semvec/pypi-packages huggingface dataset:
Data-extractor-txt-to-csv 2.1.0
A Python package to extract data from TXT filenames and save it to CSV.
Requires Python: >=3.6

# Data Extractor TXT to CSV

## Overview
`Data_extractor_txt_to_csv` is a Python package that processes `.txt` files in a specified folder. It extracts specific parts of filenames and saves them as `.csv` files.

## Features
- Process multiple `.txt` files in a folder.
- Extracts a specific part of the filename based on `_` separators.
- Saves the results into a `.csv` file with a semicolon (`;`) delimiter.
- Ensures unique extracted values in the CSV file.

## Installation
You can install the package from PyPI using:
```sh
pip install Data_extractor_txt_to_csv
```
## Usage
After installing, you can run the script using:

```shell
process-file
```

## License
This project is licensed under the MIT License.

## Author
Created by Terriculum.
online-proxy-scraper 1.0.2
A Python package for scraping free proxy lists from various online sources.
Requires Python: >=3.7

# ProxyScraper

## Overview
ProxyScraper is a Python package designed to scrape free proxy lists from various online sources. It uses multithreading to enhance performance and efficiently gather proxies.

## Features
- Fetches free proxies from multiple sources
- Uses multithreading for better performance
- Automatically formats proxies into `IP:PORT`
- Simple and easy-to-use interface

## Installation
You can install ProxyScraper via GitHub or PyPI.

### Install from GitHub
```sh
pip install git+https://github.com/alfarttusie/proxyscraper.git
```

### Install from PyPI
```sh
pip install online-proxy-scraper
```

## Usage
```python
from proxyscraper import ProxyScraper

scraper = ProxyScraper()
print(scraper.list)  # List of formatted proxies
```

## Dependencies
- `requests`

## License
MIT License

## Author
[alfarttusie](https://github.com/alfarttusie)
beep-notifications 0.2.2
Email notifications are a thing of the past, send notifications to messengers

# Beep

This library will help you integrate notifications and authorization via Telegram through our Beep platform.

## Preparation

First, you must log into the developer panel on the official [Beep website](https://beepme.org/login) and create your
project.

After that, you must copy the ID of your project. It serves as a token, so be careful and keep it secret.

## Library usage
### Install
Install this library using
```sh
pip install beep-notifications
```

### Connecting to the project
Using your ``project_id`` create ``BeepNotify`` instance.
```python
from beep_notifications import BeepNotify

beep = BeepNotify('some_project_id')
```

### Creating link code
Use ``get_link_code()`` method to get link code for your project.
```python
link_code = beep.get_link_code()
```

### Checking link code status
Use ``check_link_code(code)`` method to check link code status. It returns ``accepted``, ``beep_code``, ``username``.
```python
accepted, beep_code, username = beep.check_link_code("12345")
```

### Checking is user a subscriber
Use ``check_subscription(user_iden)`` method to check if user is subscribed to your project to be able to get notifications from it. ``user_iden`` can be a username or a Beep code.
```python
subscribed = beep.check_subscription("spiritedRaisins6")
```

### Sending notifications
Use ``send_notification(title, body, username)`` method to send notifications.

Using username as receiver identification
```python
beep.send_notification("Hello", "I SAID HELLOOOOO", "spiritedRaisins6")
```

Using Beep code as receiver identification
```python
beep.send_notification("Hello", "I SAID HELLOOOOO", "665123731")
```
### Sending auth code
Use ``send_auth_code(user_iden)`` method to send auth code to user, ``user_iden`` can be a username or a Beep code.
```python
beep.send_auth_code("spiritedRaisins6")
```

### Try to authenticate user with auth code
Use ``get_token(user_iden, auth_code)`` method to user authentication, ``user_iden`` can be a username or a Beep code.
```python
token = beep.get_token("spiritedRaisins6", "1234")
```

### Validate a token
Use ``validate_token(token, uac)`` method to validate a token, ``uac`` is 'username_as_code', if uac is True, then return a username of the token owner, else Beep code.
This method returns 3 values: ``validation_result``, ``user_iden`` and ``error``.
```python
res, user, errpr = beep.validate_token("some_token", uac=True)
```

## Contact me!

[Beep Telegram Chat](https://t.me/beepme_org)<br>[X / Twitter](https://x.com/worldz_tech) <br> [Email felix.trof@gmail.com](mailto:felix.trof@gmail.com) <br> [Telegram](https://t.me/dbaykalov) <br>
pyAOBS 0.1.1
A package for seismic data processing and visualization
Requires Python: >=3.7

# pyAOBS

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Python 3.7+](https://img.shields.io/badge/python-3.7+-blue.svg)](https://www.python.org/downloads/release/python-370/)

A Python package for seismic data processing and visualization, with a focus on ZELT format velocity models.

## Features

- Read and write ZELT format velocity models (v.in files)
- Process and manipulate velocity models
- Interpolate velocities at arbitrary points
- Average layer velocities
- Export to various formats
- Visualization tools using PyGMT and Matplotlib
- Support for time and depth domain data

## Installation

### From PyPI (Recommended)
```bash
pip install pyAOBS
```

### From Source
```bash
git clone https://github.com/go223-pyAOBS/pyAOBS.git
cd pyAOBS
pip install -e .
```

## Dependencies

- numpy >= 1.20.0
- xarray >= 0.16.0
- scipy >= 1.6.0
- matplotlib >= 3.3.0
- pandas >= 1.2.0
- pygmt >= 0.5.0

## Usage

```python
from pyAOBS.model_building import ZeltVelocityModel2d, EnhancedZeltModel

# Basic usage
model = ZeltVelocityModel2d("velocity.in")
velocity = model.at(100.0, 1.5)  # Get velocity at point (100.0, 1.5)

# Enhanced features
enhanced_model = EnhancedZeltModel("velocity.in")
avg_velocities = enhanced_model.compute_average_velocities()

# Visualization
from pyAOBS.visualization import ZeltModelVisualizer

visualizer = ZeltModelVisualizer(model)
visualizer.plot_zeltmodel(
    output_file="velocity_model.png",
    title="Velocity Model",
    colorbar_label="Velocity (km/s)"
)
```

## Documentation

For detailed documentation and examples, please visit our [documentation page](https://go223-pyAOBS.github.io/pyAOBS).

## Contributing

We welcome contributions! Please feel free to submit a Pull Request.

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

## Author

Haibo Huang (go223@scsio.ac.cn)

## Citation

If you use pyAOBS in your research, please cite:

```bibtex
@software{pyAOBS2024,
  author = {Haibo Huang},
  title = {pyAOBS: A Python Package for Seismic Data Processing and Visualization},
  year = {2024},
  publisher = {GitHub},
  url = {https://github.com/go223-pyAOBS/pyAOBS}
}
```