semvec/pypi-packages huggingface dataset:
wirehead 0.9.2
Caching system for scaling of synthetic data generators using MongoDB
Requires Python: >=3.6

# Wirehead

Caching system for scaling of synthetic data generators using MongoDB.

## Features
- Cache and efficiently serve synthetic data from generators
- Scalable architecture using MongoDB for storage
- Support for numpy and torch tensors
- Configurable caching behavior

## Quick Start
```python
# Generator example
import numpy as np
from wirehead import WireheadGenerator 

def create_generator():
    while True: 
        img = np.random.rand(256,256,256)
        lab = np.random.rand(256,256,256)
        yield (img, lab)

brain_generator = create_generator()
wirehead_runtime = WireheadGenerator(
    generator = brain_generator,
    config_path = "config.yaml" 
)
wirehead_runtime.run_generator()

# Dataset example
from wirehead import MongoheadDataset
dataset = MongoheadDataset(config_path = "config.yaml")
data = dataset[[0]]
```

## MongoDB Setup Required
Requires a running MongoDB instance.

## Documentation
For full documentation and examples, visit: https://github.com/neuroneural/wirehead