import requests import json import csv import pandas as pd import time import Apikeys from termcolor import colored, cprint KNOWLEDGEGROUPS = [ '7395831e-4325-4b16-85bb-36c94f68aec0', '180571e8-f943-4980-8997-b3eed2a0c141', '2b69f2f8-d567-48c3-8bb3-22e0dc8819bd', '3f8dc68e-1458-4199-9641-6781960e085e', '8585fe89-a050-4dbb-beb8-6ebd7358a970', 'd2542667-0dbf-4680-a5af-042d70f24a55', '2b5267b2-ce87-4e77-ad88-5cfec80496b9', '483c3416-ddfb-43fe-983b-08abb6b50c62', '1582d056-55fb-403b-8a65-f3b641c96b69', 'be95bdcc-e72a-4132-8a67-9dde9bad5e2a', '0a3412da-5f73-4738-8364-15d5919750f3', '197da27d-0497-40b5-b2f8-cec4124d32f6', 'a031d9a8-e433-45cf-826a-8881644f8eac', '02702bf3-261c-41e0-a22d-26d3e90493a3', '3b149bfe-31c5-4991-bd6c-ba4c760089d4', 'b6ae5e37-db6a-4b79-949f-be73b216f677', 'bfb708e4-18eb-47b5-afde-737f16721e9a', 'f02032d3-3d60-4cb1-acac-855c229646c3', '96b24666-85f2-4f70-ae59-f5a924cc045f', 'f7701275-cebc-482b-ac31-9cfcd93937c3', 'fcfe4ee2-b247-4244-8cfc-f3d98d219fea', 'c6b6d415-323e-46c1-859e-be86fd36ec48', 'e53216bf-9815-42c7-89c1-953a7b1289a3', '5eeef2ff-1616-43bb-a0c1-aa84ad551824', '59ccfdeb-8a8a-4693-b4fa-27034192071c', '849f1551-604a-4b5c-9b5d-e2771eed488c', 'cf5d1920-9618-43f3-8dac-53954d19a956', '0a5c0100-9500-46a5-a7be-40d03fc5dfe9', '4d0bf08e-3dda-4a2e-8213-72a020873a03', 'e48c8995-6a64-45c1-ae62-ba96fcc01542', '0ef5fdd2-718c-47d2-88bc-2d0193b18530', '604dd8b8-175a-4a74-93d2-28760f1d1835', '26c5277c-440a-4dea-b625-beb986cff673', '8e33adf0-5932-4535-90c7-10fa04e97201', '1ef34494-4d48-4b69-9819-a22c5870fc24', 'b2b8d7aa-06e8-4ed5-bc9b-cb9ce0e81309', 'e4017ee0-6141-4145-816f-ed68ee6931bc', '84d32175-8cb8-4fb0-95cc-6ae13d40aaaa', '27489e34-b04c-410e-99a2-0d93e2e42fbf', 'e5e8565f-80e2-4462-b687-56f6d64f95e4', '27accc37-c3fd-465f-99cd-3e131081aeca', '32e112bd-5495-4399-85dd-1925e1ccbba5', 'dc50ca43-5071-45b3-bf42-e1e64416ffd0', '950a6345-5a13-4931-8d82-eac6adef03e3', '700640e7-0de3-49dc-b441-4efff8ad33ba', '5f35e542-a8cf-4422-8e87-466cdca62864', 'f50cb362-2f86-44eb-89e6-bea6ecbaf89f', '31a7cbe0-6aa6-403b-a561-6bc4fa81c0b1', '853de4bd-6f6a-4d1d-980a-b67eb1b0e876', 'cd0fa4e0-2d24-4b35-918a-33baa736015e', '933baf03-3664-4c33-bd97-208a9f7ab78b', '55bae3db-5f62-4be3-823a-bcb429b8a2b2', '4754b85b-e7a6-41a8-b0e9-5e02c58ebc38', '33f4fc73-102d-492e-9b0a-383d0b0f68b0', 'fa8914be-0986-460c-884d-9973a9622045', 'b9f734fa-de0d-4a0b-9ce2-c092126e1d8d', '448f3335-cf11-4e7a-9939-c734861d16e3', '106775db-a00d-4956-bf27-97ea269bb001', '594cd6c0-17db-4241-be56-ad28a8db4f7b', '95f7b67d-3ba8-4d18-bcbb-3e02f7bfaf7a', '0323339c-b92b-481c-9249-651ef0273ad7', '38a42a60-f6e6-4beb-95f1-51c5469dc4c6', 'd694804c-ae1a-4db0-b5fc-2497e43abb6f', 'a008a4e6-e026-4a1c-8aef-eea78c41b029', '4575114c-1e63-41b1-8953-67d3ce3ed3e6', ] PERSON_IDS = [ ] APIKEY = Apikeys.ANTHOLOGY BASEURL = "https://api.northpass.com/v2/" HEADERS = {"accept": "application/json", "X-Api-Key": APIKEY} GROUPS = [] BASEFILE = "/Users/normrasmussen/Downloads/Anthology_master_backup.csv" def grab_person_group_ids(): rowdict = {"knowledgestate.edu": KNOWLEDGEGROUPS} grab_ppl_ids(rowdict) def grab_ppl_ids(rowdict): cprint(f"The dictionary is grabbing all the groups. Here's the dict: {rowdict}", 'green') page_count = 0 person_list = [] while True: # for domain, group_list in rowdict.items(): # Grab all people page_count += 1 url = ( BASEURL + f"people/?filter[email][cont]=@knowledgestate.edu&limit=100&page={page_count}" ) response = requests.get(url, headers=HEADERS) resp = response.json() nextlink = resp["links"] for data in resp["data"]: if data["attributes"]["registration_status"] == "activated": person = data["id"] person_list.append(person) else: pass if "next" not in nextlink: break if len(person_list) > 0: cprint(f"Person list for knowledgestate.edu has {len(person_list)} people.", 'blue') bulk_remove_and_enroll(person_list, KNOWLEDGEGROUPS) else: cprint(f"Person list for knowledgestate.edu has {len(person_list)} people.", 'blue') cprint(f"Skipping the bulk function.", 'yellow') def add_group_to_people(person_list): pass def bulk_remove_and_enroll(person_list, group_list): cprint("Moving people and groups into bulk function.", 'green') COUNT = 0 FINISH_SIGNAL = len(person_list) # Get people with groups and remove them from those groups for person in person_list: print(person) COUNT += 1 url = BASEURL + f"people/{person}" response = requests.get(url, headers=HEADERS) print(response.status_code) data = response.json() groups = data["data"]["relationships"]["groups"] name = data["data"]["attributes"]["full_name"] print(name) del_group_list = [] for group in groups["data"]: del_payload_var = {"id": group["id"], "type": "membership-groups"} del_group_list.append(del_payload_var) del_payload_base = {"data": del_group_list} if not del_payload_base["data"]: print("nothing in del_payload_base") pass else: try: durl = BASEURL + f"people/{person}/relationships/groups" dresponse = requests.delete(durl, headers=HEADERS, json=del_payload_base) print(dresponse.status_code) good_status_codes = [202, 204, 200, 203] if dresponse.status_code in good_status_codes: pass else: cprint(f"Error: {response.status_code} with {name}", 'red') except Exception as e: print(e) finally: pass if COUNT == FINISH_SIGNAL: # Since we're de-enrolling one by one, let's sleep and wait. cprint("Sleeping for 2 seconds.", 'yellow') time.sleep(2) cprint("Sleep Complete. Hold on to your butts!", 'yellow') # Re-enroll everyone back into all the groups by creating subset groups # Trying to do everyone at once (143 ppl * 54 groups) resulted in payloads that are too big # Doing the subsets of 25 ppl each did not yield any errors. composite_list = [person_list[x:x+25] for x in range(0, len(person_list),25)] for people_subset in composite_list: payload = {"payload": {"person_ids": people_subset, "group_ids": group_list}} cprint(f"{payload}", 'green') url = BASEURL + "bulk/people/membership/" # The above is commented out because I kept getting a 413 error of too much content # Changing this to enroll each person.... one at a time. # But this is slow and didn't work. It actually just stopped working after around 30 people. # miniload = [] # for groupuuid in group_list: # tmpload = {"type":"membership-groups","id":groupuuid} # miniload.append(tmpload) # # print(len(person_list)) # for person in person_list: # url = BASEURL + f"people/{person}/relationships/groups" # payload = { "data": miniload } try: cprint(f"Trying for person: {person}", 'green') cprint(f"With payload: {payload}", 'blue') response = requests.post(url, headers=HEADERS, json=payload) response.raise_for_status() except requests.exceptions.HTTPError as err: cprint(f"Error: {response.status_code}. Exception: {err}", 'red') except requests.exceptions.Timeout: cprint("Timeout Error", 'red') except requests.exceptions.TooManyRedirects: cprint("Too Many Redirects Error", 'red') except requests.exceptions.ChunkedEncodingError as ex: cprint(f"Invalid chunk encoding {str(ex)}", 'yellow') finally: cprint(response.status_code, 'yellow') cprint(response.text, 'yellow') cprint("Okay, let's see how that went.", 'red') if __name__ == "__main__": grab_person_group_ids()