# 🚀 Satya v0.4.0 - Production Ready Release!

## 🎉 Major Milestone: Production-Ready Performance

We're thrilled to announce **Satya v0.4.0** - a production-ready release with comprehensive benchmarks against Pydantic 2.12.0, full Python 3.14 support, and a beautiful developer experience!

---

## 📊 Benchmark Results vs Pydantic 2.12.0

<p align="center">
  <img src="benchmarks/pydantic_comparison_graph.png" alt="Performance Comparison" width="100%"/>
</p>

### Performance Summary

| Metric | Pydantic 2.12.0 | Satya 0.4.0 | Speedup |
|--------|-----------------|-------------|---------|
| **Single Validation** | 1.02M ops/sec | 1.10M ops/sec | **1.09× faster** ⚡ |
| **Batch Validation** | 915K ops/sec | **5.0M ops/sec** | **5.46× faster** 🚀 |
| **Field Access** | 65.3M/sec | 66.2M/sec | **1.01× (parity!)** 🔥 |
| **Complex Nested** | 917K ops/sec | 1.01M ops/sec | **1.11× faster** ✨ |

**Key Takeaway**: Satya achieves **5.46× faster batch validation** while maintaining field access parity with Pydantic!

---

## ✨ What's New in v0.4.0

### 🐍 Python 3.14 Support
- **Full support for Python 3.14.0** (released Oct 7, 2025)
- Supports Python 3.9 through 3.14
- Optimized for both GIL and free-threaded builds

### 📈 Comprehensive Benchmarks
- **Fair comparison with Pydantic 2.12.0** (latest version)
- Beautiful performance graphs generated with matplotlib
- Reproducible benchmarks in `benchmarks/pydantic_2_12_comparison.py`
- Results saved as JSON for transparency

### 🧪 Production-Ready Testing
- Comprehensive Pydantic compatibility test suite
- 25+ tests covering all major features
- Zero breaking changes from v0.3.x

### 📚 Enhanced Documentation
- Updated README with benchmark graphs at the top
- Clear "Quick Start" section (30 seconds to production!)
- Showcase of easy drop-in Pydantic replacement

---

## 🎯 Why Satya v0.4.0?

### 1. **Blazing Fast Batch Processing**
Perfect for:
- ETL pipelines processing thousands of records
- API endpoints handling bulk requests
- Data validation in ML pipelines
- High-throughput microservices

```python
# Process 50,000 records 5.46× faster than Pydantic!
users = User.validate_many(large_dataset)
```

### 2. **Drop-in Pydantic Replacement**
```python
# Before (Pydantic)
from pydantic import BaseModel, Field

# After (Satya) - just change the import!
from satya import BaseModel, Field

# Everything else stays the same! 🎉
```

### 3. **Field Access Parity**
No performance penalty for accessing validated data:
```python
user = User.model_validate_fast(data)
print(user.name)  # Just as fast as Pydantic!
```

---

## 🔧 Installation

```bash
pip install satya==0.4.0
```

Or upgrade from previous versions:
```bash
pip install --upgrade satya
```

---

## 📖 Quick Start

```python
from satya import BaseModel, Field

class User(BaseModel):
    name: str
    age: int = Field(ge=0, le=150)
    email: str = Field(email=True)

# Single validation (1.09× faster)
user = User.model_validate_fast({
    "name": "Alice", 
    "age": 30, 
    "email": "alice@example.com"
})

# Batch validation (5.46× faster!)
users = User.validate_many([
    {"name": "Alice", "age": 30, "email": "alice@example.com"},
    {"name": "Bob", "age": 25, "email": "bob@example.com"},
    # ... thousands more
])

print(f"✅ Validated {len(users)} users at 5× Pydantic speed!")
```

---

## 🏗️ Architecture Highlights

### Built on Solid Foundations
- **Rust + PyO3 0.26**: Native performance with Python integration
- **Hidden Classes**: V8/PyPy-inspired optimization for field access
- **BLAZE Compilation**: Schema compilation for optimal validation
- **Adaptive Parallelism**: Smart serial/parallel switching for batches

### Academic Research Applied
- Hölzle et al. (OOPSLA '91) - Hidden Classes & PICs
- Bolz et al. (VMIL '09) - PyPy Tracing JIT
- Chevalier-Boisvert et al. (PLDI 2015) - Shape-Based Optimization

---

## 📊 Use Cases

### 1. High-Throughput APIs
```python
from fastapi import FastAPI
from satya import BaseModel

app = FastAPI()

class Request(BaseModel):
    user_id: int
    action: str

@app.post("/bulk-action")
async def bulk_action(requests: list[dict]):
    # 5.46× faster than Pydantic!
    validated = Request.validate_many(requests)
    return process_bulk(validated)
```

### 2. ETL Pipelines
```python
# Process millions of records efficiently
validator = DataRecord.validator()
validator.set_batch_size(10000)

for valid_record in validator.validate_stream(huge_dataset):
    db.insert(valid_record)
```

### 3. ML Data Validation
```python
# Validate training data at scale
TrainingExample.validate_many(training_data)  # 5× faster!
```

---

## 🔄 Migration from Pydantic

### Zero Code Changes Required!

```python
# Step 1: Change import
- from pydantic import BaseModel, Field
+ from satya import BaseModel, Field

# Step 2: That's it! Everything else works the same.
```

### Performance Tips

For maximum performance:
```python
# Use model_validate_fast for single objects
user = User.model_validate_fast(data)

# Use validate_many for batches
users = User.validate_many(batch_data)
```

---

## 🙏 Acknowledgments

Special thanks to:
- The **Pydantic** team for setting the standard
- The **PyO3** team for excellent Rust-Python integration
- The **V8**, **PyPy**, and **Self** VM teams for pioneering optimization techniques
- Our community for feedback and testing

---

## 📚 Resources

- **Documentation**: [README.md](README.md)
- **Implementation Guide**: [IMPLEMENTATION_GUIDE.md](IMPLEMENTATION_GUIDE.md)
- **Technical Deep Dive**: [SUMMARY_IMPROVEMENTS.md](SUMMARY_IMPROVEMENTS.md)
- **Changelog**: [changelog.md](changelog.md)
- **Benchmarks**: [benchmarks/pydantic_2_12_comparison.py](benchmarks/pydantic_2_12_comparison.py)

---

## 🐛 Bug Reports & Feature Requests

- **GitHub Issues**: [github.com/justrach/satya/issues](https://github.com/justrach/satya/issues)
- **Discussions**: [github.com/justrach/satya/discussions](https://github.com/justrach/satya/discussions)

---

## 🎯 What's Next?

### Roadmap for v0.5.0
1. **oneOf/anyOf/allOf** support for complex schema composition
2. **$ref** schema references
3. **Enhanced error messages** with detailed validation paths
4. **More string formats** (uuid, date-time, uri)

---

## 🌟 Star Us on GitHub!

If you find Satya useful, please give us a star on GitHub! ⭐

**Satya v0.4.0 - THE FASTEST Python validation library!** 🚀

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*Released: October 9, 2025*
*Python Versions: 3.9 - 3.14*
*License: Apache 2.0*
