semvec/pypi-packages huggingface dataset:
ted-editor 0.1.4
Terminal Text Editor with TUI
Requires Python: >=3.7


<div align="center">

<!-- TODO: Add a screenshot -->
<!-- TODO: Make the text in ted logo partially selected, and put a cursor around the selected area, use monospace font for the text -->

<img src="https://raw.githubusercontent.com/james4ever0/ted/master/logo/ted-black.jpeg" alt="logo" width="270"/>

<p align="center">A simple cross-platform TUI editor with a CLI and API using Textual</p>
<p align="center">
<a href="https://github.com/james4ever0/ted/blob/master/LICENSE"><img alt="License: WTFPL" src="https://img.shields.io/badge/license-UNLICENSE-green.svg?style=flat"></a>
<a href="https://pypi.org/project/ted-editor/"><img alt="PyPI" src="https://img.shields.io/pypi/v/ted-editor"></a>
<a href="https://deepwiki.com/James4Ever0/ted"><img src="https://deepwiki.com/badge.svg" alt="Ask DeepWiki"></a>
<a href="https://pepy.tech/projects/ted-editor"><img src="https://static.pepy.tech/badge/ted-editor" alt="PyPI Downloads"></a>
<a href="https://github.com/james4ever0/ted"><img alt="Code style: black" src="https://img.shields.io/badge/code%20style-black-000000.svg"></a>
</p>
</div>


## Installation
```bash
# without syntax highlight
pip install ted-editor

# with syntax highlight
pip install ted-editor[syntax]
```

### Key Features

1. **Dual Interface**:
   - CLI: `ted <filepath>`
   - API: `ted.edit(content, filepath)`

2. **File Handling**:
   - Prompt for file path if not provided
   - Ask for file creation if doesn't exist
   - Handle permission errors

3. **TUI Editor**:
   - Textual-based interface
   - Save with Ctrl+S or Save button
   - Quit with Ctrl+Q or Quit button
   - Shows modification status in title
   - Auto-save on quit if modified

4. **API Behavior**:
   - `content=None`: Load from file if exists
   - `filepath=None`: Memory-only editing
   - Returns edited content

5. **Cross Platform**:
   - Available in Windows, macOS, Linux

### Usage

**CLI:**
```bash
ted  # Prompts for file path
ted myfile.txt
```

**API:**
```python
from ted import edit

# Edit existing file
content = edit(filepath="existing.txt")

# Create new file
new_content = edit(content="New content", filepath="new.txt")

# Memory-only editing
temp_content = edit(content="Temporary text")
```

## Screenshots

![Demo](https://raw.githubusercontent.com/james4ever0/ted/master/logo/demo.png)

## See also

[edit](https://github.com/microsoft/edit) (Microsoft rewrite in Rust)

[textual-editor](https://github.com/kyrlian/textual-editor) (Most similar, with a directory tree tab)

[TED](https://texteditors.org/cgi-bin/wiki.pl?TED) (MS-DOS)

[ted](https://github.com/robdelacruz/ted) (Go implementation)
Topsis-Gazal-102217174 0.4
A Python implementation of the TOPSIS method.


---

# Topsis Implementation and Python Package

This repository contains the implementation of the **Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)**. It includes two components:

1. **Command-Line Python Program**  
2. **Python Package Published on PyPI**

---

## 1. Command-Line Python Program

This program calculates the TOPSIS scores and ranks for a given dataset.  

### How It Works:
- **Input File:**  
  The input file is a CSV file with three or more columns:
  - The first column contains the names of the objects/variables (e.g., M1, M2, M3, etc.).
  - The remaining columns contain numeric data.

- **Output File:**  
  The output file includes all columns from the input file with two additional columns:
  - `Topsis Score`
  - `Rank`

### Features:
- Handles exceptions for:
  - Incorrect input format.
  - Missing files.
  - Non-numeric values.
- Ensures weights and impacts are correctly formatted.
- Validates the consistency of input dimensions (number of weights, impacts, and columns).

### Usage:
Run the program through the command line:

```bash
python <program.py> <InputDataFile> <Weights> <Impacts> <ResultFileName>
```

**Example:**

```bash
python Topsis-Gazal-102217174.py data.csv "1,1,1,2" "+,+,-,+" result.csv
```

---

## 2. Python Package on PyPI

https://pypi.org/project/Topsis-Gazal-102217174/ 

### User Guide:
- Install the package using `pip`:
  ```bash
  pip install Topsis-Gazal-102217174
  ```
- Run the TOPSIS calculation from the command line:
  ```bash
  Topsis-Gazal-102217174 <InputDataFile> <Weights> <Impacts> <ResultFileName>
  ```
  **Example:**
  ```bash
  Topsis-Gazal-102217174 data.csv "1,1,1,2" "+,+,-,+" result.csv
  ```

### Testing:
The package was thoroughly tested by installing it from PyPI and running multiple test cases.

---


## Resources and References
- [Learn TOPSIS](https://www.youtube.com/watch?v=kfcN7MuYVeI)
- [How to Publish Python Packages to PyPI](https://medium.com/@joel.barmettler/how-to-upload-your-python-package-to-pypi-65edc5fe9c56)

---
udot-wrangler 0.1.2
Network Wrangler parameters for UDOT
Requires Python: >=3.10

UDOT Wrangler is a Python library for UDOT-related paramters and utilities with Network Wrangler.

## System Requirements
UDOT Wrangler does require Python 3.7+. If you have a different version of Python installed (e.g. from ArcGIS), conda or a similar virtual environment manager can care of installing it for you in the installation instructions below.

## Installation
UDOT Wrangler is available on PyPI.

### Latest Official Version
Users can install via standard pip command.
```bash
pip install udot-wrangler
```

Users can also install via package managers such as uv
```bash
uv add udot-wrangler
```

### From GitHub
```bash
pip install git+https://github.com/network-wrangler/udot_wrangler.git@main#egg=udot_wrangler
```

If you wanted to install from a specific tag/version number or branch, replace `@main` with `@<branchname>`  or `@tag`

### From Clone

If you are going to be working on UDOT Wrangler locally, you might want to clone it to your local machine and install it from the clone.  The -e will install it in [editable mode](https://pip.pypa.io/en/stable/reference/pip_install/?highlight=editable#editable-installs).

If you have [GitHub desktop](https://desktop.github.com/) installed, you can either do this by using the GitHub user interface by clicking on the green button "clone or download" in the [main UDOT wrangler repository page](https://github.com/network-wrangler/udot_wrangler).

Otherwise, you can use the command prompt to navigate to the directory that you would like to store your UDOT wrangler clone and then using a [git command](https://git-scm.com/downloads) to clone it.

```bash
cd path to where you want to put wrangler
git clone https://github.com/network-wrangler/udot_wrangler
```

Then you should be able to install UDOT Wrangler in "develop" mode.

```bash
cd udot_wrangler
pip install -e .
```
ansi-terminal 0.2.0
Add your description here
Requires Python: >=3.10

# Ansi Terminal

![Author](https://img.shields.io/badge/made%20by-Luca%20BARBISAN-blue?style=plastic)
![License](https://img.shields.io/badge/license-MIT-blue.svg?style=plastic)
![Python](https://img.shields.io/badge/python-3.6%2B-blue?style=plastic)

A lightweight Python library for styling and coloring terminal output using ANSI escape codes. Easily print text in bold, underlined, or colored formats across supported terminals.


## Features 🪴

- Foreground and background colors
- Text styles: bold, italic, underline, strikethrough
- RGB color support (24-bit color)
- Nestable and composable styles
- Reset and clear formatting helpers
- Cross-platform compatibility (Windows via colorama)

## Installation 💻

```bash
pip install ansi-terminal
```

## Example 🌻

```python
from ansi_terminal import ansi_print, Color, fg, bg, style

ansi_print(f", Color, fg, bg, style", color=Color(fg.red, bg.black, style.italic))
```
___

## Contributing 🌱

1. **Clone the repository**:  
   ```bash
   git clone https://...git
   ```

2. **Create your feature branch**
   ```bash
   git checkout develop
   git checkout -b feature/YourFeature
   ```

3. **Commit your changes**:  
   ```bash
   git commit -m "Add your feature description"
   ```

4. **Push your branch** to GitHub:  
   ```bash
   git push origin feature/YourFeature
   ```

4. **Open a merge request** to the `develop` branch.

For major changes, please open an issue first to discuss what you would like to change.
ufsdk 0.1.0
UCloud UFile SDK for Python
Requires Python: >=3.7

# ufsdk

A lightweight SDK for signing UCloud UFile presigned URLs (GET, PUT).

## Example

```python
from ufsdk import UCloudClient
client = UCloudClient(...)
url = client.gen_presigned_get_url("myfile.txt", timedelta(hours=1))
```
copilot-service 1.0.1
A Copilot-like API service for code completions
Requires Python: >=3.7

# Copilot Service API

This Flask application provides an API service for AI-powered code completions, mimicking GitHub Copilot functionality.

## Features
- Generate code completions with configurable AI models
- Token usage tracking
- Prompt customization
- Caching for efficiency
- Interactive playground for testing

## PyPI Installation

```bash
pip install copilot-service
```

## GitHub Installation
```bash
pip install git+https://github.com/yourusername/copilot-service.git
```

## Usage

### Set API Keys
The service uses LiteLLM for model access. To declare API keys, use LiteLLM's standard format. For example:

```bash
export OPENAI_API_KEY=your-api-key-here
# Or for other providers
export COHERE_API_KEY=your-api-key-here
export ANTHROPIC_API_KEY=your-api-key-here
```

### Start the Service
```bash
copilot-service
```

### Configuration
You can also configure the default model and token limits:
```bash
export DEFAULT_MODEL="gpt-3.5-turbo"
export DEFAULT_MAX_TOKENS=100
copilot-service
```

## API Endpoints

### POST /copilot/completions
Get AI-generated code completions

**Request Body:**
```json
{
  "file_contents": "def hello_w",
  "cursor_position": 10
}
```

**Response:**
```json
{
  "completion": "orld():\n    print(\"Hello World!\")",
  "token_metadata": {
    "prompt_tokens": 120,
    "completion_tokens": 20,
    "total_tokens": 140
  }
}
```

### POST /copilot/preview
Preview the prompt being sent to the AI

### GET /version
Get service version information

## Testing

Run tests with:
```bash
python test.py
```

## License
GNU General Public License v3.0

## Interactive Playground
Access the playground at `http://localhost:5000`
- Type code and click "Get Completion" for ghost text suggestions
- Test API endpoints directly from the browser
mcp-server-baige 0.1.0
一个 MCP 服务器，提供基于百鸽查游戏王卡的工具
Requires Python: >=3.10

# BaiGe MCP Server

一个 MCP 服务器，提供基于百鸽查游戏王卡的工具

### Install

```bash
uvx mcp-server-baige
```

### Tools

`query_ygo_card(query: str) -> str | None`

- 通过 query 查询，得到一张游戏王卡的信息