Create a multiseries project¶

import datetime
import json
import time

from pandas.io.json import json_normalize
import requests
import yaml

FILE_CREDENTIALS = "path-to-drconfig.yaml"

parsed_file = yaml.load(open(FILE_CREDENTIALS), Loader=yaml.FullLoader)

DR_ENDPOINT = parsed_file["endpoint"]
API_TOKEN = parsed_file["token"]
AUTH_HEADERS = {"Authorization": "token %s" % API_TOKEN}

def wait_for_async_resolution(status_url):
    status = False

    while status == False:
        resp = requests.get(status_url, headers=AUTH_HEADERS)
        r = json.loads(resp.content)

        try:
            statusjob = r["status"].upper()
        except:
            statusjob = ""

        if resp.status_code == 200 and statusjob != "RUNNING" and statusjob != "INITIALIZED":
            status = True
            print("Finished: " + str(datetime.datetime.now()))
            return resp

        print("Waiting: " + str(datetime.datetime.now()))
        time.sleep(10)  # Delays for 10 seconds.


def wait_for_result(response):
    assert response.status_code in (200, 201, 202), response.content

    if response.status_code == 200:
        data = response.json()

    elif response.status_code == 201:
        status_url = response.headers["Location"]
        resp = requests.get(status_url, headers=AUTH_HEADERS)
        assert resp.status_code == 200, resp.content
        data = resp.json()

    elif response.status_code == 202:
        status_url = response.headers["Location"]
        resp = wait_for_async_resolution(status_url)
        data = resp.json()

    return data

FILE_DATASET = "/Volumes/GoogleDrive/My Drive/Datasets/Store Sales/STORE_SALES-TRAIN-2022-04-25.csv"