drugs4diseases.py

from ENTELLECT_API.ElsevierAPI.utils import execution_time, Tee
from ENTELLECT_API.ElsevierAPI.ResnetAPI.Drugs4Disease import Drugs4Targets
from ENTELLECT_API.ElsevierAPI.ResnetAPI.PathwayStudioZeepAPI import load_api_config
import pandas as pd
from datetime import datetime
import time,json


def do_the_job(dt:Drugs4Targets):
    dt.make_report()
    # dt.add_etm_refs('Drugs',['glioma'])

    report_fpath = dt.report_path('.xlsx')
    dt.print_report(report_fpath)

    raw_data_fpath= dt.report_path('_raw_data.xlsx')
    dt.print_rawdata(raw_data_fpath)

    dt.clear()
    

if __name__ == "__main__":
    print(f'Script was started at {datetime.now()}')
    start = time.time()
    
    for parameters in parameters_list:
        assert isinstance(parameters,dict)
        skip = parameters.pop('skip', False)
        if not skip:
            disease_start = time.time()
            
            dt = Drugs4Targets(load_api_config(), **parameters)
            print(f'Finding drugs for {parameters["disease"]}')
            print(f'Script started at {datetime.now()}')
            log_path = dt.report_path('.log')
            print(f'Runtime messages will be written to "{log_path}"')
            with Tee(log_path):
                do_the_job(dt)
            print(f'{parameters["disease"]} finished in {execution_time(disease_start)} at {datetime.now()}')
            print(f'Total script execution time: {execution_time(start)}')

    print(f'Script finished in {execution_time(start)} at {datetime.now()}')