booldog.io.biomodels

API to download and use SBML-qual models from the BioModels database (https://www.biomodels.org/) directly.

Attributes

`logger`
`BIOMODELS_BASE_URL`
`MAMO_ACCESSIONS`	MAMO accessions for models that are compatible with BoolDog.
`EXAMPLE_MODEL_ID`	BioModels model identifier for an example SBML-qual model (Chaouiya2013

Functions

`fetch_model`(model_id[, sbml_file, local_file, ...])	Fetch SBML from BioModels by model id
`fetch_model_info`(model_id)	Fetch model info/metadata from BioModels by model id.
`_download`(model_id[, filename, local_file])	Downloads a file from a model in BioModels, via

Module Contents

booldog.io.biomodels.logger

booldog.io.biomodels.BIOMODELS_BASE_URL = 'https://www.biomodels.org/'

booldog.io.biomodels.MAMO_ACCESSIONS = ['MAMO_0000030', 'MAMO_0000053']

MAMO accessions for models that are compatible with BoolDog.

The list contains the following accessions: * MAMO_0000030: logical model (http://identifiers.org/mamo/MAMO_0000030) * MAMO_0000053: Boolean model (http://identifiers.org/mamo/MAMO_0000053)

Type:: list

booldog.io.biomodels.EXAMPLE_MODEL_ID = 'BIOMD0000000562'

BioModels model identifier for an example SBML-qual model (Chaouiya2013 - EGF and TNFalpha mediated signalling pathway). See https://www.ebi.ac.uk/biomodels/BIOMD0000000562 for more details.

Type:: str

booldog.io.biomodels.fetch_model(model_id, sbml_file=None, local_file=None, check_modelling_approach=False)

Fetch SBML from BioModels by model id

Parameters:

model_id (str) – BioModels model identifier (e.g. ‘BIOMD0000000562’)
sbml_file (str) – Currently unused: this argument’s value is discarded and always overwritten by the name found in the model’s metadata (via model_info['files']['main'], the first entry whose description starts with “sbml”/”SBML”) before use.
local_file (str or path-like) – Name of path to save the downloaded model to. Optional, if not given will save the model to the a file in the cwd with the name as on the remote server.
check_modelling_approach (Bool) – Whether to check modelling annotation “modellingApproach” falls into Boolean or logical modelling.

Returns:

local_file – Name of the local file containing the download.

Return type:

str

Raises:

ValueError – If check_modelling_approach is True and the model’s “modellingApproach” annotation is not in MAMO_ACCESSIONS; if the model’s format (per its metadata) is not SBML; if no file in the model’s metadata has a description starting with “SBML”/”sbml”; or if the download request fails (see _download()).

Notes

This first collects the model info/metadata, and uses the ‘files’ –> ‘main’ attribute to find a file whose description starts with ‘SBML’/’sbml’ (case-insensitive). If more than one file matches, the last matching entry in the list is used (the loop does not stop at the first match).

Will always overwrite an existing file.

booldog.io.biomodels.fetch_model_info(model_id)

Fetch model info/metadata from BioModels by model id.

Parameters:: model_id (str) – BioModels model identifier (e.g. ‘BIOMD0000000562’)
Returns:: Model info/metadata as a dictionary, parsed directly from the JSON response of BioModels’ GET /{model_id}?format=json endpoint.
Return type:: dict

booldog.io.biomodels._download(model_id, filename=None, local_file=None)

Downloads a file from a model in BioModels, via GET /model/download/{model_id}.

Parameters:

model_id (str) – BioModels model identifier (e.g. ‘BIOMD0000000562’)
filename (str, optional) – Name of a specific file within the model’s archive to download (passed as the filename query parameter). If None, the whole model archive is downloaded instead.
local_file (str or path-like, optional) – Path to save the downloaded content to. If None, defaults to filename (if given) or "{model_id}.omex" (if not), saved relative to the current working directory.

Returns:

local_file – Name/path of the local file containing the download.

Return type:

str or Path

Raises:

ValueError – If the HTTP response indicates failure (non-OK status code).