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).
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