Metadata-Version: 2.4
Name: pylib-validator
Version: 0.1.0
Summary: Validate Python objects with schema definitions. Perfect for API validation.
Author: pylib-validator
License: MIT
Project-URL: Homepage, https://github.com/upendra-manike/PyLib
Project-URL: Repository, https://github.com/upendra-manike/PyLib
Project-URL: Documentation, https://github.com/upendra-manike/PyLib
Project-URL: Issues, https://github.com/upendra-manike/PyLib/issues
Keywords: ai,data-processing,data-science,data-validation,machine-learning,ml,nlp,schema,utilities,validation
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Python: >=3.8
Description-Content-Type: text/markdown

# pyvalidator

Validate Python objects

## Installation

```bash
pip install pyvalidator
```

## 💡 Usage Examples

### Basic Operations

```python
from pylib_validator import Schema, validate

# Define validation schema
schema = Schema({
    "name": lambda x: isinstance(x, str) and len(x) > 0,
    "age": lambda x: isinstance(x, int) and 0 < x < 150,
    "email": lambda x: "@" in str(x)
})

# Validate data
data = {"name": "John", "age": 30, "email": "john@example.com"}
is_valid, errors = validate(data, schema)
# (True, [])
```

### AI/ML Use Cases

```python
from pylib_validator import Schema, validate

# Validate ML model inputs
input_schema = Schema({
    "features": lambda x: isinstance(x, list) and len(x) > 0,
    "model_type": lambda x: x in ["classification", "regression"]
})
is_valid, errors = validate(model_input, input_schema)
```

## 📚 API Reference

See package documentation for complete API reference.


## 🤖 AI Agent Friendly

This package is optimized for AI agents and code generation tools:
- **Clear function names** and signatures
- **Comprehensive docstrings** with examples
- **Type hints** for better IDE support
- **Common use cases** documented
- **Zero dependencies** for reliability

## License

MIT
