from mstrio import microstrategy
import pandas as pd
import json
from datetime import datetime
from mstrio.api import reports
from mstrio.utils.parsejson import parsejson
import concurrent.futures
import asyncio

base_url = "http://localhost:8080/MicroStrategyLibrary/api"
project_id = "2916035E465E16431D6012B3FF137342"
login = "administrator"
password = ""

async def main(): # declaration of asynchronous function
    def loadData(conn, report_id_value, instance_id_value, offset, limit_value):
        response = reports.report_instance_id(connection=conn, report_id = report_id_value, instance_id=instance_id_value, offset=offset, limit=limit_value)
        json_response = response.json()
        value = ""

        if 'result' in json_response:
            value = json_response['result']['data']['root']['children'][0]['element']['formValues']['DESC']
            table_data.append(parsejson(response=json_response))
        else:
            print("One record did not have any result. Offset: " + str(offset))

    conn = microstrategy.Connection(base_url, username=str(login), password=str(password), project_name="MicroStrategy Tutorial")
    conn.connect()

    startTime = datetime.now()
    limit_value = 2000
    report_id_value = "4B99AC5E41A66BB229D3ABAFEF812562" #"4B99AC5E41A66BB229D3ABAFEF812562 B95CAF1B42C8337B74BACA8D5E69C780"

    response = reports.report_instance(connection=conn, report_id = report_id_value, offset=0, limit=limit_value)
    json_response = response.json()

    instance_id_value = json_response['instanceId'] # retrieve instance id
    pagination = json_response['result']['data']['paging']

    table_data = [parsejson(response=json_response)]
    offset = limit_value
    with concurrent.futures.ThreadPoolExecutor(max_workers=2) as executor: # declare executor and amount of workers
        loop = asyncio.get_event_loop() # create a loop for workers to go through
        futures = [
            loop.run_in_executor(
                executor,
                loadData, conn, report_id_value, instance_id_value, offset, limit_value # apply loadData() function to the executor. It is declared at the begginning of main() function
            )
            for offset in range(limit_value, pagination['total'], limit_value) # loop conditions
        ]
        for response in await asyncio.gather(*futures):
            pass

    instance = pd.concat(table_data)
    res_df = pd.DataFrame(instance)
    print("Rows: " + str(len(res_df)) + "  Limit: " + str(limit_value) + " Time: " + str((datetime.now() - startTime)))
    #df = res_df.as_matrix()

    #for x in range(0, len(res_df), limit_value):
    #    print("Offset: " + str(x) + " ; value: " + str(df[x][0]))

loop = asyncio.get_event_loop()
loop.run_until_complete(main()) # run main() function asynchronously