#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# This file is part of the `pypath` python module
#
# Copyright 2014-2023
# EMBL, EMBL-EBI, Uniklinik RWTH Aachen, Heidelberg University
#
# Authors: see the file `README.rst`
# Contact: Dénes Türei (turei.denes@gmail.com)
#
# Distributed under the GPLv3 License.
# See accompanying file LICENSE.txt or copy at
# https://www.gnu.org/licenses/gpl-3.0.html
#
# Website: https://pypath.omnipathdb.org/
#
from __future__ import annotations
from collections import namedtuple
import json
import bs4
import requests
import json
import pandas as pd
import pypath.share.curl as curl
import pypath.resources.urls as urls
[docs]
def ddinter_n_drugs() -> int:
"""
Retrieves number of drug records in the DDInter database.
"""
cookies = {
'csrftoken': '975RT1K1FXpLX6wZdcyTMIRdOAMwNNkx1MNFAbeJrlrRBFI5DbNmaQPz7tj2UNFZ',
}
data = {
'csrfmiddlewaretoken': 'ToKztkgeCHgBfAbezQL7GULrQABtRmHgL3snauKWo5iHT9nkZP0A42JN9t8ZYm2I',
'draw': '1',
'columns[0][data]': '',
'columns[0][name]': '',
'columns[0][searchable]': 'true',
'columns[0][orderable]': 'false',
'columns[0][search][value]': '',
'columns[0][search][regex]': 'false',
'start': '0',
'length': '24',
'search[value]': '',
'search[regex]': 'false',
'custom-length': '25',
}
url = urls.urls['ddinter']['source']
response = requests.post(
url,
cookies = cookies,
data = data,
verify = False,
)
return int(response.json()['recordsTotal'])
[docs]
def ddinter_identifiers(drug: str) -> list[tuple]:
"""
DrugBank, ChEMBL and PubChem identifiers of a drug in DDInter.
Args:
drug:
DDInter drug identifier.
Returns:
list of mapping namedtuple (single)
"""
url = urls.urls['ddinter']['mapping'] % drug
c = curl.Curl(url, silent = False, large = True)
soup = bs4.BeautifulSoup(c.fileobj, 'html.parser')
refs = soup.find_all('a')
links = [link.get('href', '') for link in refs]
result = set()
fields = ('ddinter', 'drugbank', 'chembl', 'pubchem')
record = namedtuple('DdinterIdentifiers', fields, defaults = (None, ) * len(fields))
mapping_targets = ['drugbank', 'chembl', 'pubchem']
mapping_dict = {}
for link in links:
for target in mapping_targets:
if target in link:
mapping_dict[target] = link.split('/')[-1]
break
result.add(record(ddinter = drug, **mapping_dict))
return list(result)
[docs]
def ddinter_mappings(return_df: bool = False) -> list[tuple] | pd.DataFrame:
"""
DrugBank, ChEMBL and PubChem identifiers of all drugs in DDInter.
Args:
return_df:
Return a pandas data frame.
Returns:
list of mapping namedtuples
"""
result = []
for idx in range(1, ddinter_n_drugs() + 1):
ddinter_drug = f'DDInter{idx}'
result.extend(ddinter_identifiers(ddinter_drug))
return pd.DataFrame(result) if return_df else result
def _ensure_hashable(data):
if isinstance(data, (dict, list, set)):
return tuple(data)
return data
[docs]
def ddinter_drug_interactions(
drug: str,
return_df: bool = False,
) -> list[tuple] | pd.DataFrame:
"""
Interactions of one single drug from the DDInter database.
Args:
drug:
A DDInter drug identifier.
return_df:
Return a pandas data frame.
Returns:
Drug-drug interaction tuples with drug ids, drug names, interaction
level and actions.
"""
url = urls.urls['ddinter']['interaction'] % drug
c = curl.Curl(url)
data = json.loads(c.result)
result = set()
record = namedtuple(
'DdinterInteraction',
(
'drug1_id',
'drug1_name',
'drug2_id',
'drug2_name',
'level',
'actions',
),
defaults = None,
)
drug1_id = data['info']['id']
drug1_name = data['info']['Name']
for interaction_fe in data['interactions']:
interaction = record(
drug1_id = drug1_id,
drug1_name = drug1_name,
drug2_id = _ensure_hashable(interaction_fe['id']),
drug2_name = _ensure_hashable(interaction_fe['name']),
level = _ensure_hashable(interaction_fe['level']),
actions = _ensure_hashable(interaction_fe['actions']),
)
result.add(interaction)
return pd.DataFrame(result) if return_df else result
[docs]
def ddinter_interactions(return_df: bool = False) -> list[tuple] | pd.DataFrame:
"""
Drug-drug interactions from the DDInter database.
Args:
return_df:
Return a pandas data frame.
Returns:
list of interaction namedtuple with drug ids, drug names, interaction level and actions
"""
result = [
ddinter_drug_interactions(drug = f'DDInter{i}')
for i in range(1, ddinter_n_drugs()+1)
]
return pd.DataFrame(result) if return_df else result
