semvec/pypi-packages huggingface dataset:
nagini3D 0.2.2
Implementation of NAGINI-3D, a python package designed for Multi-Object Segmentation in Biological Imaging based on deep learning and active surfaces.
Requires Python: >=3.9

# NAGINI-3D | Prediction of Parametric Surfaces for Multi-Object Segmentation in 3D Biological Imaging

We present NAGINI-3D (N-Active shapes for seGmentINg 3D biological Images), a method dedicated to 3D biological images segmentation, based on both deep learning (CNN) and Active Surfaces (Snakes).

This package implement the method described in:

- Quentin RAPILLY, Anaïs BADOUAL,Pierre MAINDRON, Guenaelle BOUET, Charles KERVRANN.
*Prediction of Parametric Surfaces for Multi-Object Segmentation in 3D Biological Imaging*.
Scale Space and Variational Methods in Computer Vision. SSVM 2025. Lecture Notes in Computer Science, vol 15667, Devon, UK, May 2025,
[(preprint)](https://hal.science/hal-04978619), [(final paper)](https://link.springer.com/chapter/10.1007/978-3-031-92366-1_20).

All details on the implementation and the tutorials are available on [the github of the project.](https://github.com/QuentinRapilly/NAGINI-3D)

## Versions

### 0.2.2

New surface regularization strategy that permits to train the network to predict highly parametrized surfaces.

### 0.1.2

Minor bugs fix.

### 0.1.1

**Anisotropic version:** option to process highly anisotropic images.

### 0.0.2

**Paper version**: code used to assess our method for SSVM submission.

### 0.0.1

**Test version**: first pypi version.
solie 9.3.2
GUI trading bot designed for targeting the futures markets of Binance
Requires Python: <4.0,>=3.12

# Solie

[![PyPI - Python Version](https://img.shields.io/pypi/v/solie)](https://pypi.org/project/solie/)
[![uv](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/uv/main/assets/badge/v0.json)](https://github.com/astral-sh/uv)
[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)
[![Checked with pyright](https://microsoft.github.io/pyright/img/pyright_badge.svg)](https://microsoft.github.io/pyright/)

![Preview](https://github.com/cunarist/solie/assets/66480156/8521df2b-a315-4e00-8963-1db287e0c8ce)

**Solie** is a GUI trading bot designed for targeting the futures markets of Binance.

It enables you to create and customize your own trading strategies, simulating them using real historical data from Binance with the power of Python.

Please note that while this solution provides tools for strategy development, profitability is not guaranteed as success depends on individual decision-making.

Solie connects to Binance, retrieves real-time market and account data, saves it on disk, and presents it as intuitive charts to assist users in strategy development.

## 🛞 Usage

### Preparation

You can install Solie via `pip`. It is recommended to use [`uv`](https://docs.astral.sh/uv/) for modern Python package management and virtual environments.

```shell
pip install solie
```

### Running With a Script File

Make a Python script file that has the extension `.py`. Just copy and paste the content below in the file. Solie will start working once you execute the Python script file.

```python
import solie

if __name__ == "__main__":
    solie.bring_to_life()
```

For advanced usage, see the `example` folder in the repository.

> Note that on Windows, giving the extension `.pyw` to the file allows you to hide the terminal window and only leave the GUI.

## 🖥️ Available Platforms

- ✅ Windows: Fully supported
- ✅ Linux: Fully supported
- ⏸️ macOS: [Currently unstable](https://github.com/cunarist/solie/issues/87)

## 📖 Documentation

Read the [documentation](https://solie-docs.cunarist.org) to understand how to turn on auto-trading, make your own strategies with the internal API, and get involved in Solie development.
spdx_checker 0.1.20
Fast SPDX License Checker for Source Code
Requires Python: >=3.11

# SPDX License Checker

`spdx-checker` is a fast Python package for validating and analyzing SPDX license headers in your projects. It leverages Zig for exceptional speed and efficiency. The checker raises an error immediately if any file contains an incorrect or missing license header.

### Supported platforms
The wheels published by the GitHub Actions workflow are built with cibuildwheel. The table below lists all supported operating systems and Python versions for the pre-built wheels.

| Operating System | Python versions / ABI |
|---|---|
| macOS (arm64) | 3.11, 3.12, 3.13 (cp311, cp312, cp313 — macosx_arm64) |
| manylinux (x86_64) | 3.11, 3.12, 3.13 (cp311, cp312, cp313 — manylinux_x86_64) |
| musllinux (x86_64) | 3.11, 3.12, 3.13 (cp311, cp312, cp313 — musllinux_x86_64) |
| Windows (amd64) | 3.11, 3.12, 3.13 (cp311, cp312, cp313 — win_amd64) |


## Example Usage

```python
import spdx_checker

spdx_checker.check_license(
    "MIT", 
    ["example1.py", "example2.svelte", "example3.html"]
    extensions=["zig", "py", "svelte"]
    fix=True,
    continue_on_error=False
    )
```

## Development

Issues with uv caching

```
To force uv to ignore existing installed versions, pass --reinstall to any installation command (e.g., uv sync --reinstall or uv pip install --reinstall ...).
```

## License

[MIT](LICENSE)