Metadata-Version: 2.1
Name: BioClients
Version: 0.2.16
Summary: Clients for online biomedical resources, usually via REST APIs.
Home-page: https://github.com/jeremyjyang/BioClients
Author: Jeremy Yang
Author-email: jeremyjyang@gmail.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE

# `BioClients` <img align="right" src="doc/images/BioClients_logo.png" height="120" alt="BioClients logo">

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 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 may included additional functionality.

___(First download or clone.)___
```
$ cd BioClients
$ python3 setup.py install
```

## Dependencies

* Python 3.8+
* Python packages: `pandas`, `requests`, `yaml`, `psycopg2`, `tqdm`, etc. (See [conda/environment.yml](conda/environment.yml)).

## Modules

 [__Allen__](doc/allen.md) &#8226; [__AMP-T2D__](doc/amp__t2d.md) &#8226; [__BindingDb__](doc/bindingdb.md) &#8226; [__BioGrid__](doc/biogrid.md) &#8226; [__Bioregistry__](doc/bioregistry.md) &#8226; [__BRENDA__](doc/brenda.md) &#8226; [__CAS__](doc/cas.md) &#8226; [__CDC__](doc/cdc.md) &#8226; [__CFDE__](doc/cfde.md) &#8226; [__Chem2Bio2RDF__](doc/chem2bio2rdf.md) &#8226; [__ChEBI__](doc/chebi.md) &#8226; [__ChEMBL__](doc/chembl.md) &#8226; [__ChemIdPlus__](doc/chemidplus.md) &#8226; [__ClinicalTrials.gov__](doc/clinicaltrials.md) &#8226; [__Disease Ontology__](doc/diseaseontology.md) &#8226; [__DisGeNet__](doc/disgenet.md) &#8226; [__DNorm__](doc/dnorm.md) &#8226; [__DrugCentral__](doc/drugcentral.md) &#8226; [__EMBL-EBI__](doc/emblebi.md) &#8226; [__EnsEMBL__](doc/ensembl.md) &#8226; [__FDA__](doc/fda.md) &#8226; [__Gene Ontology__](doc/geneontology.md) &#8226; [__GTEx__](doc/gtex.md) &#8226; [__GWAS Catalog__](doc/gwascatalog.md) &#8226; [__HUGO__](doc/hugo.md) &#8226; [__HumanBase__](doc/humanbase.md) &#8226; [__iCite__](doc/icite.md) &#8226; [__IDG__](doc/idg.md) &#8226; [__JensenLab__](doc/jensenlab.md) &#8226; [__LINCS__](doc/lincs.md) &#8226; [__MaayanLab__](doc/maayanlab.md) &#8226; [__Medline__](doc/medline.md) &#8226; [__MeSH__](doc/mesh.md) &#8226; [__MONARCH__](doc/monarch.md) &#8226; [__MyGene__](doc/mygene.md) &#8226; [__NCBO__](doc/ncbo.md) &#8226; [__NCATS__](doc/ncats.md) &#8226; [__OMIM__](doc/omim.md) &#8226; [__OncoTree__](doc/oncotree.md) &#8226; [__Open Targets__](doc/opentargets.md) &#8226; [__Panther__](doc/panther.md) &#8226; [__PDB__](doc/pdb.md) &#8226; [__PubChem__](doc/pubchem.md) &#8226; [__PubMed__](doc/pubmed.md) &#8226; [__PubTator__](doc/pubtator.md) &#8226; [__Reactome__](doc/reactome.md) &#8226; [__RXNorm__](doc/rxnorm.md) &#8226; [__STRINGDB__](doc/stringdb.md) &#8226; [__TCGA__](doc/tcga.md) &#8226; [__UBKG__](doc/ubkg.md) &#8226; [__UMLS__](doc/umls.md) &#8226; [__UniProt__](doc/uniprot.md) &#8226; [__Wikidata__](doc/wikidata.md) &#8226; [__WikiPathways__](doc/wikipathways.md) 

Miscellaneous utilities: [__UTIL__](doc/util.md) 

## Usage Example

```
$ python3 -m BioClients.pubchem.Client -h
```

## Design pattern

Generally each module includes command-line app `Client.py` which calls 
functions in a corresponding `Utils.py`, providing all capabilities
by import of the module. Command-line apps not API clients are generally 
named `App.py`. Functions can write to an output file
or return a Pandas dataframe (if output file unspecified).

## Data structures and formats, XML, JSON, and TSV

BioClients is designed to be simple and practical, and XML, JSON
and 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. TSV represents tables of
rows and columns, related by common keys, reflecting the development
of SQL and relational databases. Transforming JSON to TSV, as these
clients generally do, projects data objects to tables useful for many
applications (e.g. machine learning).


