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PyValidata is a Python package for data validation, created to ensure the integrity and quality of data in Python projects. With PyValidata, you can easily validate data types, numeric ranges, string lengths, null values, and apply custom validation rules.
New functions released, which are more advanced and useful to developers:
Validation functions:
Data type validation: Check if data elements belong to the expected data types.
Numeric range validation: Validate whether numeric data falls within specified ranges.
String length validation: Ensure that string data meets specified length criteria.
Null and missing value detection: Check for null or missing values in data.
Pattern matching: Validate data based on specific patterns or regular expressions.
Custom validation rules: Define and apply your custom validation rules to the data.
Note that this is just Pyvalidata's current functionality, and more will be added as more feedback is given.
You can install PyValidata using pip:
pip install pyvalidata
Please simply call the help function via pyvalidata.help()
for full documentation on how to use this package. The documentation goes in detail and provides examples of each function, all while being easy to follow.
We welcome contributions! If you find a bug, have a suggestion, or want to contribute in any other way, please open an issue or submit a pull request.
PyValidata is open-source software licensed under the MIT License.
Thank you for considering PyValidata! We hope it simplifies and enhances your data validation process in your Python projects. Happy validating!
FAQs
A Python package for data validation
We found that pyvalidata demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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