Metadata-Version: 2.1
Name: RXN4Chemistry
Version: 0.1.3
Summary: Python wrapper for IBM RXN for Chemistry
Home-page: https://github.com/rxn4chemistry/rxn4chemistry
Author: RXN for Chemistry team
Author-email: phs@zurich.ibm.com, tte@zurich.ibm.com
License: MIT
Description: # Python wrapper for the IBM RXN for Chemistry API
        
        [![Build Status](https://travis-ci.org/rxn4chemistry/rxn4chemistry.svg?branch=master)](https://travis-ci.org/rxn4chemistry/rxn4chemistry)
        [![PyPI version](https://badge.fury.io/py/RXN4Chemistry.svg)](https://badge.fury.io/py/RXN4Chemistry)
        [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
        
        ![logo](./docs_source/_static/logo.jpg)
        
        A python wrapper to access the API of the IBM RXN for Chemistry [website](https://rxn.res.ibm.com/rxn/).
        
        ## Install
        
        From PYPI:
        
        ```console
        pip install rxn4chemistry
        ```
        
        Or directly from the repo:
        
        ```console
        git+https://github.com/rxn4chemistry/rxn4chemistry.git
        ```
        
        ## Usage
        
        Get your API key from [here](https://rxn.res.ibm.com/rxn/user/profile) and build the wrapper:
        
        ```python
        api_key='API_KEY'
        from rxn4chemistry import RXN4ChemistryWrapper
        
        rxn4chemistry_wrapper = RXN4ChemistryWrapper(api_key=api_key)
        # NOTE: you can create a project or set an esiting one using:
        # rxn4chemistry_wrapper.set_project('PROJECT_ID')
        rxn4chemistry_wrapper.create_project('test_wrapper')
        print(rxn4chemistry_wrapper.project_id)
        ```
        
        Run a reaction prediction is as simple as:
        
        ```python
        response = rxn4chemistry_wrapper.predict_reaction(
            'BrBr.c1ccc2cc3ccccc3cc2c1'
        )
        results = rxn4chemistry_wrapper.get_predict_reaction_results(
            response['prediction_id']
        )
        print(results['payload']['attempts'][0]['smiles'])
        ```
        
        ## Examples
        
        An example on how to predict retrosynthesis for COVID19 candidates [here](./examples/diamond_light_source_covid19_candidates_retrosynthesis.ipynb).
        
        ## Documentation
        
        The documentation is hosted [here](https://rxn4chemistry.github.io/rxn4chemistry/) using GitHub pages.
        
        
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Description-Content-Type: text/markdown
