semvec/pypi-packages huggingface dataset:
yaqd-gage 2026.1.0
yaq daemons for GaGe hardware
Requires Python: >=3.7

# yaqd-gage

[![PyPI](https://img.shields.io/pypi/v/yaqd-gage)](https://pypi.org/project/yaqd-gage)
[![Conda](https://img.shields.io/conda/vn/conda-forge/yaqd-gage)](https://anaconda.org/conda-forge/yaqd-gage)
[![yaq](https://img.shields.io/badge/framework-yaq-orange)](https://yaq.fyi/)
[![black](https://img.shields.io/badge/code--style-black-black)](https://black.readthedocs.io/)
[![ver](https://img.shields.io/badge/calver-YYYY.M.MICRO-blue)](https://calver.org/)
[![log](https://img.shields.io/badge/change-log-informational)](https://github.com/yaq-project/yaqd-gage/blob/main/CHANGELOG.md)

yaq daemons for [GaGe](http://www.gage-applied.com/) hardware

This package contains the following daemon(s):

- https://yaq.fyi/daemons/gage-chopping
- https://yaq.fyi/daemons/gage-compuscope

## driver installation

This package relies on GaGe's official Python interface, provided as part of their C SDK. A license for this SDK must be purchased from GaGe.

GaGe will provide you with a `.pyd` file: `PyGage3_64.pyd` or `PyGage3_32.pyd`. [This is essentially a Windows DLL with special Python functionality](https://docs.python.org/3/faq/windows.html#is-a-pyd-file-the-same-as-a-dll). You must put this file in your PYTHONPATH.

This open source software package is not officially supported by GaGe.

## maintainers

[Kent Meyer](https://github.com/kameyer226)
dir2chat 0.1.0a0
Generate an OpenAI Chat Completions-compatible JSON from all UTF-8 plaintext files in a directory.
Requires Python: >=2

# `dir2chat`

Generate an OpenAI Chat Completions-compatible JSON from all UTF-8 plaintext files in a directory.

## Use Cases

This tool is designed to help with a variety of tasks involving directory contents and large-language models, such as:

- **Codebase Summarization for LLMs**  
  Preparing a repository as an input for Chat Completions-compatible models, making it easy to "upload" a codebase as a
  conversational context.

- **Automated Project Documentation**  
  Quickly gather all plaintext documentation files (like `README.md`, `docs/`, etc.) and their contents for further
  summarization, analysis, or indexing.

## Installation

```
pip install dir2chat
```

## Usage

```
python -m dir2chat <directory> [options]
```

Options:

- `-o`, `--output`: Output JSON file (default: `-` for stdout).
- `--max-file-size`: Max size for files in bytes (default: `65536`, or 64 KB).

Example:

```bash
python -m dir2chat path/to/my/project -o chat.json --max-file-size 32768
```

## Output

The output is a JSON array of messages suitable for OpenAI Chat models, in the structure:

```
[
  {
    "role": "user",
    "content": "- README.md\n- src/\n  - main.py\n  - utils.py"
  },
  {
    "role": "user",
    "content": "README.md"
  },
  {
    "role": "user",
    "content": "<contents of README.md>"
  },
  ...
]
```

1. First message: The tree view of the directory.
2. Subsequent pairs: For each included file, a message with the file's relative path, then another with its content.

> **Only UTF-8-encoded, plaintext files below the size limit are included.** Skipped files are reported to stderr.

## Contributing

Contributions are welcome! Please submit pull requests or open issues on the GitHub repository.

## License

This project is licensed under the [MIT License](LICENSE).
gemseo-pyoptsparse 1.1.1
GEMSEO interface to pyoptsparse algorithms.
Requires Python: <3.14,>=3.10

<!--
Copyright 2021 IRT Saint Exupéry, https://www.irt-saintexupery.com

This work is licensed under the Creative Commons Attribution-ShareAlike 4.0
International License. To view a copy of this license, visit
http://creativecommons.org/licenses/by-sa/4.0/ or send a letter to Creative
Commons, PO Box 1866, Mountain View, CA 94042, USA.
-->

# gemseo-pyoptsparse


[![PyPI - License](https://img.shields.io/pypi/l/gemseo-pyoptsparse)](https://www.gnu.org/licenses/lgpl-3.0.en.html)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/gemseo-pyoptsparse)](https://pypi.org/project/gemseo-pyoptsparse/)
[![PyPI](https://img.shields.io/pypi/v/gemseo-pyoptsparse)](https://pypi.org/project/gemseo-pyoptsparse/)
[![Codecov branch](https://img.shields.io/codecov/c/gitlab/gemseo:dev/gemseo-pyoptsparse/develop)](https://app.codecov.io/gl/gemseo:dev/gemseo-pyoptsparse)

## Overview

GEMSEO interface to pyoptsparse algorithms.

## Installation

This plugin requires the package `pyoptsparse` with `SNOPT` support.
It shall be installed beforehand.

Install the latest version with `pip install gemseo-pyoptsparse`.

See [pip](https://pip.pypa.io/en/stable/getting-started/) for more information.

## Bugs and questions

Please use the [gitlab issue tracker](https://gitlab.com/gemseo/dev/gemseo-pyoptsparse/-/issues)
to submit bugs or questions.

## Contributing

See the [contributing section of GEMSEO](https://gemseo.readthedocs.io/en/stable/software/developing.html#dev).

## Contributors

- Francois Gallard
- Antoine Dechaume
- Nicolas Roussouly
oxgram 0.0.10
ㅤ
Requires Python: ~=3.10
Keywords: bot, bots, telegram

<p align="center">
 📦 <a href="https://pypi.org/project/oxgram" style="text-decoration:none;">Oxgram</a>
</p>


```python

from Oxgram.functions import Pyrogram

dcid = await Pyrogram.get01(update)

print(dcid)

```
njmtech-upload-blob 0.1.1
This is a simple FastAPI application to upload files to Vercel Blob storage.
Requires Python: >=3.11

# NJMTech Upload Blob API

## Tech Stack

This project is built using the following technologies:

*   🐍 **Python**: The core programming language.
*   ⚡ **FastAPI**: A modern, fast (high-performance) web framework for building APIs with Python 3.7+ based on standard Python type hints.
*   ☁️ **Vercel Blob**: A serverless, scalable, and cost-efficient object storage solution for the web.
*   🦄 **Uvicorn**: A lightning-fast ASGI server, used to run the FastAPI application.
*   .env **python-dotenv**: Manages environment variables, loading them from a `.env` file.
*   🛠️ **Werkzeug**: A comprehensive WSGI web application library, used here for secure filename handling.
*   🧪 **Pytest**: A mature full-featured Python testing framework.



This is a simple FastAPI application to upload files to Vercel Blob storage.

## Setup

1.  **Install dependencies:**

    ```bash
    pip install -r requirements.txt
    ```

2.  **Set up environment variables:**

    Create a `.env.local` file in the root of the project and add your Vercel Blob read-write token:

    ```
    BLOB_READ_WRITE_TOKEN="YOUR_BLOB_READ_WRITE_TOKEN"
    ```

    Replace `"YOUR_BLOB_READ_WRITE_TOKEN"` with your actual token.

3.  **Run the application:**

    ```bash
    uvicorn api.main:app --reload
    ```

    The application will be running at `http://127.0.0.1:8000`.

## Testing

To run the tests for this project, follow these steps:

1.  **Install test dependencies:**

    ```bash
    pip install -r tests/requirements.txt
    ```

2.  **Run the tests:**

    ```bash
    pytest tests/
    ```

## API Endpoint

### Upload File

*   **URL:** `/api/v1/upload`
*   **Method:** `POST`
*   **Headers:**
    *   `Authorization: Bearer YOUR_API_TOKEN`
*   **Form Data:** `file` (the file to upload)

**Example using `curl`:**

```bash
curl -X POST \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -F "file=@/path/to/your/file.txt" \
  http://127.0.0.1:8000/api/v1/upload
```
stackit-secretsmanager 0.4.0
STACKIT Secrets Manager API
Requires Python: <4.0,>=3.9

# stackit.secretsmanager
This API provides endpoints for managing the Secrets-Manager.



This package is part of the STACKIT Python SDK. For additional information, please visit the [GitHub repository](https://github.com/stackitcloud/stackit-sdk-python) of the SDK.


## Installation & Usage
### pip install

```sh
pip install stackit-secretsmanager
```

Then import the package:
```python
import stackit.secretsmanager
```

## Getting Started

[Examples](https://github.com/stackitcloud/stackit-sdk-python/tree/main/examples) for the usage of the package can be found in the [GitHub repository](https://github.com/stackitcloud/stackit-sdk-python) of the SDK.