BioClients

Python package for access to online biomedical resources, usually via REST APIs. Modules generally include Client.py for command-line use and Utils.py for integration into other code. With the advent of HTTP web services, first SOAP/XML and then mostly REST/JSON, many online APIs require very similar methods for data search, requests and transforms into usable formats, often CSV/TSV.

Availability and installation

Source at https://github.com/jeremyjyang/BioClients; releases available via pypi.org: https://pypi.org/project/BioClients/ (pip3 install BioClients).

However, current development snapshot recommended.

(First download or clone.)

$ cd BioClients
$ python3 setup.py install

Dependencies

• Python 3.6+
• Python packages: pandas, requests, urllib, json, xml, yaml, psycopg2, tqdm, etc.

Modules

AMP-T2D • BioGrid • BRENDA • Chem2Bio2RDF • ChEMBL • Disease Ontology • DisGeNet • DNorm • DrugCentral • EnsEMBL • FDA • Gene Ontology • GWAS Catalog • HUGO • HumanBase • iCite • IDG • JensenLab • LINCS • MaayanLab • MeSH • MONARCH • OMIM • Open Targets • Panther • PDB • PubChem • PubMed • PubTator • Reactome • RXNorm • STRINGDB • TCGA • TIN-X • UMLS • UniProt

Usage

$ python3 -m BioClients.pubchem.Client -h

Data structures and formats, XML, JSON, and CSV/TSV

BioClients is designed to be simple and practical, and XML, JSON and CSV/TSV are likewise simple in many respects, yet a great deal of conceptual and technological progress is reflected. XML and JSON can represent arbitrarily complex data objects, comprised of nested lists, dictionaries, and trees of primary types. CSV/TSV represents tables of rows and columns, related by common keys, reflecting the development of SQL and relational databases. Transforming JSON to CSV/TSV, as these clients generally do, projects data objects to tables useful for many applications (e.g. machine learning).