datavitals 0.1.6

A reusable Python library for data cleaning, ETL pipelines, and SQL query building

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

pip install datavitals