semvec/pypi-packages huggingface dataset:
finmc 0.0.8
finmc is a Python library for Monte Carlo Simulation.

# finmc

[![CI](https://github.com/finlib/finmc/actions/workflows/main.yml/badge.svg)](https://github.com/finlib/finmc/actions/workflows/main.yml)

This package contains Monte-Carlo implementations of many financial models derived from a common interface class. This interface allows for

 - [Shared utilities](https://finlib.github.io/finmc/utilities/) that can be used for all models for tasks such as calculating implied vol surface.
 - [Price Calculators](https://finlib.github.io/finmc/calculators/) that are model invariant.
 - High performance, even with a large number of paths.
 - [New models](https://finlib.github.io/finmc/models/api/#mc-models-in-other-repos) can be created outside this repositary, by indepedent contributors, and yet be compatible with above utilities and calculators.

## Documentation

- [Home](https://finlib.github.io/finmc/)
- [Models](https://finlib.github.io/finmc/models/localvol)

## Notebooks
<table>
<tr>
    <td> 
    <a href="https://github.com/finlib/finmc/blob/main/notebooks/hullwhite.ipynb">
    <img src="https://finlib.github.io/finmc/images/blank_mc.png"/>
    </td>
    <td>
    <a href="https://github.com/finlib/finmc/blob/main/notebooks/heston.ipynb">
    <img src="https://finlib.github.io/finmc/images/heston_vol_mc.png" alt="forward collar"/>
    </td>
</tr>
<tr>
    <td> Hull-White with a term structure of rates.</td>
    <td> Paths of Variance in Heston Model.</td>
</tr>
</table>

[All Notebooks](https://github.com/finlib/finmc/tree/main/notebooks)

## Install it from PyPI

```bash
pip install finmc
```

### Example
This is an example of pricing a vanilla option using the local volatility model.

```py
import numpy as np
from finmc.models.localvol import LVMC
from finmc.calc.option import opt_price_mc

# Define Dataset with zero rate curve, and forward curve.
dataset = {
    "MC": {"PATHS": 100_000, "TIMESTEP": 1 / 250},
    "BASE": "USD",
    "ASSETS": {
        "USD":("ZERO_RATES", np.array([[2.0, 0.05]])),
        "SPX": ("FORWARD", np.array([[0.0, 5500], [1.0, 5600]])),
        },
    "LV": {"ASSET": "SPX", "VOL": 0.3},
}

model = LVMC(dataset)
price = opt_price_mc(5500.0, 1.0, "Call", "SPX", model)
```
paudio 0.3.0
A Python wrapper for paplay and parecord to play and record audio using PulseAudio.
Requires Python: >=3.6


# pAudio

`pAudio` is a Python wrapper for `paplay and parecord`, the PulseAudio command-line tool for playing and capturing audio data. This module allows you to use `parecord` directly from Python by passing options as function arguments.

## Installation

You can install the package via pip:

```
pip install paudio
```

## Example Usage

```
from pAudio import parecord

# Example of recording with specific options
output_file = "output.wav"
parecord(
    output_file=output_file,
    record=True,
    verbose=True,
    device="@DEFAULT_SOURCE@",
    rate=48000,  # Sample rate in Hz
    channels=1,  # Mono audio
    volume=32000,  # Mid-range volume
    raw=True  # Recording raw PCM data
)

```
processamento-imagens-matheus 0.1
Image processing package using Skimage
Requires Python: >=3.5

# Image Processing Packages

Description. 
The package *processamento-imagens-matheus* is used for:
- Processing:
  	- Transfer histogram between two images.
  	- Find differences between two images based on structural similarity 	index (SSIM).
  	- Resize images with specified proportions.
 	- Apply Gaussian and Sobel filters for smoothing and edge detection.
  	- Rotate images by a specified angle.
- Utilities:
  - Read and save images.
  - Plot images, comparison results, and histograms (grayscale or RGB).

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install *processamento-imagens-matheus*

```bash
pip install processamento-imagens-matheus
```

## Usage

```python
from processing.combination import transfer_histogram, find_difference
from processing.transformation import resize_image, apply_gaussian_filter, apply_sobel_filter, rotate_image
from utils.io import read_image, save_image
from utils.plot import plot_image, plot_result, plot_histogram

# Transfer histogram between two images
image1 = read_image('path_to_image1.jpg')
image2 = read_image('path_to_image2.jpg')

matched_image = transfer_histogram(image1, image2)
plot_result(image1, image2, matched_image)

# Resize an image
resized_image = resize_image(image1, 0.5)
plot_image(resized_image)

# Apply Sobel filter
edges_image = apply_sobel_filter(image1)
plot_image(edges_image)
```

## Author
Matheus Pizani

## License
[MIT](https://choosealicense.com/licenses/mit/)
networkx-gdf 1.5.3
Python package to read and write NetworkX graphs in GDF (Graph Data Format).
Requires Python: >=3.7
Keywords: Network, Graph, GDF

# networkx-gdf

[![PyPI package](https://badge.fury.io/py/networkx-gdf.svg)](https://pypi.org/p/networkx-gdf/)
[![Documentation Status](https://readthedocs.org/projects/networkx-gdf/badge/?version=latest)](https://networkx-gdf.readthedocs.io/en/latest/?badge=latest)
[![Downloads](https://static.pepy.tech/badge/networkx-gdf)](https://pepy.tech/project/networkx-gdf?versions=*)
[![Downloads](https://static.pepy.tech/badge/networkx-gdf/month)](https://pepy.tech/project/networkx-gdf?versions=*)
[![License](https://img.shields.io/pypi/l/networkx-gdf)](https://github.com/nelsonaloysio/networkx-gdf/blob/main/LICENSE.md)

Python package to read and write NetworkX graphs as GDF (Graph Data Format).

GDF is a compact file format originally implemented by [GUESS](https://graphexploration.cond.org). Although the software itself is not anymore maintained, the format is still supported by active open-source projects such as [Gephi](https://gephi.org/) (see details [here](https://networkx-gdf.readthedocs.io/en/stable/api.html#networkx_gdf.GDF)).

## Requirements

* **Python>=3.7**
* networkx>=2.1
* pandas>=1.1.0

## Install

Package is available to install on [PyPI](https://pypi.org/project/networkx-gdf/):

```bash
$ pip install networkx-gdf
```

## Usage

The following is an example covering the package's functionality:

```python
from networkx_gdf import read_gdf, write_gdf

# Builds NetworkX graph object from file.
G = read_gdf("input_file.gdf")

# Writes NetworkX graph object to file.
write_gdf(G, "output_file.gdf")
```

For detailed information on usage, please refer to its [official documentation](https://networkx-gdf.readthedocs.io).

## License

This package is released under the [BSD License](https://github.com/nelsonaloysio/networkx-gdf/blob/main/LICENSE.md).
fastzdp-redis 0.1.0
FastZDP框架体系下操作Redis的国产框架, 低代码开发, 简单易用, 提高企业项目开发效率
Requires Python: <4.0,>=3.12

# fastzdp_redis

FastZDP框架体系下操作Redis的国产框架, 低代码开发, 简单易用, 提高企业项目开发效率

## 环境搭建

### 通过docker启动Redis

```bash
docker run -p 6379:6379 -it redis/redis-stack:latest
```

## 版本发布

### v0.1.0

- FastZDPRedisClient类
- 封装get和set方法
vector-db-benchmark 1.0.0
Benchmarking tool for vector databases
Requires Python: >=3.6
Keywords: vector database benchmark milvus numpy

# Vector DB Benchmark

`vector_db_benchmark` is a Python package that allows you to benchmark vector databases. It enables you to run benchmarks on different vector database implementations under identical conditions, ensuring replicable and fair comparisons.

## Features

- **Benchmark any vector database implementation** that provides the required methods.
- **Replicable benchmarking configurations** using a fixed random seed.
- **Supports both on-disk and in-memory vector databases**.
- **Generates metrics and graphs** for ingestion time, search times, and memory usage.
- **Easy to use** with simple API and command-line interface.

## Installation

Install the package using `pip`:

```bash
pip install vector_db_benchmark
```
package-name-Alisson-Wendel 0.0.1
Pacote para estudo de conceitos de criação de pacotes
Requires Python: >=3.5

# package_name

Description. 
The package package_name is used to:
	- 
	-

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install package_name

```bash
pip install package_name
```

## Author
Alisson

## License
[MIT](https://choosealicense.com/licenses/mit/)
package-name-Alisson 0.0.1
Pacote para estudo de conceitos de criação de pacotes
Requires Python: >=3.5

# package_name

Description. 
The package package_name is used to:
	- 
	-

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install package_name

```bash
pip install package_name
```

## Author
Alisson

## License
[MIT](https://choosealicense.com/licenses/mit/)