Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/rdkit/mongo-rdkit
GSoC 2020 project to integrate the RDKit and MongoDb
https://github.com/rdkit/mongo-rdkit
Last synced: about 2 months ago
JSON representation
GSoC 2020 project to integrate the RDKit and MongoDb
- Host: GitHub
- URL: https://github.com/rdkit/mongo-rdkit
- Owner: rdkit
- License: bsd-2-clause
- Created: 2020-05-28T07:25:40.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2021-04-21T03:54:45.000Z (over 3 years ago)
- Last Synced: 2024-03-25T20:06:01.519Z (9 months ago)
- Language: Python
- Homepage:
- Size: 317 KB
- Stars: 16
- Watchers: 6
- Forks: 7
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# mongo-rdkit
[](https://dev.azure.com/cwzou/mongo-rdkit/_build/latest?definitionId=1&branchName=master)
Mongo-rdkit is an integration between MongoDB,
a NoSQL database platform, and RDKit, a collection of cheminformatics and machine-learning software.
This package contains tools to create and manipulate a chemically-intelligent database, as well as
methods for high-performance searches on the database that leverage native MongoDB features.
Useful links:
* [BSD License](https://github.com/rdkit/mongo-rdkit/blob/master/LICENSE) - a business friendly license for open-source.
* [Jupyter Notebooks](https://github.com/rdkit/mongo-rdkit/tree/master/docs) - walkthroughs for main functionality.
* [Testing Guide](https://github.com/rdkit/mongo-rdkit/blob/master/docs/testing.md) - walkthrough of running `mongordkit` tests.
## Documentation
Jupyter Notebooks and resources for getting started in the [docs](https://github.com/rdkit/mongo-rdkit/tree/master/docs)
folder on GitHub.
## Installation
### macOS and Linux:
Ensure that you have either Anaconda or Miniconda installed and that `conda` has been added to `PATH`.
Clone the repository into your desired directory.
Navigate so that your current working directory is `mongo-rdkit`.
Create a conda environment called mongo_rdkit that includes all dependencies needed for this package:
```
conda env create --quiet --force --file env.yml
```
Activate said conda environment:
```
source activate mongo_rdkit
```
Install a local copy of mongo-rdkit by running this from the same directory as `setup.py` (`mongo-rdkit` is not yet published to PyPI):
```
pip install -e .
```
You can now `import mongordkit` in your Python interpreter or run all tests using the `pytest` command.
### Windows:
Similarly, ensure that `conda` has been added to `PATH`.
Clone the repository into your desired directory and navigate into it.
Create a conda environment called mongo_rdkit that includes dependencies:
```
conda env create --quiet --force --file env.yml
```
Activate this conda environment:
```
call activate mongo_rdkit
```
Check that you are able to import mongordkit:
```
python -c "import mongordkit"
```
If this fails, you may need to add the current directory manually to `PYTHONPATH`:
```
set PYTHONPATH=%PYTHONPATH%;C:.
```
You can now use `mongordkit` in your interpreter and run tests using `python -m pytest`.
## Package Contents
### Modules
`mongordkit` contains two main modules, each of which contains a variety of importable methods and classes.
`Database` contains functionality for writing and registering data. `Search` contains functionality for setting up and performing
substructure and similarity search. Detailed walkthroughs can be found in the notebooks, listed below.
### Notebooks
- **Creating and Writing to MongoDB**: documentation and demos for creating and modifying mongo-rdkit databases.
- **Similarity and Substructure Search**: documentation and demos for similarity and substructure search.
- **Similarity Benchmarking**: documentation for reproducing similarity benchmarking.
- **Substructure Benchmarking**: documentation for reproducing substructure benchmarking.
### Configuration
- **azure_pipelines.yml**: CI/CD pipeline configurations.
- **conftest.py**: `pytest` configurations.
- **env.yml**: required dependencies.
- **setup.py**: python package setup including pip dependencies
## License
Code released under the BSD License.