import Apikeys
import requests
import pprint
import csv
import pandas as pd

pp = pprint.PrettyPrinter(indent=4)
APIKEY = Apikeys.ANTHOLOGY
HEADERS = {
    "accept": "application/json",
    "X-Api-Key": APIKEY,
}
BASEURL = "https://api.northpass.com/v2/"
GROUPS = [
    "Academic Economics",
    "Academy Use/Navigation",
    "Accreditation",
    "Anthology 101",
    "Baseline",
    "Course Evaluations",
    "Engage",
    "Evaluate",
    "Finance & HCM",
    "Learn",
    "Portfolio",
    "Power BI",
    "Raise",
    "Reach",
    "Student",
]

def all_groups():
    """
    Get all Group IDs
    """
    gids = []
    group_count = 0
    while True:
        group_count += 1
        url = f"https://api.northpass.com/v2/groups?page={group_count}"
        gresponse = requests.get(url, headers=HEADERS)
        gdata = gresponse.json()
        gnext = gdata["links"]

        for response in gdata["data"]:
            group_id = response["id"]
            group_name = response["attributes"]["name"]
            group_tupe = (group_id, group_name)
            print(group_tupe)
            gids.append(group_tupe)

        if "next" not in gnext:
            break

    get_courses(gids)

def group_ids():
    """
    Get the group Ids from a list of named groups.
    """
    url = "groups"
    ids = []
    for group in GROUPS:
        filter = f"?filter[name][cont]={group} - ("
        urlreq = f"{BASEURL}{url}{filter}"
        response = requests.get(urlreq, headers=HEADERS)
        response = response.json()

        for data in response["data"]:
            group = data["attributes"]["name"]
            id1 = data["id"]
            group_tupe = (id1, group)
            ids.append(group_tupe)

    get_courses(ids)

    #portfolio t1 - dc50ca43-5071-45b3-bf42-e1e64416ffd0
    #academy use/nav t1 - 3875a210-f86d-4b4a-a86a-980022374936

def get_courses(ids):
    df = pd.DataFrame()
    courses = []
    for tupe in ids:
        id = tupe[0]
        group = tupe[1]
        print(f"Get Courses Function. Group:{ group } and id: {id}")
        for count in range(1, 10):
            url2 = f"groups/{id}/courses?limit=100&page={count}"
            courseurl = f"{BASEURL}{url2}"
            coursereq = requests.get(courseurl, headers=HEADERS)
            coursedata = coursereq.json()
            print(coursedata)
            nextlink = coursedata["links"]
            for cdata in coursedata["included"]:
                # if cdata["attributes"]["status"] == "archived":
                coursedict = parse_data(cdata, group)
                print(f"Coursedict --> {coursedict} for page {count}")
                if coursedict is not None:
                    courses.append(coursedict)
            if "next" not in nextlink:
                break

    pddata = df.from_records(courses)
    pddata.to_csv("~/Downloads/ARCHIVED-Anthology_Course_IDs_Names.csv")


def parse_data(cdata, group):
    name = cdata["attributes"]["name"]
    courseid = cdata["attributes"]["share_course_link"].split("/")[5]
    enrollments = cdata["attributes"]["enrollments_count"]
    created = cdata["attributes"]["created_at"]
    updated = cdata["attributes"]["updated_at"]
    status = cdata["attributes"]["status"]
    coursedict = {
        "group": group,
        "name": name,
        "id": courseid,
        "enrollments": enrollments,
        "created at": created,
        "updated at": updated,
        "status": status,
    }
    if coursedict is not None:
        return coursedict


if __name__ == "__main__":
    # group_ids()
    all_groups()