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InterLex client library documentation

Project Details

Project Details

InterLexClient is meant to help outside curators add entities and annotations in an efficient process.

Prerequisites

python==3.65 +
requests==2.18.4 +
pytest==3.10.0 +

pip3 install requests
pip3 install pytest

API_KEY

Get your api_key via SciCrunch

Register
Login
While on home page go to MY ACCOUNT. API KEYS will be 4th from the bottom
Provide Password
Click [Generate an API key] in the middle of the screen
copy and paste the 32 character api_key to .bashrc or .zshrc (if using zsh)

How it should look in your .bashrc or .zshrc file:
```
export INTERLEX_API_KEY="YOUR API KEY HERE"
```

Running the tests

Pytest with -v option for verbose

pytest -v test/test_interlex_client.py

Directions in how to use InterLexClient

Importing:

from ontquery.interlex import interlex_client

Setup for TEST:
This Should be used to test if your code works first
```
ilx_cli = interlex_client('test3.scicrunch.org')
```

Setup for PRODUCTION:

ilx_cli = interlex_client('scicrunch.org')

Adding Entity Needed:

added_entity_data = ilx_cli.add_entity(
    label = '',
    type = '', # term, fde, cde, pde, relationship, annotation
)

Adding Entity Example

added_entity_data = ilx_cli.add_entity(
    label = 'Label of entity you wish to create',
    type = 'A type that should be one of the following: term, relationship, annotation, cde, fde, pde',
    # subThingOf can take either iri or curie form of ID
    subThingOf = 'http://uri.interlex.org/base/ilx_0108124', # superclass or subClassOf ILX ID
    definition = 'Entities definition',
    comment = 'A comment to help understand entity',
    synonyms = ['synonym1', {'literal': 'synonym2', 'type': 'hasExactSynonym'}, 'etc'],
    # exisiting IDs are List[dict] with keys iri & curie
    existing_ids = [{'iri':'https://example.org/example_1', 'curie':'EXAMPLE:1'}],
    cid = 504,  # community ID
    predicates = {
        # annotation_entity_ilx_id : 'annotation_value',
        'http://uri.interlex.org/base/tmp_0381624': 'PMID:12345', # annotation
        # relationship_entity_ilx_id : 'entity2_ilx_id',
        'http://uri.interlex.org/base/ilx_0112772': 'http://uri.interlex.org/base/ilx_0100001', # relationship
    }
)

Updating Entity Example

updated_entity = update_entity( 
    ilx_id='ilx_1234567', 
    label='Brain', 
    type='term',  # options: term, pde, fde, cde, annotation, or relationship 
    definition='Official definition for entity.', 
    comment='Additional casual notes for the next person.', 
    superclass='ilx_1234567', 
    add_synonyms=[{ 
        'literal': 'Better Brains',  # label of synonym 
        'type': 'obo:hasExactSynonym',  # Often predicate defined in ref ontology. 
    }], 
    delete_synonyms=[{ 
        'literal': 'Brains',  # label of synonym 
        'type': 'obo:hasExactSynonym',  # Often predicate defined in ref ontology. 
    }], 
    add_existing_ids=[{ 
        'iri': 'http://purl.obolibrary.org/obo/UBERON_0000956', 
        'curie': 'UBERON:0000956',  # Obeys prefix:id structure. 
        'preferred': '1',  # Can be 0 or 1 with a type of either str or int. 
    }], 
    delet_existing_ids=[{ 
        'iri': 'http://purl.obolibrary.org/obo/UBERON_0000955', 
        'curie': 'UBERON:0000955',  # Obeys prefix:id structure. 
    }], 
    cid='504',  # SPARC Community, 
    status='0',  # remove delete 
)

Both functions add_entity() and add_annotation() will return a dictionary of the populated data for the entity or term even if it already existed. If it already exists it will just print a warning saying it already exists, but again, it will return the dictionary of its populated data anyway.

Because of this simple logic, it would be perfectly fine to be lazy and re-add any entities or annotations if it crashed half way through because of a string error on your end once it is fixed.

Example add_entity output

{
    "id": "304713",
    "orig_uid": "34142",
    "uid": "34142",
    "orig_cid": "0",
    "cid": "0",
    "ilx": "tmp_0381629",
    "label": "brain",
    "type": "pde",
    "definition": "Part of the central nervous system",
    "comment": "Cannot live without it",
    "version": "1",
    "status": "0",
    "display_superclass": "1",
    "orig_time": "1541459612",
    "time": "1541459612",
    "synonyms": [{
        "id": "375931",
        "tid": "304713",
        "literal": "Encephalon",
        "type": "",
        "time": "1541459612",
        "version": "1",
    }],
    "superclasses": [{
        "id": 340809,
        "tid": 304820,
        "superclass_tid": 8125,
        "version": 1,
        "time": 1541618830,
    }],
    "existing_ids": [
        {
            "id": "416448",
            "tid": "304713",
            "curie": "BIRNLEX:796",
            "iri": "http://uri.neuinfo.org/nif/nifstd/birnlex_796",
            "curie_catalog_id": "0",
            "version": "1",
            "time": "1541459612",
            "preferred": "1"
        },
        {
            "id": "416449",
            "tid": "304713",
            "curie": "ILX:0381629",
            "iri": "http://uri.interlex.org/base/ilx_0381629",
            "curie_catalog_id": "3",
            "version": "1",
            "time": "1541459613",
            "preferred": "0"
        }
    ],
    "relationships": [],
    "mappings": [],
    "annotations": [],
    "ontologies": []
}

Notes

Dictionay outputs from add_entity and update_entity will not always have string type for the values. That does not matter for the api endpoints, but just in case this data is used somewhere else, this should be noted.

Author

Troy Sincomb

License

MIT