Metadata-Version: 2.4
Name: datavitals
Version: 0.1.6
Summary: A reusable Python library for data cleaning, ETL pipelines, and SQL query building
Home-page: https://github.com/kamaleshkumaroffi/datavitals
Author: Kamaleshkumar.K
Author-email: kamaleshkumaroffi@gmail.com
License: MIT
Project-URL: Source, https://github.com/kamaleshkumaroffi/datavitals
Project-URL: Tracker, https://github.com/kamaleshkumaroffi/datavitals/issues
Project-URL: LinkedIn, https://www.linkedin.com/in/kamaleshkumaroffi
Keywords: data-engineering,etl,data-cleaning,sql-builder,pandas,python-library
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Information Technology
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Database
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas>=1.5.0
Provides-Extra: dev
Requires-Dist: pytest>=7.0.0; extra == "dev"
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: keywords
Dynamic: license
Dynamic: license-file
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# datavitals

**datavitals** is a production-ready Python library that simplifies
real-world data engineering workflows by standardizing:

- Data Cleaning
- ETL Pipelines
- SQL Query Generation

It helps developers and data engineers avoid repetitive boilerplate,
reduce runtime errors, and build consistent pipelines faster.

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## 👤 Author

**Kamaleshkumar.K**  
🔗 LinkedIn: https://www.linkedin.com/in/kamaleshkumaroffi  
💻 GitHub: https://github.com/kamaleshkumaroffi/datavitals  

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## 🚀 Why datavitals?

In real projects:
- Data is messy (nulls, duplicates, wrong types)
- ETL code breaks due to edge cases
- SQL strings become unsafe and unreadable

**datavitals solves this by providing safe, tested, reusable utilities
that work out-of-the-box.**

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## ✨ Features

### 🧹 Data Cleaning
- Remove duplicates
- Drop or fill null values
- Trim string columns
- Safe numeric conversion
- Strong validation with meaningful errors

### 🔄 ETL Pipelines
- Plug-and-play Extract → Transform → Load
- Supports custom transform functions
- Safe handling of empty or invalid data
- Execution time measurement

### 🧠 SQL Builder
- Dynamic SELECT queries
- WHERE clause with safe value handling
- Optional LIMIT
- Clear error messages for invalid inputs

### 🧪 Production-Ready Tests
- Pytest-based validation
- Covers edge cases and failure scenarios
- Ensures reliability during future changes

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## 📦 Installation

```bash
pip install datavitals
