semvec/pypi-packages huggingface dataset:
shmate 0.3.1
A command-line application integrating with OpenAI's API.

# ShellMate

ShellMate is a command-line application that interfaces with OpenAI's API to execute shell commands and provide intelligent responses. It orchestrates chat management, command extraction, and response handling to offer a seamless user experience.

## Installation

Ensure Python 3.6+ is installed on your system.

The recommended way to install this application is throught pip:

```shell
pip install shmate
```

1. **Create and activate a virtual environment:**

   ```shell
   python -m venv .venv
   source .venv/bin/activate  # On Windows use .venv\\Scripts\\activate
   ```

2. **Install dependencies:**

   ```shell
   pip install .
   ```

3. **Environment Setup:**
   The package provides a `.env.example` file. You will be prompted to modify this file using your API credentials of choice. You must restart the tool after editing environment variables.

## Usage

Run the application using:

```shell
shellmate
```

Follow the on-screen prompts to interact with the AI model, execute commands, and receive feedback.

## License

This project is licensed under the MIT License. See the LICENSE file for more details.
datahawk 0.0.4
Text data browser for visualization and analysis
Requires Python: >=3.8
Keywords: data visualization, research, natural language processing

<p align="center">
  <img src="static/datahawk-title.png" width=40%>
</p>

---

A lightweight app that makes browsing and analyzing text data a breeze.

#### Key Features

🔍 **Intuitive Navigation**: Effortlessly browse local (or remote) data in HuggingFace, JSONL, etc., formats.<br>
⚡ **Efficient Browsing**: Stream large local (or remote) datasets without loading (or downloading) in memory.<br>
🚀 **Powerful Analysis**: Easily filter and sort data for better insights.<br>
💻 **Pretty-Print Code**: Human-friendly visualization of code embedded in your data.

Experience seamless data browsing and analysis with Datahawk 🦅!

<p align="center">
  <img src="static/demo.gif" width=90%>
</p>

Alternatives include: [Lilac](https://www.lilacml.com/), [HuggingFace Dataset Viewer](https://huggingface.co/docs/datasets-server/).


## Instructions

#### Install

Installation requires `python>=3.8`.

```shell
pip install datahawk
```

#### Run

Launch the app from anywhere as:

```shell
datahawk
```

This will start the application at `localhost:5009`.

Specify a custom port number as:

```shell
datahawk -p PORT
```

This will start the application at `localhost:PORT`.

#### Usage

Usage is quite intuitive! You can find on-screen instructions by hovering over the information icons ℹ️.


## License

Datahawk has an MIT license, as found in the [LICENSE](LICENSE) file.


## Acknowledgements

* [Hawk icon](https://www.flaticon.com/free-icon/eagleemblem_14733103) made by [IconBaandar](https://www.flaticon.com/authors/iconbaandar) from [Flaticon](https://www.flaticon.com).
receipt-print 0.0.1
receipt printer CLI
Requires Python: >=3.11

# receipt-print

A simple CLI tool for printing text on thermal receipt printers.

## Installation

```bash
pip install receipt-print
```

## Usage

Print piped text directly:
```bash
echo "hello" | receipt-print
```

Print the contents of files:
```bash
receipt-print cat file1.txt file2.txt
```

Print text directly:
```bash
receipt-print echo "hello" "world"
receipt-print echo -l "line 1" "line 2"  # use newlines instead of spaces
```

Count how many lines would be printed:
```bash
receipt-print count file.txt
man ls | receipt-print count
```

## Configuration

Configure using environment variables ([see python-escpos documentation](https://readthedocs.org/projects/python-envconfig/en/latest/)):

- `RP_VENDOR`: USB vendor ID (default: 04b8)
- `RP_PRODUCT`: USB product ID (default: 0e2a)
- `RP_PROFILE`: Printer profile (default: TM-T20II)
- `RP_HOST`: Network printer IP address (optional, fallback if USB fails)
- `RP_CHAR_WIDTH`: Character width per line (default: 72)
- `RP_MAX_LINES`: Maximum lines allowed without confirmation (default: 40)
pyMalbolge 0.0.1
Simple Malbolge(https://en.wikipedia.org/wiki/Malbolge) interpreter in python
Requires Python: >=3.8

# pyMalbolge

This is fork from https://github.com/Avantgarde95/pyMalbolge

Simple Malbolge(https://en.wikipedia.org/wiki/Malbolge) interpreter in python

Fix:
Integer division syntax

Add:
Eval function for inline evalation


TODO:
Support Malbolge20 and Malbolge Unshackled.
Add Debug mode