semvec/pypi-packages huggingface dataset:
fastbinning 0.0.1
A high-performance binning library specifically designed for Credit Risk Modeling and Scorecard Development.
Requires Python: >=3.8

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A high-performance binning library specifically designed for **Credit Risk Modeling** and **Scorecard Development**. 

In financial risk modeling, **Weight of Evidence (WoE)** and **Information Value (IV)** are gold standards for feature engineering. `fastbinning` ensures mathematical rigor with extreme speed.

# Why fastbinning for Credit Scoring?

* **Monotonicity Guaranteed**: In credit scoring, features like 'Utilization Rate' or 'Age' must have a monotonic relationship with default risk to be explainable and compliant.
* **Built for Big Data**: While traditional tools struggle with millions of rows, `fastbinning` handles 10M+ records in milliseconds.
* **Robustness**: Prevents overfitting by enforcing minimum sample constraints (`min_bin_pct`), ensuring each bin is statistically significant.

# Installation
Install using pip:
```bash
pip install fastbinning
```

# Example
Please refer to the [**Examples**](https://github.com/RektPunk/fastbinning/tree/main/examples) provided for further clarification.
qrusty-pyclient 0.5.0
Python client wrapper for the qrusty API.
Requires Python: >=3.7

# qrusty_pyclient

A Python client wrapper for the qrusty API.

## Features

- Connect to a qrusty server
- Publish, consume, ack, and purge messages
- List and manage queues

## Installation

```bash
pip install qrusty_pyclient
```

## Usage

```python
from qrusty_pyclient import QrustyClient

client = QrustyClient(base_url="http://localhost:6784")
client.create_queue(name="orders", ordering="MaxFirst", allow_duplicates=True)
client.publish(queue="orders", priority=100, payload={"order_id": 123})
message = client.consume(queue="orders", consumer_id="worker-1")
if message is not None:
    client.ack(queue="orders", message_id=message["id"], consumer_id="worker-1")
```

## Development

Don't forget your `~/.pypirc` file if you intend to publish to PyPI.

## License

MIT