semvec/pypi-packages huggingface dataset:
haja-workers 0.1.1
Haja Workers SDK - Python implementation for workflow functions
Requires Python: >=3.10

# Haja Workers SDK

Python SDK for building workers that integrate with the Haja workflow system.

## Installation

```bash
pip install haja_workers
```

## Quick Start

```python
import asyncio
from haja_workers import Server, SimpleFunction

async def main():
    server = Server()
    
    # Define a simple function
    echo = SimpleFunction[dict, dict](
        name="echo", 
        version="1.0.0", 
        description="Echoes input"
    ).with_handler(lambda inputs: inputs)
    
    # Register and start
    server.register_function(echo)
    await server.start()

if __name__ == "__main__":
    asyncio.run(main())
```

## Features

- Create input functions
- Store chat history
- Handle workflow events
- Communicate with the Haja workflow system

## Examples

See the `examples/` directory for more detailed usage examples.
pyg-timeseries 0.0.42
Utilities for fast timeseries analysis
Requires Python: >=3.6

# pyg-timeseries
pandas is great but pyg-timeseries introduces a few improvements. 

* pyg is designed so that for dataframes/series without nans, it matches pandas exactly 
* consistent treatments of nan's: unlike pandas, pyg ignores nans everywhere in its calculations.
* np.ndarray and pandas dataframes are treated the same and pyg operates on np.arrays seemlessly
* state-management: pyg introduces a framework for returning not just the timeseries, but also the state of the calculation. This can be fed into the next calculation batch, allowing us not to have to 're-run' everything from the distant past.
* performance-wise, pyg is implemented via numba with performance times comparable to pandas

pip install from https://pypi.org/project/pyg-timeseries/