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⚡ B-FAST (Binary Fast Adaptive Serialization Transfer)

B-FAST is an ultra-high performance binary serialization protocol, developed in Rust for Python and TypeScript ecosystems. It's designed to replace JSON in critical routes where latency, CPU usage, and bandwidth are bottlenecks.

"Performance is not just about speed—it's about efficiency where it matters most"

B-FAST was born from the recognition that modern applications need more than just fast serialization—they need smart serialization that adapts to real-world constraints. After extensive optimization, B-FAST has found its perfect niche in bandwidth-constrained environments, achieving 1.7x faster than orjson for simple objects and 5.7x faster on slow networks.

Philosophy: We believe that the future of data transfer lies not in raw CPU speed alone, but in intelligent protocols that minimize network overhead while maintaining excellent performance. B-FAST represents our contribution to a more efficient, bandwidth-conscious web.

🚀 Why B-FAST?

  • Rust Engine: Native serialization without Python interpreter overhead
  • Pydantic Native: Reads Pydantic model attributes directly from memory, skipping the slow .model_dump() process
  • Zero-Copy NumPy: Serializes tensors and numeric arrays directly, achieving 14-96x speedup vs JSON/orjson
  • Parallel Compression: LZ4 with multi-thread processing for large payloads (>1MB)
  • Cache Optimized: Aligned allocation and batch processing for maximum efficiency

📊 Performance

🚀 Simple Objects (10,000)

Format Time (ms) Speedup
JSON 12.0ms 1.0x
orjson 8.19ms 1.5x
B-FAST 4.83ms 🚀 2.5x

B-FAST is 1.7x faster than orjson!

🔄 Round-Trip (Encode + Network + Decode)

📡 100 Mbps (Slow Network)

Format Total Time Speedup vs orjson
JSON 114.5ms 0.8x
orjson 91.7ms 1.0x
B-FAST + LZ4 16.1ms 🚀 5.7x

📡 1 Gbps (Fast Network)

Format Total Time Speedup vs orjson
JSON 29.4ms 0.5x
orjson 15.3ms 1.0x
B-FAST + LZ4 7.2ms 🚀 2.1x

📡 10 Gbps (Ultra-Fast Network)

Format Total Time Speedup vs orjson
JSON 20.9ms 0.4x
orjson 7.7ms 1.0x
B-FAST + LZ4 6.3ms 🚀 1.2x

🎯 Ideal Use Cases

  • 📱 Mobile/IoT: 89% data savings + 5.7x performance on slow networks
  • 🌐 APIs with slow networks: Up to 5.7x faster than orjson
  • 📊 Data pipelines: 14-96x speedup for NumPy arrays
  • 🗜️ Storage/Cache: Superior integrated compression
  • 🚀 Simple objects: 1.7x faster than orjson
  • 🗜️ Storage/Cache: Superior integrated compression

📦 Installation

Backend (Python)

uv add bfast-py

or

pip install bfast-py

Frontend (TypeScript)

npm install bfast-client

🛠️ Basic Usage

Python

import b_fast
from pydantic import BaseModel

class User(BaseModel):
    id: int
    name: str
    email: str

# Create encoder
bf = b_fast.BFast()

# Sample data
users = [User(id=i, name=f"User {i}", email=f"user{i}@example.com") for i in range(1000)]

# Serialize
data = bf.encode_packed(users, compress=True)
print(f"Size: {len(data)} bytes")

# Deserialize
decoded = bf.decode_packed(data)

TypeScript

import { BFastDecoder } from 'bfast-client';

async function loadData() {
    const response = await fetch('/api/users');
    const buffer = await response.arrayBuffer();

    // Decode and decompress automatically
    const users = BFastDecoder.decode(buffer);
    console.log(users);
}

📄 License

Distributed under the MIT License. See LICENSE for more information.