semvec/pypi-packages huggingface dataset:
filewalker 1.0.2
Searches hard drives/given path for files specified by file extension
License: MIT

# Description

Searches hard drives/given path for files specified by file extensions

# Installation

`pip install filewalker`

# Usage

**From command line:**

`python -m filewalker [-h] [--path PATH] [--files FILES] [--overrideDefaultFileTypes | --no-overrideDefaultFileTypes | -o]`

| Option | Short | Type | Default | Description |
|---|---|---|---|---|
|--path | -p | String | - | Path which shall be searched. If no path is provided, all available drives will be searched |
|--files | -f | String[] | [] | Comma separated list of file type to be searched for: pdf,jpg,txt |
|--overrideDefaultFileTypes | -o | Boolean | False | If true, the default file types will be overwritten. |

**Default File Types**:

`pdf, doc, docx, ppt, pptx, xls, xlsx, png, jpeg, jpg, gif, txt`


**Programmatically:**

```python
from filewalker.search.Search import Search

s = Search(["md", "txt"]) # Provide the file extension you are interested in
files = s.identifyFiles("path/to/dir")  # If no path is provided, all available 
                                        # hard disk will be searched
                                        # You can see the structure of the files 
                                        # dictionary in the example below.

# Print findings
printable = json.dumps(files, indent=4) 


```


# Example

`py -m filewalker -p path/to/dir -f md,txt -o`

Search for all `md` and `txt` files within the path `path/to/dir` and it's
subdirectories.

```
################################################################################

filewalker by 5f0
Searches hard drives/given path for files specified by file extensions

Current working directory: path/to/filewalker

Datetime: 01/01/1970 20:20:20

 Targeted path: path/to/dir
Targeted files: ['md', txt]

################################################################################

[
    {
        "type": "md",
        "count": 2,
        "paths": [
            "path/to/dir/LICENSE.md",
            "path/to/dir/config/README.md"
        ]
    },
    {
        "type": "txt",
        "count": 1,
        "paths": [
            "path/to/dir/config/other/options.txt"
        ]
    }
]

################################################################################

Execution Time: 0.016395 sec


```


# License

MIT
dinoexplorer 1.0.1
DINO Explorer: A tool to explore DINO embeddings.
License: MIT

# 🦖 DINO Explorer 🦖

DINO Explorer is a powerful tool designed to explore and visualize DINOv2 embeddings. Given a list of folders containing images, DINO Explorer extracts their DINO embeddings and creates an interactive visualization using Voxel51.

## 🚀 Usage

> **Note:** Input folders must be separated by spaces.

* To create a UMAP visualization, use the following command:

```bash
diex <folder 1> .. <folder N>
```
> Diex uses UMAP for dimension reduction by default.
 
* For t-SNE or PCA visualizations, use the `--m` option followed by `tsne` or `pca`:

```bash
diex <folder 1> .. <folder N> --m tsne
```

* To host the visualization on a specific port, use the `--p` option:

```bash
diex <folder 1> .. <folder N> --p <port>
```

* To set a specific GPU device, use the `--d` option:

```bash
diex <folder 1> .. <folder N> --d <gpu number>
```

After running the command, go to the `add` section, select `embeddings`, choose the brain key: `img_viz` and voila! You have your visualization.

> **Tip:** For multiple folders, select `Color by` as `tags`.

## 💾 Caching Embeddings

DINO Explorer stores DINO embeddings for all datasets in a `.cache` directory to allow quick loading in subsequent visualizations. To force regeneration of embeddings, use the `--force` or `--f` option.

> **Note:** These embeddings can also be used for other downstream tasks. Load them with `torch.load()`.

## 📖 Examples

1. **NuImages** - A random set of 1000 images from NuImages
    ```bash
    diex nuimages_1000
    ```
    A. **Embeddings:** Interactive 2D visualization of embeddings
    ![Embeddings](https://raw.githubusercontent.com/nityanandmathur/diex/main/assests/embed.png)

    B. **Embeddings to Image Mapping:** Select embeddings to view corresponding images
    ![Mapping](https://raw.githubusercontent.com/nityanandmathur/diex/main/assests/mapping.png)

2. **NuImages × CityScapes** - A random set of 1000 and 600 images from the datasets.
    ```bash
    diex nuimages_1000 cityscapes_1000
    ```
    Clusters for different datasets, each with a different color.
    ![Cluster](https://raw.githubusercontent.com/nityanandmathur/diex/main/assests/multiple.png)

## 🙏 Credits

- Model used: `facebook/dinov2-giant`
- Visualization tool: `Voxel51`

> For any issues encountered while using DINO Explorer, please open an issue on our GitHub [repository](https://github.com/nityanandmathur/diex). We appreciate your feedback and contributions!
SourceRoboticsToolbox 1.1
Python module for Spectral BLDC motor controllers
License: MIT

        [![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](https://opensource.org/licenses/MIT) ![Issues](https://img.shields.io/github/issues/PCrnjak/Source-Robotics-Toolbox) ![release](https://img.shields.io/github/v/release/PCrnjak/Source-Robotics-Toolbox)
        
        
        
        # More about our projects
        - [Youtube](https://www.youtube.com/channel/UCp3sDRwVkbm7b2M-2qwf5aQ)
        - [Instagram](https://www.instagram.com/source_robotics/)
        - [Twitter](https://twitter.com/SourceRobotics)
        - [Discord](https://discord.com/invite/prjUvjmGpZ )
        - [Forum](https://discourse.source-robotics.com/)
        - [Blog](https://source-robotics.com/blogs/blog)
        
        
        # Liability 
        1. The software and hardware are still in development and may contain bugs, errors, or incomplete features.
        2. Users are encouraged to use this software and hardware responsibly and at their own risk.
        
        # Support the project
        
        The majority of this project is open source and freely available to everyone. Your assistance, whether through donations or advice, is highly valued. Thank you!
        
         [![General badge](https://img.shields.io/badge/PayPal-00457C?style=for-the-badge&logo=paypal&logoColor=white)](https://paypal.me/PCrnjak?locale.x=en_US)
        [![General badge](https://img.shields.io/badge/Patreon-F96854?style=for-the-badge&logo=patreon&logoColor=white)](https://www.patreon.com/PCrnjak)
        
        # Project is under MIT Licence
        
Keywords: python,BLDC,CANBUS,Robot,Source robotics,robotics
Platform: UNKNOWN
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Operating System :: Unix
Classifier: Operating System :: Microsoft :: Windows
Description-Content-Type: text/markdown
tree-sitter-clarity 0.0.1
Clarity grammar for tree-sitter
License: MIT
Requires Python: >=3.8
Keywords: incremental, parsing, tree-sitter, clarity

# tree-sitter-clarity
> 💡 this grammar is still in development.

This repository contains a grammar for [tree-sitter](https://github.com/tree-sitter/tree-sitter).

The goal of this project is to provide an parser efficient low-dependency parser for clarity.


### Navigating this repository
The primary file in this repository is `grammar.js` which describes the tree-sitter grammar.

```
# Primary file:
grammar.js
# Tests:
/test/**/*

# Auto generated:
/src/**/*
binding.gyp
```

Major inspriration & some structures have been taken from tree-sitter-solidity, a big thanks to the contributors to this repo!