Usage
schemist has a variety of utilities which can be used through the command-line or the Python API.
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
You can access the underlying functions of schemist to help custom analyses or develop other tools.
>>> import schemist as sch