consists of three tabs - Data Quality Summary, Data Quality by Table (Time Series), and Data Quality by Table (Full Snapshot) - each catering to different monito |
| `v0.13.0` | 2026-02-09 | Low | ## What's Changed * New DQX Data Quality Dashboard ([#1019](https://github.com/databrickslabs/dqx/issues/1019)). The data quality dashboard has been significantly enhanced to provide a centralized view of data quality metrics across all tables, allowing users to monitor and track data quality issues with greater ease. The dashboard now consists of three tabs - Data Quality Summary, Data Quality by Table (Time Series), and Data Quality by Table (Full Snapshot) - each catering to different monito |

## Citation

- HTML: https://www.freshcrate.ai/projects/databricks-labs-dqx
- Markdown: https://www.freshcrate.ai/projects/databricks-labs-dqx.md
- Dependencies JSON: https://www.freshcrate.ai/api/projects/databricks-labs-dqx/deps

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