semvec/pypi-packages huggingface dataset:
PenguinMol3D 0.1.3
3D visualization of small compounds
Requires Python: >=3.10

# PenguinMol3D
PenguinMol3D is an open source Python3 package, which utilizes OpenGL python binding (https://pyopengl.sourceforge.net) for rendering of small compounds' 3D models. 
# Installation

**Dependencies**
* numpy
* rdkit
* PyOpenGL
* PyOpenGL_accelerate
* glfw
* Pillow

NOTE: Although dependencies are installed with package, on Windows OS Microsoft C++ 14 Build Tools are required to install PyOpenGL_accelerate
# Usage

Initially, the RDKit Mol object is created from data in a file (e.g, MOL/SDF, MOL2 format) provided by user; the Mol object is further passed as an argument to the Mol3D class constructor, which generates a 3D model based on atom coordinates of the Mol object conformer. During the initialization stage (before running an event loop) user has to setup a scene by creating MolecularScene object and adding all necessary components like molecule and light sources as it is demonstrated in examples. As a drawing surface for rendering can be used any surface compatible with OpenGL; particularly, provided by such GUI libaries as GLFW (used in examples), PyGame, PyQt, PySide, wxPython, Tkinter + Togl widget, etc.

To check if package was installed correctly after installation enter:

**Windows OS:**

* python -m PenguinMol3D.glfw_surface_example

**Linux OS:**

* python3 -m PenguinMol3D.glfw_surface_example

PenguinMol3D currently supports two lighting models: Physically Based Lighting Model (default) and Blinn-Phong Lighting Model.
To see examples of this two models enter:

**Windows OS:**

* python -m PenguinMol3D.glfw_bpr_example
* python -m PenguinMol3D.glfw_pbr_example
* python -m PenguinMol3D.glfw_custom_material_example

**Linux OS:**

* python3 -m PenguinMol3D.glfw_bpr_example
* python3 -m PenguinMol3D.glfw_pbr_example
* python3 -m PenguinMol3D.glfw_custom_material_example

Main folder also contains script, which can be used for small molecule visualization with predefined scene, to run it enter:

**Windows OS:**

* python -m PenguinMol3D.display_molecule molecule_name.sdf

**Linux OS:**

* python3 -m PenguinMol3D.display_molecule molecule_name.sdf
oskat 0.1.2
Open-Source Kamera-Arts Tools
Requires Python: >=3.9,<4.0

# OSKAT
***Open Source Kamera-Arts Tools***  
A set of command line tools for batch processing photos without opening up a photo-editing application.

### Current Tools (v0.1.2):
**varimat**: adds borders to fit certain aspect ratio.  
**instamat**: adds borders to fit 4:5 aspect ratio, e.g. for Instagram

## Quickstart Guide
### 1. Installation
The simplest way to install `oskat` as a globally-available command-line tool is to use `pipx`. Find the guide [here](https://pipx.pypa.io/stable/installation/).

Once you have `pipx` installed, simply run either of the following commands from your terminal:  
```
pipx install oskat
```

*or, alternatively:*
```
pipx install git+https://github.com/kl819/oskat.git
```  

The second command installs directly from the GitHub repository and is recommended.

Once `pipx` is done installing, you should receive a message like this:
  ```installed package oskat 0.1.0, installed using Python 3.9.6
  These apps are now globally available
    - oskat
done! ✨ 🌟 ✨
```
You should be able to verify this with `pipx list`, which lists out the apps installed through `pipx`. One of them should be `oskat`. If it shows up on the list, you've successfully installed `oskat`!
  

### 2. Using `oskat`
The easiest way to use `oskat` is to navigate to the folder with the photos you'd like to process. If no path and output is specified on any `oskat` command, it will process all images in the directory in which it is run and output the results to a separate folder. 

#### ex. 1: `instamat`
You've just exported a fresh set of photos from Lightroom, almost ready to post to Instagram but *oh, no*, every photo's a different aspect ratio!

You can use `instamat` to add white borders as needed to make all the images the same (Instagram-optimal) 4:5 aspect ratio!  
First, navigate to the folder with all your photos and open a terminal there (or navigate there via the terminal). Then, just type `oskat instamat` into the terminal. Give it a few seconds, and you should see a message like this:
```
matted 3 images in 0.9s!
```

**All done!** Your Instagram-ready photos will be in a new folder within the folder in which you ran the command.