import jenkins
import boto3
import time
import os
import json

from datetime import datetime
from datetime import timedelta
from boto3.dynamodb.conditions import Key

# this script also needs in env variables
# AWS_ACCESS_KEY_ID=
# AWS_SECRET_ACCESS_KEY=
# AWS_SESSION_TOKEN=
# #AWS_SECURITY_TOKEN=  - the same value as AWS_SESSION_TOKEN


# table name in dynamo to check status
DYNAMODB_TABLE_NAME = 'prod_feed_ingestion_status'


FEED_NAME = 'spotify_backfill_sme_streams'

# connect to jenkins.
# JENKINGS_PASS - jenkins token can be generated in UI
# https://scheduler.theorchard.io/user/<user_name>/configure
server = jenkins.Jenkins(
    'https://scheduler.theorchard.io',
    username='',  # put jenkins username
    password=os.environ.get('JENKINGS_PASS')
)


start_date = '2018-09-01'  # the most earliest date to backfill
end_date = '2018-11-30'  # the most recent date to backfill

start_date_obj = datetime.strptime(start_date, '%Y-%m-%d')
end_date_obj = datetime.strptime(end_date, '%Y-%m-%d')
skip = (datetime.now() - end_date_obj).days
print(skip)  # can use skip value for jenkins exec job

dynamodb = boto3.resource('dynamodb', region_name='us-east-1')
dynamodb_table = dynamodb.Table(DYNAMODB_TABLE_NAME)

client = boto3.client('swf', region_name='us-east-1')


def count_executions():
    """Return number of active executions."""
    return len(client.list_open_workflow_executions(
        domain='prod_swf_feed_ingestion',
        startTimeFilter={
            # todo set appropriate dates to monitor swf
            'oldestDate': datetime(2020, 4, 23),
            'latestDate': datetime(2020, 5, 30)
        },
        typeFilter={
            'name': 'spotify_backfill_feed_ingestion',
            'version': '3.0'
        },
    )['executionInfos'])


while start_date != end_date:

    response = dynamodb_table.query(
        KeyConditionExpression=Key('feed_name').eq(FEED_NAME) &
                               Key('date').eq(end_date))
    if response['Items'] and response['Items'][0]['status'] == 'INGESTED':
        print(end_date, response['Items'][0]['status'])

    else:
        while count_executions() >= 3:  # todo set the max allowed concurrent executions
            print('sleeping')
            time.sleep(50)

        print('Launching for', end_date)

        # in case you using flow exec job , not prod-swf-ingestion-exec
        # use skip parameter
        server.build_job(
            'prod-swf-ingestion-exec',
            {"CONTEXT": json.dumps(
                   {
                       "context_date": end_date}),
                "WORKFLOW": "spotify_backfill"})

        time.sleep(60 * 7)  # todo set sleep time between launches
        if count_executions() >= 3:
            time.sleep(60 * 20)

    end_date_obj = end_date_obj - timedelta(days=1)
    skip += 1
    end_date = end_date_obj.strftime('%Y-%m-%d')