semvec/pypi-packages huggingface dataset:
twsc 0.9.1
A tool to clean trailing whitespace from recently changed lines or an entire codebase.
Requires Python: >=3.7

# TWSC: Trailing Whitespace Cleaner

TWSC (Trailing Whitespace Cleaner) is a Python package designed to clean up trailing whitespace in code files efficiently. It works for files in Git repositories, untracked files, or even entire codebases when not in a Git environment.

---

## Features

1. **Clean Tracked Changes:**
   - Cleans only the changed lines in tracked files since the last commit.
   
2. **Handle Untracked Files:**
   - Cleans trailing whitespace from all untracked files in a Git repository.

3. **Full Codebase Cleanup:**
   - Offers to clean trailing whitespace from all files in the codebase when not in a Git repository.

4. **Supported Extensions:**
   - Python (`.py`), JavaScript (`.js`), TypeScript (`.ts`), Java (`.java`), Go (`.go`), C (`.c`), C++ (`.cpp`), Ruby (`.rb`), Shell (`.sh`), Rust (`.rs`), HTML (`.html`), CSS (`.css`).

---

## Installation

Install TWSC using pip:

```bash
pip install twsc
```

---

## Usage

### Command-Line Interface

Run `twsc` from the root of your project directory:

```bash
twsc
```

### Options

1. **Force Full Cleanup:**
   Use the `--force-clean-all` flag to clean the entire codebase, even if it’s a Git repository:

   ```bash
   twsc --force-clean-all
   ```

2. **Version Information:**
   Check the package version:

   ```bash
   twsc --version
   ```

---

## How It Works

### In a Git Repository:
1. **Tracked Files:**
   - Identifies lines changed since the last commit and cleans up only those lines.
2. **Untracked Files:**
   - Cleans up all lines in untracked files.

### Outside a Git Repository:
- Prompts the user to clean the entire codebase, targeting supported file types.

---

## Example

**Before Cleanup:**
```python
def example_function():     
    print("Hello, World!")      
    
```

**After Cleanup:**
```python
def example_function():
    print("Hello, World!")
```

---

## Logging

TWSC uses Python's `logging` module to provide detailed logs during execution. Logs are printed to the console in the following format:

```
2024-11-19 10:45:23 - INFO - Cleaning recently changed files.
2024-11-19 10:45:23 - INFO - Cleaned trailing whitespace in: file1.py
```

---

## For contribution and development

### Run Tests

Clone the repository and install dependencies:

```bash
git clone https://github.com/letsgogeeky/twsc.git
cd twsc
pip install -r requirements.txt
python -m unittest discover -s tests
```

---

## Contributing

Contributions are welcome! Feel free to:
1. Open an issue for bug reports or feature requests.
2. Submit pull requests for improvements.

---

## License

This project is licensed under the MIT License. See the `LICENSE` file for details.

---

## Known Limitations

- **Unsupported Extensions:**
  - `.php` files are not supported for cleanup.
  
- **Non-Git Directories:**
  - Requires confirmation to clean the entire codebase.

---

Feel free to reach out if you have questions or issues with TWSC!
trembao 0.0.0
Trembão: Um framework inovador.
Requires Python: >=3.6

# TrembÃ£o

TrembÃ£o Ã© um framework Python inovador para transformar componentes Jinja2 em Single Page Applications (SPA), PWAs e mais.

## InstalaÃ§Ã£o

```bash
pip install trembao
```
together-gradio 0.0.1
A Python package for replicating Gradio applications using Together AI
Requires Python: >=3.10

# `together_gradio`

is a Python package that makes it very easy for developers to create machine learning apps that are powered by Together's Inference API.

# Installation

1. Clone this repo: `git clone git@github.com:gradio-app/together_gradio.git`
2. Navigate into the folder that you cloned this repo into: `cd together_gradio`
3. Install this package: `pip install -e .`

<!-- ```bash
pip install Together-gradio
``` -->

That's it! 

# Basic Usage

Just like if you were to use the `Together` Client, you should first save your together API token to this environment variable:

```
export TOGETHER_API_KEY=<your token>
```

Then in a Python file, write:

```python
import gradio as gr
import together_gradio

gr.load(
    name='meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo',
    src=together_gradio.registry,
).launch()
```

Run the Python file, and you should see a Gradio ChatInterface connected to the model on Together!

![ChatInterface](chatinterface.png)

# Customization 

Once you can create a Gradio UI from a Together endpoint, you can customize it by setting your own input and output components, or any other arguments to `gr.ChatInterface`. For example, the screenshot below was generated with:

```py
import gradio as gr
import together_gradio

gr.load(
    name='meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo',
    src=together_gradio.registry,
    title='Together-Gradio Integration',
    description="Chat with Meta-Llama-3.1-70B-Instruct-Turbo model.",
    examples=["Explain quantum gravity to a 5-year old.", "How many R are there in the word Strawberry?"]
).launch()
```
![ChatInterface with customizations](chat_custom.png)

# Composition

Or use your loaded Interface within larger Gradio Web UIs, e.g.

```python
import gradio as gr
import together_gradio

with gr.Blocks() as demo:
    with gr.Tab("8B"):
        gr.load('meta-llama/Meta-Llama-3-8B-Instruct-Lite', src=Together_gradio.registry)
    with gr.Tab("70B"):
        gr.load('meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo', src=Together_gradio.registry)

demo.launch()
```

# Under the Hood

The `Together-gradio` Python library has two dependencies: `Together_cloud_sdk` and `gradio`. It defines a "registry" function `Together_gradio.registry`, which takes in a model name and returns a Gradio app.

# Supported Models in Together API
Currently the available options are: llama3.1-8b, llama3.1-70b

-------

Note: if you are getting a 401 authentication error, then the Together API Client is not able to get the API token from the environment variable. This happened to me as well, in which case save it in your Python session, like this:

```py
import os

os.environ["TOGETHER_API_KEY"] = ...
```
pypirccua 1.1.0
A PyQt-based application for visualizing and analyzing relay counts from DB files.
Requires Python: >=3.7

# pypirccua

pypirccua - Python Pickering Relay Cycle Counting Utility Application is a PyQt-based application for visualizing and analyzing relay counts from DB files from Pickering PXI cards.

The **file format specification** is described in the [official reference manual](https://downloads.pickeringtest.info/downloads/RelayCountingApplication/RelayCountingAppHelp.pdf)

## License
- Under GNU/GPLv3

## Features
- Parses **RelayCount Card Database Files** (similar to the NI PXIe Health Monitor).
- Displays statistics on Pickering PXI card physical or logical layers.
- Allows users to set a **count heatmap** and provides **visual feedback** as a reference.
- Associates a `.db` file with a **table view**.

## Changelog

### [1.x.x] Future (somwhere in the future)

+ Support: **Interconnect DB data mapping** with the eBirst Card Definition set XML data, and visualize side-by-side with the default database **PiTableView**.
+ Support: **dataset export functionality** to Google Sheets.
+ Support: **PiLpxi & LXI client bridge functionality** into the application.
+ Support: additional statistics with an improved graph view (including support for zoom-in/out, selection, and callbacks in the table view).

### [1.1.0] - 2024-11-20

+ Added: Thread support for Db card loading.
+ Added: PiDbCardList support for removing and clearing card list.
+ Added: PiDbCardList detect already existing duplicates when adding Card DB File to the list.
+ Added: PircViewer proper ProgressBar, StatusBar for app feedbacking information to the user.
+ Added: PircViewer About dialog.
+ Added: PiTableView export table to csv functionality.

### [1.0.0] - 2024-11-17

+ Initial released version of the application.

## Screenshots

![initial db view](./assets/app1.png)

![dbfile -> table association](./assets/app2.png)

## Install
```
pip install .
```

## Run
```
pypirccua
```