synkit 1.1.1

Utility for reaction modeling using graph grammar

SynKit

Toolkit for Synthesis Planning

SynKit is a collection of tools designed to support the planning and execution of chemical synthesis. Check out the documentation for a comprehensive description of its features.

Our tools are tailored to assist researchers and chemists in navigating complex chemical reactions and synthesis pathways, leveraging the power of modern computational chemistry. Whether you're designing novel compounds or optimizing existing processes, synkit aims to provide the critical tools you need.

For more details on each utility within the repository, please refer to the documentation provided in the respective folders.

Table of Contents

• Installation
• Contribute to SynKit
• Contributing
• License
• Acknowledgments

Installation

1. Python Installation: Ensure that Python 3.11 or later is installed on your system. You can download it from python.org.

2. Creating a Virtual Environment (Optional but Recommended): It's recommended to use a virtual environment to avoid conflicts with other projects or system-wide packages. Use the following commands to create and activate a virtual environment:

python -m venv synkit-env
source synkit-env/bin/activate  

Or Conda

conda create --name synkit-env python=3.11
conda activate synkit-env

3. Install from PyPi: The easiest way to use SynTemp is by installing the PyPI package synkit.

pip install synkit

Optional if you want to install full version

pip install synkit[all]

4. Install via Docker
   Pull the image:

   docker pull tieulongphan/synkit:latest
   # or a specific version:
   docker pull tieulongphan/synkit:1.0.0
   

   Run a container (sanity check):

   docker run --rm tieulongphan/synkit:latest
   

Contribute

We're welcoming new contributors to build this project better. Please not hesitate to inquire me via email.

Before you start, ensure your local development environment is set up correctly. Pull the latest version of the main branch to start with the most recent stable code.

git checkout main
git pull

Working on New Features

1. Create a New Branch:
   For every new feature or bug fix, create a new branch from the main branch. Name your branch meaningfully, related to the feature or fix you are working on.

   git checkout -b feature/your-feature-name
   

2. Develop and Commit Changes:
   Make your changes locally, commit them to your branch. Keep your commits small and focused; each should represent a logical unit of work.

   git commit -m "Describe the change"
   

3. Run Quality Checks:
   Before finalizing your feature, run the following commands to ensure your code meets our formatting standards and passes all tests:

   ./lint.sh # Check code format
   pytest Test # Run tests
   

   Fix any issues or errors highlighted by these checks.

Integrating Changes

1. Rebase onto Staging:
   Once your feature is complete and tests pass, rebase your changes onto the staging branch to prepare for integration.

   git fetch origin
   git rebase origin/staging
   

   Carefully resolve any conflicts that arise during the rebase.

2. Push to Your Feature Branch: After successfully rebasing, push your branch to the remote repository.

   git push origin feature/your-feature-name
   

3. Create a Pull Request: Open a pull request from your feature branch to the staging branch. Ensure the pull request description clearly describes the changes and any additional context necessary for review.

Contributing

• Tieu-Long Phan
• Klaus Weinbauer
• Phuoc-Chung Nguyen Van
• Tuyet-Minh Phan

Publication

SynKit: A Graph-Based Python Framework for Rule-Based Reaction Modeling and Analysis

License

This project is licensed under MIT License - see the License file for details.

Acknowledgments

This project has received funding from the European Unions Horizon Europe Doctoral Network programme under the Marie-Skłodowska-Curie grant agreement No 101072930 (TACsy -- Training Alliance for Computational)