Abstract
We present the development of CyBy2, a versatile framework for chemical data management written in purely functional style in Scala, a modern multi-paradigm programming language. Together with the core libraries we provide a fully functional example implementation of a HTTP server together with a single page web client with powerful querying and visualization capabilities, providing essential functionality for people working in the field of organic and medicinal chemistry. The main focus of CyBy2 are the diverse needs of different research groups in the field and therefore the flexibility required from the underlying data model. Techniques for writing type level specifications giving strong guarantees about the correctness of the implementation are described, together with the resulting gain in confidence during refactoring. Finally we talk about the advantages of using a single code base from which the server, the client and the software’s documentation pages are being generated. We conclude with a comparison with existing open source solutions. All code described in this article is published under version 3 of the GNU General Public License and available from GitHub including an example implementation of both backend and frontend together with documentation how to download and compile the software (available at https://github.com/stefan-hoeck/cyby2).
Highlights
As researchers in the field of drug discovery we have very specific needs when it comes to electronically archiving and visualizing the results produced in our research group
Considering that many solutions in cheminformatics consist of thousands of lines of code written in dynamically typed scripting languages like Python (e.g. RDKit [3]), Perl (e.g. Perl bindings in OpenBabel [4]), Ruby (e.g. Chemotion ELN [2]), JavaScript (e.g. ChemDoodle [5]), PHP, or statically but—compared to the languages described below—weakly typed languages like Java (e.g. CDK [7]) or C++ (e.g. OpenBabel [4]), we believe these risks to be real and quite limitating
With the exception of raw file data and user settings, which are stored in a lightweight SQLite database, changes made to the data are stored incrementally in JSON format and the dataset is reassembled from these changes when the server is started
Summary
As researchers in the field of drug discovery we have very specific needs when it comes to electronically archiving and visualizing the results produced in our research group. It comes with powerful building blocks to write reactive user interfaces where users can conveniently analyze datasets in different views, define versatile combined queries including (sub)structure and similarity searches, and quickly add or modify data objects like compounds, linked files, or containers.
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