semvec/pypi-packages huggingface dataset:
visaion5lvis 0.5.4
Python API for LVIS dataset.

LVIS (pronounced ‘el-vis’): is a new dataset for Large Vocabulary Instance Segmentation.
We collect over 2 million high-quality instance segmentation masks for over 1200 entry-level object categories in 164k images. LVIS API enables reading and interacting with annotation files,
visualizing annotations, and evaluating results.
redqlite 1.1.0
A lightweight Messaging queue implementation using Redis for producer-worker-subscriber messaging.
Requires Python: >=3.12

# RedQLite

A lightweight Messaging queue implementation using Redis for producer-worker-subscriber messaging.

---

## Features

- Redis-backed message queuing
- Producer and worker interface
- Producer and subscriber interface
- Lightweight and fast alternative to Kafka/Celery
- Works for long running tasks
- Provides configurable heartbeats from inside worker callback functions
- Redis server required
- Minimal setup — no broker required


---

## Installation

```bash
pip install redqlite
```

## How It Works
This package simulates a basic messaging system using Redis lists.
It includes:

A **Producer** that pushes messages to a Redis queue or broadcasts messages to all subscribers.

A **Worker** that consumes messages from the queue and processes them.

A **Worker Pool** to run concurrent workers. 

A **Subscriber** that consumes messages from channel specific message queue.

## Usage
### Example: Producing a Message
```python
# Import RQProducer class
from redqlite.producer import RQProducer

# Create a producer instance
rqproducer = RQProducer(host="localhost", port=6379)

# Send a message
rqproducer.send(topic="yourtopicname", message="hello world")

# Broadcast message on a channel
rqproducer.broadcast(channel="yourchannelname", message="hello world")
```

### Example: Starting a Worker
```python
# Import RQWorker class
from redqlite.worker import RQWorker

def callback_func(msg, **kwargs):
	print(msg)

# Create a worker instance
## Provide your redis connection details or Redis connection pool object
rqworker = RQWorker(host="localhost", port=6379, topic="yourtopicname", callback=callback_func)

# Start worker thread
rqworker.start()

```

### Example: Starting a Worker Pool
```python
# Import RQWorkerPool class
from redqlite.worker import RQWorkerPool

def callback_func(msg, **kwargs):
	print(msg)

# Create a worker pool
## Provide your redis connection details or Redis connection pool object
rqworker_pool = RQWorkerPool(host="localhost", port=6379, topic="yourtopicname", callback=callback_func, num_workers=2)

# Start worker pool
rqworker_pool.start()
```

### Example: Starting a subscriber
```python
# Import QSubscriber class
from redqlite.subscriber import RQSubscriber
from redis import Redis

def callback_func(msg, **kwargs):
	print(msg)

# Create a worker instance
rqsubscriber = RQSubscriber(redis_conn=Redis(), channel="yourchannelname", callback=callback_func)

# Start subscriber thread
rqsubscriber.start()

```

## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

## Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you’d like to change.

## Contact
Feel free to reach out by [opening an issue](https://github.com/shashankgandhi1/redqlite/issues) or by [contacting the author](https://github.com/shashankgandhi1).
patch-torchcodec 0.1.4
Patch TorchCodec to use PyAV's bundled FFmpeg — one command, no system FFmpeg needed
Requires Python: >=3.9
Keywords: decoder, ffmpeg, patchelf, pyav, torchcodec, video

# patch-torchcodec

Patch TorchCodec to use PyAV's bundled FFmpeg — **one command, no system FFmpeg needed**.

## Problem

TorchCodec requires FFmpeg shared libraries (`libavcodec.so.62`, etc.), but installing FFmpeg system-wide can be complex and may cause version conflicts.

## Solution

PyAV already bundles FFmpeg. `patch-torchcodec` patches TorchCodec's RPATH to find them — no environment variables needed!

## Quick Start

```bash
pip install torchcodec          # install torchcodec (with PyTorch)
pip install patch-torchcodec    # install patcher (av & patchelf included)
patch-torchcodec                # patches RPATH — done!
```

That's it. TorchCodec now works:

```python
from torchcodec.decoders import VideoDecoder  # ✓ just works
```

## Command Line Options

```bash
patch-torchcodec               # Patch RPATH (default, recommended)
patch-torchcodec --env-only    # Symlinks only (requires LD_LIBRARY_PATH)
patch-torchcodec --status      # Check current setup status
patch-torchcodec --verify      # Verify TorchCodec works
patch-torchcodec --quiet       # Silent mode
```

## Python API

```python
from patch_torchcodec import setup_with_patchelf, verify_torchcodec, is_rpath_patched

# Patch RPATH (recommended) — persists across sessions
setup_with_patchelf(verbose=True)

# Verify
assert verify_torchcodec(require_env=False)
```

## How It Works

1. **Finds PyAV's bundled FFmpeg** in `site-packages/av.libs/`
2. **Creates symbolic links** with standard names (e.g., `libavcodec.so.62`)
3. **Patches TorchCodec's `.so` files** with `patchelf` to include PyAV's library path in RPATH

## Limitations

- **Linux only** (RPATH is Linux-specific)
- **Same virtualenv**: PyAV and TorchCodec must be in the same environment
- **Re-run after reinstall**: If you reinstall TorchCodec, run `patch-torchcodec` again

## License

MIT
markus_exam_matcher 0.4.0
A package for matching students to test papers in MarkUs
Requires Python: <3.15,>=3.11

# MarkUs Exam Matcher

## Installation
It is recommended to use a [virtual environment](https://docs.python.org/3/library/venv.html) to install this package, as it contains many pinned runtime dependencies.

### Production Installation (Recommended)
To install the production version of the package, run the following command in the console:

```console
$ pip install markus-exam-matcher --extra-index-url https://download.pytorch.org/whl/cpu
```

### Latest Development Installation

To install the latest development version of the package, run the following command in the console:

```console
$ pip install git+https://github.com/MarkUsProject/markus-exam-matcher.git --extra-index-url https://download.pytorch.org/whl/cpu
```

### Branch Installation
To install the version specified by a particular branch (when permissions are granted), run the following command in the
console:
```console
$ pip install git+https://github.com/MarkUsProject/markus-exam-matcher.git@branch_name --extra-index-url https://download.pytorch.org/whl/cpu
```

### Commit Hash Installation
To install the version specified by a specific commit, the commit hash can be used by running the following command in
the console:
```console
$ pip install git+https://github.com/MarkUsProject/markus-exam-matcher.git@commit_hash --extra-index-url https://download.pytorch.org/whl/cpu
```
## Usage
This package works under the assumption that the characters to be detected are surrounded by boxes that are placed
side-by-side. An example image with this format is displayed below:

![Text](./examples/student_info_num.jpg?raw=true)

Below is a sample usage that generates a prediction from the file shown above.
```console
$ python3 -m markus_exam_matcher --char_type digit char examples/student_info_num.jpg
0001250981
```

## Developers

1. First, clone this repository.
2. Open a terminal in this repo, and create a new [virtual environment](https://docs.python.org/3/library/venv.html).
3. Run `pip install -e ".[dev]"` to install the dependencies.
4. Then run `pre-commit install` to install the pre-commit hooks (for automatically formatting and checking your code on each commit).
uv-helper 0.1.8
Helper for UV.
Requires Python: >=3.14.3
Keywords: uv, helper, cli, automation, dependencies, pyproject.toml

# Uv helper

Helpful commands for the `uv` tool.

---

## Dev

### Uv install or update

https://docs.astral.sh/uv/getting-started/installation/

```bash
if ! command -v uv &> /dev/null; then
    curl -LsSf https://astral.sh/uv/install.sh | sh;
else
    uv self update;
fi

uv --version
```

### Create venv

```bash
uv sync --all-packages
```

### Register pre-commit hooks

```shell
prek install
```

### Run pre-commit hooks

```shell
prek run --all-files
```

---

## Extra

- Why is the `.idea` folder is partially stored in the repository?
    - [read (UKR)](https://github.com/Alirex/notes/blob/main/notes/ignore_or_not_ide_config/ukr.md)
- Why `py.typed`?
    - [mypy (ENG)](https://mypy.readthedocs.io/en/stable/installed_packages.html#creating-pep-561-compatible-packages)
    - [typing (ENG)](https://typing.python.org/en/latest/spec/distributing.html#packaging-type-information)

### Reinit .idea folder for git for better gitignore support

If you created a new project with JetBrains IDE and automatically created git repository,
before providing more granular `.gitignore` file, you need to reinit `.idea` folder.

```shell
git rm -r --force --cached .idea &&\
git add .idea
```

### Check the paths for the venv

```shell
uv run python -c 'import sys, os; [print(p) for p in sys.path if p and "zip" not in p.lower() and os.path.basename(p)!="src"]'
```