⬢⬢⬢ schemist

Cleaning, collating, and augmenting chemical datasets.

• Installation
• Command-line usage
• Python API
• Documentation

Installation

The easy way

Install the pre-compiled version from PyPI:

pip install schemist

From source

Clone the repository, then cd into it. Then run:

pip install -e .

Command-line usage

schemist provides command-line utlities. The list of commands can be checked like so:

$ schemist --help
usage: schemist [-h] [--version] {clean,convert,featurize,collate,dedup,enumerate,react,split} ...

Tools for cleaning, collating, and augmenting chemical datasets.

options:
  -h, --help            show this help message and exit
  --version, -v         show program's version number and exit

Sub-commands:
  {clean,convert,featurize,collate,dedup,enumerate,react,split}
                        Use these commands to specify the tool you want to use.
    clean               Clean and normalize SMILES column of a table.
    convert             Convert between string representations of chemical structures.
    featurize           Convert between string representations of chemical structures.
    collate             Collect disparate tables or SDF files of libraries into a single table.
    dedup               Deduplicate chemical structures and retain references.
    enumerate           Enumerate bio-chemical structures within length and sequence constraints.
    react               React compounds in silico in indicated columns using a named reaction.
    split               Split table based on chosen algorithm, optionally taking account of chemical structure during splits.

Each command is designed to work on large data files in a streaming fashion, so that the entire file is not held in memory at once. One caveat is that the scaffold-based splits are very slow with tables of millions of rows.

All commands (except collate) take from the input table a named column with a SMILES, SELFIES, amino-acid sequence, HELM, or InChI representation of compounds.

The tools complete specific tasks which can be easily composed into analysis pipelines, because the TSV table output goes to stdout by default so they can be piped from one tool to another.

To get help for a specific command, do

schemist <command> --help

For the Python API, see below.

Python API

schemist can be imported into Python to help make custom analyses.

>>> import schemist as sch

Documentation

Full API documentation is at ReadTheDocs.