semvec/pypi-packages huggingface dataset:
binypt-cli 1.0.4
Command line tool for downloading data charts from Binance
License: MIT
Requires Python: >=3.10,<4.0
Keywords: crypto,binance,cli

# Binypt - Cryptocurrency Chart Data Downloader

[![PyPI - Version](https://img.shields.io/pypi/v/binypt-cli?color=pink)](https://github.com/Tejaromalius/Binypt-cli/blob/main/pyproject.toml)
[![PyPI - License](https://img.shields.io/pypi/l/binypt-cli?color=blue)](https://github.com/Tejaromalius/Binypt-cli/blob/main/LICENSE)
[![PyPI - Status](https://img.shields.io/pypi/status/binypt-cli?color=%20%23239b56%20)](https://pypi.org/project/binypt-cli/)

## Overview

**Binypt** is a versatile Python command-line utility tool that allows you to effortlessly download historical cryptocurrency chart data from the Binance exchange. Whether you're a trader, researcher, or just a crypto enthusiast, Binypt simplifies the process of collecting and exporting candlestick data for your preferred trading pairs and time intervals.

## Installation

Before using Binypt, make sure you have the required dependencies installed:

```bash
pip install binypt-cli
```

## Usage

Binypt offers a range of options to tailor your data collection. Here's how to use it:

```bash
$ binypt -p <TRADING_PAIR> -i <INTERVAL> -od <OPEN_DATE> -cd <CLOSE_DATE> [OPTIONS]
```

### Required Arguments

- `-p`, `--trading-pair`: Specify the trading pair symbol (e.g., BTCUSDT).
- `-i`, `--interval`: Set the candlestick interval (e.g., 1h, 1d, 1w).
- `-od`, `--open-date`: Define the start date for data collection (YYYY-MM-DD/HH:mm:ss).
- `-cd`, `--close-date`: Define the end date for data collection (YYYY-MM-DD/HH:mm:ss).

### Optional Arguments

- `-o`, `--output-path`: Path to the output file for data storage. Supported formats: .csv, .excel, .pkl. (Default: binypt_data.csv)
- `-hr`, `--add-hr-time`: Include human-readable time format in the output data.
- `-v`, `--verbose`: Enable verbose logging for debugging purposes.

## Examples

### Basic Usage

Download 1-hour candlestick data for the BTCUSDT trading pair from January 1, 2023, to January 10, 2023, and save it as "btc_data.csv":

```bash
$ binypt -p BTCUSDT -i 1h -od 2023-01-01/00:00:00 -cd 2023-01-10/23:59:59 -o btc_data.csv
```

### Verbose Mode

Enable verbose logging to get detailed information during data retrieval:

```bash
$ binypt -p BTCUSDT -i 1h -od 2023-01-01/00:00:00 -cd 2023-01-10/23:59:59 -v
```

### Human-Readable Time Format

Include human-readable time format in the output data:

```bash
$ binypt -p BTCUSDT -i 1h -od 2023-01-01/00:00:00 -cd 2023-01-10/23:59:59 -hr
```

## Output

Binypt will download the requested data and save it in the specified format and file path. The data will be ready for further analysis or visualization.

## License

This software is distributed under the MIT License. You are free to use, modify, and distribute it as needed. Please refer to the LICENSE file for more details.

**Happy trading, and may your charts always be green!** 🚀💰

---
[![Generated by ChatGPT](https://img.shields.io/badge/Generated%20by-ChatGPT-45b39d.svg)](https://chat.openai.com/)
odp-sdk-python 0.4.1
ODP Python SDK
License: MIT
Requires Python: >=3.10,<4.0

<a href="https://www.oceandata.earth/">
    <img src="assets/ODP-SDK.png" alt="ODP SDK logo" title="ODP" align="right" height="100" />
</a>


# ODP Python SDK

Connect to the Ocean Data Platform with Python through the Python SDK. Download queried ocean data easily and efficiently into data frames, for easy exploring and further processing in your data science project.

## Documentation

[WIP]

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install the Ocean Data Platform Python SDK.

```bash
pip3 install odp_sdk
```
 
## Usage

*Note: Accessing the Ocean Data Platform requires an authorzed account. Contact ODP to require one.*

```python
from odp_sdk.client import OdpClient

client = OdpClient()

for item in client.catalog.list():
     print(item)
```

Examples can be found in /examples.
binypt-lib 2.3.7
Library to download data charts from Binance
License: MIT
Requires Python: >=3.10,<4.0
Keywords: crypto,binance

# Binypt: A Python Library for Cryptocurrency Data Retrieval and Processing

[![PyPI - Version](https://img.shields.io/pypi/v/binypt-lib?color=pink)](https://github.com/Tejaromalius/Binypt-lib/blob/main/pyproject.toml)
[![PyPI - License](https://img.shields.io/pypi/l/binypt-lib?color=blue)](https://github.com/Tejaromalius/Binypt-lib/blob/main/LICENSE)
[![PyPI - Status](https://img.shields.io/pypi/status/binypt-lib?color=%20%23239b56%20)](https://pypi.org/project/binypt-lib/)

## Overview

**Binypt** is a Python library designed for retrieving historical cryptocurrency price data from the Binance exchange. It allows you to specify trading pairs, time intervals, and date ranges to download and work with historical price data efficiently. This library is a helpful tool for anyone interested in analyzing or visualizing cryptocurrency price trends.

## Features

- Retrieve historical cryptocurrency price data from Binance.
- Specify trading pairs, time intervals, and date ranges.
- Export data in various formats such as CSV, Excel, or Pickle.
- Added human readable dates to the chart.

## Installation

You can install Binypt using `pip`:

```bash
pip install binypt-lib
```

## Usage

Here's a brief overview of how to use Binypt:

```python
from binypt import Binypt

# Initialize Binypt
binypt = Binypt()

# Set data retrieval parameters
binypt.set_arguments("BTCUSDT", "1h", "01/09/2023-00:00:00", "10/09/2023-23:59:59")

# Fetch cryptocurrency price data
binypt.retrieve_data()

# Export data to a CSV file
binypt.export("crypto_data.csv")

# Add human-readable timestamps
binypt.add_human_readable_time()

# Show progress bar and log messages
binypt.set_verbosity(show_bar=True, show_log=True)

# Access the data as a Pandas DataFrame
price_data = binypt.get_data()

# You can now perform various data analysis or visualization tasks with the price_data DataFrame
```

## Contributions

Contributions to this project are welcome. Feel free to submit bug reports, feature requests or pull requests!

## Documentation

To deep dive in on how this library functions, please refer to the [documentation](DOCUMENTATION.md)

---

[![Generated by ChatGPT](https://img.shields.io/badge/Generated%20by-ChatGPT-45b39d.svg)](https://chat.openai.com/)
hf-torrent 0.0.1-2401021918
A tool to download HuggingFace models via BitTorrent.
License: MIT

## HF-Torrent

This repository contains an experimental torrent-style download for model weights in Hugging Face.

The core implementation is `main_hub.py`, which downloads files from Hugging Face and converts them into seedable torrents.

## How to use

`pip install hf-torrent`

Before launching downloads, make sure you have [aria2c](https://aria2.github.io/) installed and 

<details>
<summary>  run the following command in a separate terminal </summary>

```bash
aria2c --enable-rpc --rpc-listen-all \
    --max-upload-limit=4M \
    --optimize-concurrent-downloads=true \
    --bt-detach-seed-only=true \
    --seed-ratio=10.0  
```
</details>


Then you can start using HF-Torrent with the following command:

```bash
hf-torrent <your target repo>
```

[![asciicast](https://asciinema.org/a/4ppEU7HDGzUqwReSIosXOkCs9.svg)](https://asciinema.org/a/4ppEU7HDGzUqwReSIosXOkCs9)


Or if you have your preferred torrent clients, you can pull the torrent file only

```bash
hf-torrent --get-torrent <your target repo>
```


## How to contribute

### Installation

To install, run the following command:

`pip install -r requirements.txt`


### Seeding

It is easy to contribute to seeding! First, change `--seed-ratio=0` (from 10 to 0) when launching the `aria2c` RPC. Setting `0` means the daemon will seed infinitely.
Next, change the upload bandwidth limit to a value that suits you, for example: `--max-upload-limit=20M` (4M by default).

After making these changes, launching seeding is as simple as downloading models. You can start seeding by running the following script and help distribute your favorite models!

```bash
python download.py <your target repo>

```

### Create

To create a popular torrent, run the following command:

`python generate_popular_torrents.py -r efederici/retnet-120m`

This script will (1) download model files from Hugging Face, (2) iterate through the folder, (3) generate torrents for each file, and then put them under `hf-torrent-store/{repo}`.

We are looking for a wanted model list. Please open an issue if you have any favorite models to share.