Skip to main content

A collection of chemoinformatics and machine-learning software written in C++ and Python

Project description

RDKit

Azure build Status Documentation Status DOI

RDKit is a collection of cheminformatics and machine-learning software written in C++ and Python.

  • BSD license - a business friendly license for open source
  • Core data structures and algorithms in C++
  • Python 3.x wrapper generated using Boost.Python
  • Java and C# wrappers generated with SWIG
  • 2D and 3D molecular operations
  • Descriptor and Fingerprint generation for machine learning
  • Molecular database cartridge for PostgreSQL supporting substructure and similarity searches as well as many descriptor calculators
  • Cheminformatics nodes for KNIME
  • Contrib folder with useful community-contributed software harnessing the power of the RDKit

Web presence

Code

Community

Materials from user group meetings

Documentation

Available on the RDKit page and in the Docs folder on GitHub

Installation

Installation instructions are available in Docs/Book/Install.md.

Binary distributions, anaconda, homebrew

  • binaries for conda python or, if you are using the conda-forge stack, the RDKit is also available from conda-forge.
  • RPMs for RedHat Enterprise Linux, Centos, and Fedora. Contributed by Gianluca Sforna.
  • debs for Ubuntu and other Debian-derived Linux distros. Contributed by the Debichem team.
  • homebrew formula for building on the Mac. Contributed by Eddie Cao.
  • recipes for building using the excellent conda package manager. Contributed by Riccardo Vianello.
  • APKs for Alpine Linux. Contributed by da Verona

Projects using RDKit

  • stk (docs, paper) - a Python library for building, manipulating, analyzing and automatic design of molecules.
  • gpusimilarity - A Cuda/Thrust implementation of fingerprint similarity searching
  • Samson Connect - Software for adaptive modeling and simulation of nanosystems
  • mol_frame - Chemical Structure Handling for Dask and Pandas DataFrames
  • RDKitjs - port of RDKit functionality to JavaScript
  • DeepChem - python library for deep learning for chemistry
  • mmpdb - Matched molecular pair database generation and analysis
  • CheTo (paper)- Chemical topic modeling
  • OCEAN (paper)- Optimized cross reactivity estimation
  • ChEMBL Beaker - standalone web server wrapper for RDKit and OSRA
  • myChEMBL (blog post, paper) - A virtual machine implementation of open data and cheminformatics tools
  • ZINC - Free database of commercially-available compounds for virtual screening
  • sdf_viewer.py - an interactive SDF viewer
  • sdf2ppt - Reads an SDFile and displays molecules as image grid in powerpoint/openoffice presentation.
  • MolGears - A cheminformatics tool for bioactive molecules
  • PYPL - Simple cartridge that lets you call Python scripts from Oracle PL/SQL.
  • shape-it-rdkit - Gaussian molecular overlap code shape-it (from silicos it) ported to RDKit backend
  • WONKA - Tool for analysis and interrogation of protein-ligand crystal structures
  • OOMMPPAA - Tool for directed synthesis and data analysis based on protein-ligand crystal structures
  • OCEAN - web-tool for target-prediction of chemical structures which uses ChEMBL as datasource
  • chemfp - very fast fingerprint searching
  • rdkit_ipynb_tools - RDKit Tools for the IPython Notebook
  • Vernalis KNIME nodes
  • Erlwood KNIME nodes
  • AZOrange

License

Code released under the BSD license.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

rdkit_pypi-2020.9.5.2-cp39-cp39-manylinux2014_x86_64.whl (39.2 MB view details)

Uploaded CPython 3.9

rdkit_pypi-2020.9.5.2-cp38-cp38-manylinux2014_x86_64.whl (39.2 MB view details)

Uploaded CPython 3.8

rdkit_pypi-2020.9.5.2-cp37-cp37m-manylinux2014_x86_64.whl (39.0 MB view details)

Uploaded CPython 3.7m

rdkit_pypi-2020.9.5.2-cp36-cp36m-manylinux2014_x86_64.whl (39.0 MB view details)

Uploaded CPython 3.6m

File details

Details for the file rdkit_pypi-2020.9.5.2-cp39-cp39-manylinux2014_x86_64.whl.

File metadata

  • Download URL: rdkit_pypi-2020.9.5.2-cp39-cp39-manylinux2014_x86_64.whl
  • Upload date:
  • Size: 39.2 MB
  • Tags: CPython 3.9
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/3.8.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.8.8

File hashes

Hashes for rdkit_pypi-2020.9.5.2-cp39-cp39-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 29fd9c37228d0d239aad53823faa762fad41b1918c095f2e7106d3371cd7227f
MD5 a0cf0ea931ca6730dc636a0a28250d7f
BLAKE2b-256 fab84d08025c4d597d647f1dd54471672c22fc2c02d7df328f85a4bff6bcdf1f

See more details on using hashes here.

File details

Details for the file rdkit_pypi-2020.9.5.2-cp38-cp38-manylinux2014_x86_64.whl.

File metadata

  • Download URL: rdkit_pypi-2020.9.5.2-cp38-cp38-manylinux2014_x86_64.whl
  • Upload date:
  • Size: 39.2 MB
  • Tags: CPython 3.8
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/3.8.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.8.8

File hashes

Hashes for rdkit_pypi-2020.9.5.2-cp38-cp38-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 202018ac11427f927f8c73a0398fbffea1c3d7fa2211cce5d7d214138ea6efa9
MD5 ebb7d8ee5422869228b3bd77a679112c
BLAKE2b-256 f06fc6285ed6baf08b8a29bd6cd2fb0c2f0e85f481af970f2be69436a87c8f2e

See more details on using hashes here.

File details

Details for the file rdkit_pypi-2020.9.5.2-cp37-cp37m-manylinux2014_x86_64.whl.

File metadata

  • Download URL: rdkit_pypi-2020.9.5.2-cp37-cp37m-manylinux2014_x86_64.whl
  • Upload date:
  • Size: 39.0 MB
  • Tags: CPython 3.7m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/3.8.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.8.8

File hashes

Hashes for rdkit_pypi-2020.9.5.2-cp37-cp37m-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 4a4a3402a0c09ca6a2013ea4c689a62bceb27ddbd3f92e67d4b5ddac54dfa167
MD5 15dbe813724d2f2d53d56880679d3245
BLAKE2b-256 bab3facb4d6474433de043a24bad45584b43e21cd8ea2b203dc6759d789169dc

See more details on using hashes here.

File details

Details for the file rdkit_pypi-2020.9.5.2-cp36-cp36m-manylinux2014_x86_64.whl.

File metadata

  • Download URL: rdkit_pypi-2020.9.5.2-cp36-cp36m-manylinux2014_x86_64.whl
  • Upload date:
  • Size: 39.0 MB
  • Tags: CPython 3.6m
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/3.8.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.59.0 CPython/3.8.8

File hashes

Hashes for rdkit_pypi-2020.9.5.2-cp36-cp36m-manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 6ca32243d68a701986fa686eca721cfd7a54fdb889d34d9e20c9b62898047529
MD5 9f03b6fc3631ad74de1847ed6458a2a4
BLAKE2b-256 8b0d526f9a0d35f7cc40474e99eba32fca13c143178ba9901c455872893c288d

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page