137 lines
3.7 KiB
Python
137 lines
3.7 KiB
Python
import Apikeys
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import requests
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import pprint
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import csv
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import pandas as pd
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pp = pprint.PrettyPrinter(indent=4)
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APIKEY = Apikeys.ANTHOLOGY
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HEADERS = {
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"accept": "application/json",
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"X-Api-Key": APIKEY,
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}
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BASEURL = "https://api.northpass.com/v2/"
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GROUPS = [
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"Academic Economics",
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"Academy Use/Navigation",
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"Accreditation",
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"Anthology 101",
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"Baseline",
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"Course Evaluations",
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"Engage",
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"Evaluate",
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"Finance & HCM",
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"Learn",
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"Portfolio",
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"Power BI",
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"Raise",
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"Reach",
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"Student",
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]
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def all_groups():
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"""
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Get all Group IDs
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"""
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gids = []
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group_count = 0
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while True:
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group_count += 1
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url = f"https://api.northpass.com/v2/groups?page={group_count}"
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gresponse = requests.get(url, headers=HEADERS)
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gdata = gresponse.json()
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gnext = gdata["links"]
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for response in gdata["data"]:
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group_id = response["id"]
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group_name = response["attributes"]["name"]
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group_tupe = (group_id, group_name)
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print(group_tupe)
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gids.append(group_tupe)
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if "next" not in gnext:
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break
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get_courses(gids)
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def group_ids():
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"""
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Get the group Ids from a list of named groups.
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"""
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url = "groups"
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ids = []
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for group in GROUPS:
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filter = f"?filter[name][cont]={group} - ("
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urlreq = f"{BASEURL}{url}{filter}"
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response = requests.get(urlreq, headers=HEADERS)
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response = response.json()
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for data in response["data"]:
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group = data["attributes"]["name"]
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id1 = data["id"]
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group_tupe = (id1, group)
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ids.append(group_tupe)
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get_courses(ids)
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#portfolio t1 - dc50ca43-5071-45b3-bf42-e1e64416ffd0
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#academy use/nav t1 - 3875a210-f86d-4b4a-a86a-980022374936
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def get_courses(ids):
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df = pd.DataFrame()
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courses = []
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error_groups = []
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for tupe in ids:
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id = tupe[0]
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group = tupe[1]
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for count in range(1, 10):
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print(f"Get Courses For Loop. Group:{ group } and count: {count}")
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url2 = f"groups/{id}/courses?limit=100&page={count}"
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courseurl = f"{BASEURL}{url2}"
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coursereq = requests.get(courseurl, headers=HEADERS)
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try:
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coursedata = coursereq.json()
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nextlink = coursedata["links"]
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for cdata in coursedata["included"]:
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# if cdata["attributes"]["status"] == "archived":
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coursedict = parse_data(cdata, group)
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print(f"Coursedict --> {coursedict} for page {count}")
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if coursedict is not None:
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courses.append(coursedict)
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except JSONDecodeError as e:
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print("JSON Error! {e}")
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error_groups.append(group)
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finally:
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if "next" not in nextlink:
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break
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pddata = df.from_records(courses)
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pddata.to_csv("/Users/normrasmussen/Downloads/ALL-Anthology_Course_IDs_Names.csv")
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print(error_groups)
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def parse_data(cdata, group):
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name = cdata["attributes"]["name"]
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courseid = cdata["attributes"]["share_course_link"].split("/")[5]
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enrollments = cdata["attributes"]["enrollments_count"]
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created = cdata["attributes"]["created_at"]
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updated = cdata["attributes"]["updated_at"]
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status = cdata["attributes"]["status"]
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coursedict = {
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"group": group,
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"name": name,
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"id": courseid,
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"enrollments": enrollments,
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"created at": created,
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"updated at": updated,
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"status": status,
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}
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if coursedict is not None:
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return coursedict
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if __name__ == "__main__":
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# group_ids()
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all_groups()
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