semvec/pypi-packages huggingface dataset:
opencal 4.0.2
OpenCAL core library for Python
Requires Python: >=3.11

=======
OpenCAL
=======

Copyright (c) 2008-2024 Jérémie DECOCK <jd.jdhp@gmail.com> (www.jdhp.org)

* Web site: https://gitlab.com/opencal/opencal-lib-python
* Online documentation: https://opencal.gitlab.io/opencal-lib-python
* Source code: https://gitlab.com/opencal/opencal-lib-python
* Issue tracker: https://gitlab.com/opencal/opencal-lib-python/issues
* Pytest code coverage: https://opencal.gitlab.io/opencal-lib-python/htmlcov/index.html
* OpenCAL on PyPI: https://pypi.org/project/opencal


Table of Contents
=================

.. contents::
   :depth: 2


Description
===========

OpenCAL core library for Python

Note:

    This project is still in beta stage, so the API is not finalized yet.


Dependencies
============

OpenCAL requires Python 3.11 (or newer) and Python packages listed in the `requirements.txt` file.


.. _install:

Installation (development environment)
======================================

Posix (Linux, MacOSX, WSL, ...)
-------------------------------

From the OpenCAL source code::

    conda deactivate         # Only if you use Anaconda...
    python3 -m venv env
    source env/bin/activate
    python3 -m pip install --upgrade pip
    python3 -m pip install -r requirements-dev.txt


Windows
-------

From the OpenCAL source code::

    conda deactivate         # Only if you use Anaconda...
    python3 -m venv env
    env\Scripts\activate.bat
    python3 -m pip install --upgrade pip
    python3 -m pip install -r requirements-dev.txt


Installation (production environment)
=====================================

::

    pip install opencal


Documentation
=============

* Online documentation: https://opencal.gitlab.io/opencal-lib-python
* API documentation: https://opencal.gitlab.io/opencal-lib-python/api.html


Build and run the Python Docker image
=====================================

Build the docker image
----------------------

From the OpenCAL source code::

    docker build -t opencal:latest .

Run unit tests from the docker container
----------------------------------------

From the OpenCAL source code::

    docker run opencal pytest

Run an example from the docker container
----------------------------------------

From the OpenCAL source code::

    docker run opencal python3 /app/examples/hello.py


Bug reports
===========

To search for bugs or report them, please use the OpenCAL Bug Tracker at:

    https://gitlab.com/opencal/opencal-lib-python/issues


License
=======

This project is provided under the terms and conditions of the `MIT License`_.


.. _MIT License: http://opensource.org/licenses/MIT
.. _command prompt: https://en.wikipedia.org/wiki/Cmd.exe
proxbox-api 0.0.2.post3
Proxbox API service made using FastAPI
Requires Python: >=3.10

# Installing proxbox-api (Plugin backend made using FastAPI)

## Using docker (recommended)

### Pull the docker image

```
docker pull emersonfelipesp/proxbox-api:latest
```

### Run the container
```
docker run -d -p 8800:8800 --name proxbox-api emersonfelipesp/proxbox-api:latest
```

## Using git repository

### Clone the repository

```
git clone https://github.com/netdevopsbr/netbox-proxbox.git
```

### Change to 'proxbox_api' project root folder

```
cd proxbox_api 
```

### Install dependencies

```
pip install -r requirements.txt
```

### Change to 'proxbox_api' app folder (the actual code)

```
cd proxbox_api
```

### Start the FastAPI using astral-uv (recommended)

```
uv run fastapi run --host 0.0.0.0 --port 8800
```

- `--host 0.0.0.0` will make the app available on all host network interfaces, which my not be recommended.
Just pass your desired IP like `--host <YOUR-IP>` and it will also work.

- `--port 8800` is the default port, but you can change it if needed. Just to remember to update it on NetBox also, at FastAPI Endpoint model.

### If using 'uv' fails, try to start it directly:

Using `fastapi`:

```
pip install -e .
fastapi run --host 0.0.0.0 --port 8800
```

Or using `uvicorn`:

```
uvicorn main:app --host 0.0.0.0 --port 8800
```

## Using mkcert

Install the local CA in the system trust store.

```
mkcert -install
mkcert proxbox.backend.local localhost 127.0.0.1 ::1
```

With the keyfile and certfile generated, pass it on uvicorn command to start up FastAPI

### NGINX

```
sudo cp nginx.conf /etc/nginx/sites-available/proxbox
sudo ln -s -f /etc/nginx/sites-available/proxbox /etc/nginx/sites-enabled/proxbox
sudo systemctl restart nginx
```

```
/opt/netbox/venv/bin/uvicorn netbox-proxbox.proxbox_api.proxbox_api.main:app --host 0.0.0.0 --port 8800 --app-dir /opt/netbox/netbox --ssl-keyfile=localhost+2-key.pem --ssl-certfile=localhost+2.pem
```

Or 

```
cd /opt/netbox/netbox/netbox-proxbox/proxbox_api
uvicorn proxbox_api.main:app --host 0.0.0.0 --port 8800 --reload --ssl-keyfile=./proxbox_api/proxbox.backend.local+3-key.pem --ssl-certfile=./proxbox_api/proxbox.backend.local+3.pem
```
itkwasm-morphological-contour-interpolation 2.0.0
Morphology-based approach for interslice interpolation of anatomical slices from volumetric images.
Requires Python: >=3.8
Keywords: emscripten, itkwasm, wasi, webassembly

# itkwasm-morphological-contour-interpolation

[![PyPI version](https://badge.fury.io/py/itkwasm-morphological-contour-interpolation.svg)](https://badge.fury.io/py/itkwasm-morphological-contour-interpolation)

Morphology-based approach for interslice interpolation of anatomical slices from volumetric images.

## Installation

```sh
pip install itkwasm-morphological-contour-interpolation
```
itkwasm-morphological-contour-interpolation-emscripten 2.0.0
Morphology-based approach for interslice interpolation of anatomical slices from volumetric images.
Requires Python: >=3.8
Keywords: emscripten, itkwasm, webassembly

# itkwasm-morphological-contour-interpolation-emscripten

[![PyPI version](https://badge.fury.io/py/itkwasm-morphological-contour-interpolation-emscripten.svg)](https://badge.fury.io/py/itkwasm-morphological-contour-interpolation-emscripten)

Morphology-based approach for interslice interpolation of anatomical slices from volumetric images. Emscripten implementation.

This package provides the Emscripten WebAssembly implementation. It is usually not called directly. Please use the [`itkwasm-morphological-contour-interpolation`](https://pypi.org/project/itkwasm-morphological-contour-interpolation/) instead.


## Installation

```sh
import micropip
await micropip.install('itkwasm-morphological-contour-interpolation-emscripten')
```

## Development

```sh
pip install hatch
hatch run download-pyodide
hatch run test
```
llmtraceviewer 0.2.0
A tool to view LLM call traces from JSONL log files.
Requires Python: >=3.8

# llmtraceviewer

A Python package and CLI tool to view LLM call traces from JSONL log files. It starts a local HTTP server for interactive log exploration.

## Usage

```sh
llmtraceviewer <log_filename or directory>
```

- Starts a FastAPI server
- Provides an API endpoint for log data
- You can specify a single log file or a directory containing log files

## Log File Format

The tool expects a JSONL (JSON Lines) log file where each relevant line contains the string `LLMTRACE:` followed by a JSON object. Only lines with `LLMTRACE:` are parsed.

**Each JSON object should have the following structure:**

```
{
  "type": "chat.completion",
  "messages": [
    { "role": "user", "content": "Hello, world!" },
    { "role": "assistant", "content": "Hi!" }
  ],
  "response_format": "text",
  "reasoning_effort": "low",
  "temperature": 0.7,
  "elapsed_time": 1.23,
  "response": "Hi!",
  "finish_reason": "stop",
  "completion_tokens": 10,
  "prompt_tokens": 8,
  "reasoning_tokens": 2,           // optional
  "start_time": 1713268800.0       // optional (Unix timestamp)
}
```

**Example log file:**

```
2024-04-16T12:00:00Z INFO LLMTRACE: {"type": "chat.completion", "messages": [{"role": "user", "content": "Hello, world!"}], "response_format": "text", "reasoning_effort": "low", "temperature": 0.7, "elapsed_time": 1.23, "response": "Hi!", "finish_reason": "stop", "completion_tokens": 10, "prompt_tokens": 8}
2024-04-16T12:00:01Z INFO LLMTRACE: {"type": "chat.completion", "messages": [{"role": "user", "content": "How are you?"}], "response_format": "text", "reasoning_effort": "medium", "temperature": 0.7, "elapsed_time": 1.45, "response": "I'm an AI, so I don't have feelings, but thanks for asking!", "finish_reason": "stop", "completion_tokens": 15, "prompt_tokens": 10, "reasoning_tokens": 3, "start_time": 1713268801.0}
```

- Each line can have arbitrary text before `LLMTRACE:`
- The JSON object after `LLMTRACE:` should contain the LLM call trace fields as shown above

## Requirements
- Python 3.8+
- Node.js (for development)

## Development
- Backend: FastAPI
- Frontend: Next.js (served as static files)
itkwasm-morphological-contour-interpolation-wasi 2.0.0
Morphology-based approach for interslice interpolation of anatomical slices from volumetric images.
Requires Python: >=3.8
Keywords: itkwasm, wasi, webassembly

# itkwasm-morphological-contour-interpolation-wasi

[![PyPI version](https://badge.fury.io/py/itkwasm-morphological-contour-interpolation-wasi.svg)](https://badge.fury.io/py/itkwasm-morphological-contour-interpolation-wasi)

Morphology-based approach for interslice interpolation of anatomical slices from volumetric images. WASI implementation.

This package provides the WASI WebAssembly implementation. It is usually not called directly. Please use [`itkwasm-morphological-contour-interpolation`](https://pypi.org/project/itkwasm-morphological-contour-interpolation/) instead.


## Installation

```sh
pip install itkwasm-morphological-contour-interpolation-wasi
```

## Development

```sh
pip install pytest itkwasm-image-io
pip install -e .
pytest

# or
pip install hatch
hatch run test
```
folder-merger 0.1.0
A utility for safely merging multiple folders while handling file conflicts
Requires Python: >=3.6

# Folder Merger

A Python utility for safely merging multiple folders while handling file conflicts intelligently.

## Features

- Recursively merges folders while preserving directory structure
- Detects and handles file conflicts automatically
- Skips duplicate files using MD5 hash comparison
- Progress tracking with tqdm
- Comprehensive logging

## Installation

```bash
pip install folder-merger
```

## Usage

### Command Line Interface

```bash
folder-merger --source /path/to/source --destination /path/to/destination
```

### Python API

```python
from folder_merger import MergeManager

manager = MergeManager(
    source_root="/path/to/source",
    output_path="/path/to/destination"
)
manager.merge_all()
```

## How it Works

1. The tool recursively walks through the source directory
2. For each file:
   - Checks if file exists in destination
   - If file exists, compares MD5 hashes to detect duplicates
   - If files are different, creates a conflict copy with "_conflict" suffix
   - If file doesn't exist, copies it to destination

## License

MIT License

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.
pynetbox-api 0.0.2.post1
pynetbox API
Requires Python: >=3.10

# pynetbox-api
FastAPI layer above pynetbox lib.

---

You can provide environment variables to communicate with NetBox at `./pynetbox_api/env.py` or use the API (by creating the endpoint into the sqlite database via FastAPI app routes)

## Install using pip
- Production mode using pypi package

```
pip install pynetbox-api
```

## Install using git
- Developer mode using git repository
```
git clone https://github.com/emersonfelipesp/pynetbox-api.git
cd pynetbox-api
python3 -m venv venv
source venv/bin/activate
python3 -m pip install -r requirements.txt
python3 -m pip install -e .
```

## Start FastAPI app (Optional)

> **OBS:** This is optional because this lib was created with the intention to be used as a lib, where you import it into your project.
> The FastAPI is available to make it easy to test each NetBox object/model with all validation and features this project provides.

```
uv run fastapi dev
```

You can optionally pass `--host` and `--port` attributes, like:

```
uv run fastapi dev --host 0.0.0.0 --port 8800
```

This will start FastAPI listening on all host network interfaces IP addresses and HTTP port 8800.