From cclib

Welcome to cclib

cclib is an open source library, written in Python, for parsing and interpreting the results of computational chemistry packages. The current version, cclib 0.9, parses output files from ADF, GAMESS (US), GAMESS-UK, Gaussian, Jaguar, Molpro, ORCA and PC GAMESS. See what's new in cclib 0.9.

The goals of cclib

• to facilitate the implementation of algorithms that are not specific to a particular computational chemistry package
• to provide a simple and standard interface to the results of computational chemistry calculations, particularly those results that are useful for algorithms or visualisation
• to maximise interoperability with other open source computational chemistry and cheminformatic software libraries

Capabilities of cclib

Among other data, cclib extracts:

• atom coordinates
• atomic orbital information
• molecular orbital information
• information on vibrational modes
• the results of TD-DFT calculations

(For a complete list see Extracted Data).

cclib also provides some calculation methods for interpreting some electronic properties of molecules using analyses such as:

• Mulliken population analysis
• Overlap population analysis
• Calculation of Mayer's bond orders.

How to use cclib

To download cclib, click here. For information on how to use cclib, see the tutorial. Applications that use cclib include GaussSum and QMForge.

About cclib

If you need help, find a bug, want new features or have any questions, please send an email to our mailing list. To keep up to date with the latest news, use this RSS feed.

cclib started as a collaboration between Noel O'Boyle and Adam Tenderholt, later joined by Karol Langner. Other developers are encouraged to contribute to this open source project (send an email to the developers mailing list). cclib is licensed under the LGPL.

How to cite cclib

If you use cclib in your scientific work, please support our work by adding reference to the following article:

• N. M. O'Boyle, A. L. Tenderholt, K. M. Langner, cclib: a library for package-independent computational chemistry algorithms, J. Comp. Chem. 29 (5), pp. 839-845, 2008 (DOI).