import pandas as pd
import salesforce_bulk as sf
from time import sleep

## PRODUCTION ENV
addresses = ['']
username = ''
password = ''
security_token = ''
client = ''
secret = ''

###############################################################################
###############################################################################

def SF_Dataframe(query_list, object_list):
    print('Establishing Connection to Salesforce')
    bulk = sf.SalesforceBulk(username = username,
                             password = password, security_token = security_token,
                             sandbox = False)
    print('Connection Established')

    def Run_SF_Query(query, object_name):
        job_id = bulk.create_query_job(object_name = object_name)

        batch_id = bulk.query(job_id = job_id, soql = query)

        bulk.close_job(job_id)

        while not bulk.is_batch_done(batch_id):
            sleep(1)

        results = bulk.get_all_results_for_query_batch(batch_id)


        for result in results:
            df = pd.read_csv(result)
            break

        return df

    dfs = []
    for query, obj in zip(query_list, object_list):
        df = Run_SF_Query(query, obj)
        print('-------------------------------------------')
        print('%s object has been queried.' % obj)
        print('-------------------------------------------')
        print()

        df.drop_duplicates(inplace = True)
        dfs.append(df)

    return dfs

#Below are the SOQL queries to send to Salesforce
queries = ["""

"""]

#These are the objects being queried
objects = ['']

#Returns a list (dfs) that has a dataframe for each query you ran
dfs = SF_Dataframe(queries, objects)