semvec/pypi-packages huggingface dataset:
valve-gfx-ci.gfxinfo 0.1.4
Generate a list of tags that describe the environment running a GFX workload
Requires Python: >=3.6

# GFXInfo

Access the list of supported GPUs, from their codename to the environment they
are used in. The primary purpose is to generate a list of tags that can be used
to compare the results coming from machines running automated testing.

## How to

```
$ pipx install valve_gfx_ci.gfxinfo[vulkan]
$ gfxinfo
```

The `gfxinfo` command will print generated tags for the current machine
valve-gfx-ci.salad 0.0.2
Valve GFX CI's serial multiplexer
Requires Python: >=3.6

# SALAD

SALAD provides automatic mapping between serial consoles and their attached
test machine. This is done with a service running by default on port 8006
and a REST interface running on port 8005.

## REST interface

The REST API provides the following endpoints:

### GET /api/v1/machine/

List of machines that have been discovered using the `SALAD.machine_id=...` scheme.

### GET /api/v1/machine/$machineid

Details about the machine identified by `$machineid`.

### POST /api/v1/machine/$machineid/reset

Trigger a reset of the serial console associated to the machine identified by `$machineid`.

Return codes:

* `200`: Success
* `501`: No console associated to this machine
* `503`: Tried but failed to perform the reset

## Configuration

SALAD's configuration is done through environment variables:

* `SALAD_PORT`: TCP port to use for the REST interface (default: `8005`)
* `SALAD_TCPCONSOLE_PORT`: TCP port to use for the TCP console (default: `8100`)
* `SALAD_CONSOLE_USB_RESET_POWER_OFF_TIME`: Number of seconds a USB-based serial console should remain powered off to
  perform a successful reset (default: `3` seconds)
* `SALAD_CONSOLE_USB_RESET_DISABLE`: Disable resetting of USB-serial adapters,
  it is required in case of using containers not running on top of b2c (both
  privileged and unprivileged).
* `LISTEN_PID` and `LISTEN_FDS`: See Systemd's socket activation scheme
surf-scrap 0.0.2
Une bibliothèque pour scraper les données de surf-report.com
Requires Python: >=3.7

# 🏄‍♂️ surf_scrap

`surf_scrap` est une bibliothèque Python légère conçue pour extraire facilement les données de prévisions météo du site **Surf-Report.com**. 

Elle permet de récupérer les informations sur la taille des vagues, la vitesse du vent et son orientation pour n'importe quel spot répertorié, et de les sauvegarder directement dans un fichier CSV.

## 🚀 Installation

Si vous avez le dossier du projet, installez-le localement via le terminal :
```bash
pip install . 
pip install surf_scrap
```
## 🛠 Utilisation

La bibliothèque propose une fonction unique et simple : `scrape_surf_report`. Elle permet de choisir n'importe quel spot de surf-report.com et de sauvegarder les résultats où vous le souhaitez.

```python
from surf_scrap import scrape_surf_report
```
# URL du spot (ex: Carcans ou Moliets)
url = "https://www.surf-report.com/meteo-surf/carcans-plage-s1013.html"

# Emplacement personnalisé pour le fichier CSV
destination = "data_surf/data_surf.csv"

# Lancement de la fonction
scrape_surf_report(url, destination)

## 📊 Données extraites
Le package extrait les informations essentielles pour chaque créneau horaire :

Day : Le jour de la semaine.

Hour : L'heure de la prévision.

Waves_size : La hauteur des vagues (ex: 1m20).

Wind_speed : La force du vent (ex: 15km/h).

Wind_direction : L'orientation (ex: Offshore / Side-shore).

Pour mettre ces sections dans ton fichier README.md, il te suffit d'ouvrir ton fichier avec un éditeur de texte (comme VS Code, Notepad++, ou même le Bloc-notes) et de copier-coller le texte brut.
eic-codebase-analysis 0.1.1
A library for codebase analysis
Requires Python: >=3.7

# Codebase Analysis Utils

## Overview

`eic-codebase-analysis` is a Python library designed to assist in the analysis of code repositories and large codebases. It leverages advanced analysis techniques and AI to provide deep insights into project structure, components, functionality, and documentation.

## Installation

```bash
pip install eic-codebase-analysis
```

## Tools

This library provides a set of modular tools for different analysis tasks:

### 1. Repository Structure Extractor
*   **Purpose**: Extracts the directory and file structure of repositories without including file contents.
*   **Output**: Markdown tree structure.
*   **Usage**:
    ```bash
    python -m eic_codebase_analysis.repository_structure_extractor.main --root ./path/to/repo
    ```
*   **Documentation**: [Read more](src/eic_codebase_analysis/repository_structure_extractor/README.md)

### 2. Detailed Code Content Extractor
*   **Purpose**: Generates a single Markdown document containing both the directory structure and the full contents of files (in code blocks). Ideal for RAG contexts.
*   **Output**: Markdown with file contents.
*   **Usage**:
    ```bash
    python -m eic_codebase_analysis.detailed_code_content_extractor.main --root ./path/to/repo
    ```
*   **Documentation**: [Read more](src/eic_codebase_analysis/detailed_code_content_extractor/README.md)

### 3. Repository File Metadata Generator
*   **Purpose**: Uses AI (Gemini) to generate descriptive metadata for each file. Can output as sidecar files, a single aggregate file, or per-folder summaries.
*   **Output**: AI-generated summaries and documentation for files.
*   **Usage**:
    ```bash
    python -m eic_codebase_analysis.repository_file_metadata_generator.main --root ./path/to/repo --model gemini-1.5-pro
    ```
*   **Documentation**: [Read more](src/eic_codebase_analysis/repository_file_metadata_generator/README.md)

### 4. Hierarchical Project Metadata Generator
*   **Purpose**: Generates AI metadata at three levels: File (sidecar), Folder (summary of contents), and Project (high-level overview).
*   **Output**: Hierarchical Markdown documentation (`.ai-meta.md`, `.folder-ai-meta.md`, `project.ai-meta.md`).
*   **Usage**:
    ```bash
    python -m eic_codebase_analysis.hierarchical_project_metadata_generator.main --root ./path/to/repo --model gemini-1.5-pro
    ```
*   **Documentation**: [Read more](src/eic_codebase_analysis/hierarchical_project_metadata_generator/README.md)

## Integration

These tools are designed to be part of a broader ecosystem of AI-driven development tools. They can be integrated with existing libraries for Retrieval Augmented Generation (RAG) and dataset preparation.

## Requirements

*   Python 3.x
*   `google-generativeai` (for AI-powered tools)
underscores 0.0.4
_ allows you to write Python code using only _.
Requires Python: >=3.9
Keywords: _, underscore, encoding, joke

# `_`

`_` allows you to write Python code using only `_`.

## Installation

> [!TIP]
> It is highly recommended to use a virtual environment for proper installation of the `_.pth` file.

```shell
python -m pip install underscores
```

[Python 3.9](https://www.python.org/downloads/) or a newer version is required.

## Usage

The following script is a "Hello, world!" program which can be executed by the Python interpreter:

```python
# coding: _
_ ____ _ _____ _ ____ __ _ _ ___ ______ ____ _ ____ _ ___ _ ____ __ ___ _ __ _
_____ _ _ ______ _____ _ ___ _ _ _ ___ _____ ______ _ ____ _ _ _ ____ _ _ _ ____
_ ____ _ __ __ ___ _ _ ______ ___ _ ____ __ ______ _ ____ _ ____ _ ____ __ _ _
____ _ _ _ ___ _____ _____ _ _ ______ ____ _ _ ______ _____ _ __ _ ______
```

You can generate a script with `_`:

```python
print('print("Hello, world!")'.encode("_").decode("utf-8"))
```

A `_` command is also provided:

```shell
_ script1.py > script2.py
# or
echo 'print("Hello, world!")' | _ > script.py
```

## Troubleshooting

If you get `SyntaxError: invalid syntax`, make sure the line `# coding: _` is present at the top of your script.

If you get `SyntaxError: encoding problem: _`, follow the steps below to make sure the `_` encoding is registered on startup:

1. Run `SITE_PACKAGES=$(python -c 'import sysconfig; print(sysconfig.get_path("purelib"))')` to get the path to the Python site-packages directory.
2. Run `echo "import underscores" > "$SITE_PACKAGES/_.pth"` to register the `_` encoding on startup.

> [!NOTE]
> If using PowerShell, use `$SITE_PACKAGES` instead of `SITE_PACKAGES` to assign the variable.

This issue is commonly encountered when installing `_` into the user site-packages.

## Credits

`_` is a port of [`_`](https://github.com/mame/_) from Ruby to Python.
Please check out the original creator [mame](https://github.com/mame).

Big thanks to [shailist](https://github.com/shailist) for [this](https://shailist.github.io/posts/python-source-preprocessor-custom-encoding/) awesome post about custom encodings.

## License

[MIT License](LICENSE.txt)