import django
from time import time
from pyscada.models import Variable
from concurrent.futures import ThreadPoolExecutor, ProcessPoolExecutor



def subprocess_setup():
    django.setup()
    from django.db import connections
    for conn in connections.all():
        conn.close()

def process_variables(variable_ids):
    for variable_id in variable_ids:
        v = Variable.objects.get(pk=variable_id)
        points = []
        i = 0
        #          now     days                primary key offset, -> ms
        min_time = (time()-(1 * 24 * 60 * 60)) * 2097152 * 1000
        data = v.recordeddata_set.filter(pk__gt=min_time)
        i_max = data.count()
        if i_max == 0:
            continue
        print(f"{v} {i} {i_max} {i/i_max*100}")
        if not hasattr(v.datasource,"influxdatabase"):
            continue
        new_point = v.datasource.influxdatabase.create_data_element_from_variable
        for rc in data.iterator():
            points.append(new_point(v ,rc.timestamp, rc.value()))
            i += 1
            if i%5000==0:
                v.datasource.influxdatabase.write_points(points)
                print(f"{v} {i} {i_max} {i/i_max*100:1.2f}")
                points = []
        v.datasource.influxdatabase.write_points(points)
        print(f"{v} {i} {i_max} {i/i_max*100:1.2f}")
        points = []

variables = []
workers = 1
for worker_id in range(workers):
    variables.append([])
worker = 0

for em in Variable.objects.all():
    variables[worker % workers].append(em.pk)
    worker += 1

#with ProcessPoolExecutor(max_workers=workers, initializer=subprocess_setup) as executor:
#    for worker_id in range(workers):
#        executor.submit(process_variables, variables[worker_id])
process_variables(variables[0])