Metadata-Version: 2.1
Name: py-data-validator
Version: 0.1.2
Summary: Python data validation library
Author-email: Krunal Dodiya <krunal@example.com>
License: MIT
Project-URL: homepage, https://www.proalgotrader.com
Project-URL: repository, https://github.com/krunaldodiya/py-data-validator
Project-URL: documentation, https://krunals-organization-2.gitbook.io/pydatavalidator
Requires-Python: >=3.10
Description-Content-Type: text/markdown

---
icon: shield-check
description: Data Validation Library for Python
---

# Introduction

**PyDataValidator** is a powerful and flexible Python library designed to streamline data validation processes. Whether you're building data pipelines, developing web applications, or handling complex datasets, PyDataValidator offers a comprehensive suite of tools to ensure your data is clean, consistent, and reliable.

#### Key Features

* **Comprehensive Rule Set**:
  * Validate data with a wide range of built-in rules, including checks for required fields, conditional presence, format validation, and more.
  * Examples include rules for ensuring fields are present, validating email formats, checking numeric ranges, and enforcing unique constraints.
* **Custom Validators**:
  * Easily create and integrate custom validation rules tailored to your specific needs.
  * Extend the library with your own validation logic to handle any specific data requirements.
* **Chainable Validation**:
  * Build complex validation logic by chaining multiple rules together for more nuanced data integrity checks.
  * Combine rules like `Required`, `Min`, and `Email` in a single, readable chain to enforce multiple conditions on a single field.
* **Detailed Error Reporting**:
  * Generate clear, actionable error messages that help you quickly identify and resolve data issues.
  * Each validation failure is accompanied by descriptive messages indicating the nature of the error and the affected data fields.
* **Ease of Use**:
  * Designed with simplicity in mind, PyDataValidator's intuitive API allows you to validate data with minimal code.
  * Quickly set up validations using a declarative syntax that integrates seamlessly into your Python projects.
* **Highly Extensible**:
  * Flexible architecture that integrates seamlessly with other libraries and frameworks, making it ideal for use in a variety of projects.
  * Whether you're working with Flask, Django, or standalone scripts, PyDataValidator adapts to your environment.
