Gainsight/Scripts/API_Tests/bulk_invite_and_props-minimal.py

import pandas as pd
import requests
import time
"""
Note that all single-line hash comments are referencing the code _below_ the comment line.
"""

APIKEY = "INSERT API KEY BETWEEN QUOTES"
HEADERS = {
    "accept": "application/json",
    "X-Api-Key": APIKEY,
}
BASEURL = "https://api.northpass.com/v2/"
IMPORTFILE = "INSERT THE PATH TO THE CSV ON YOUR LOCAL MACHINE"


def bulk_invite_and_group():
    """
    Bulk endpoint which invites new people and adds them to a group via this structure:
    {
    "email": "me@mac.com"
    "groups": "GroupA"
    }

    This function looks for the group in the CSV as well.
    """
    # This first line reads the CSV using pandas and puts the dataframe into a variable
    data = pd.read_csv(IMPORTFILE)

    # Grab all unique values from the Group column. It should only be 3 values (the 3 groups you're adding members to)
    groups = data["Group"].unique()

    # Turn it into a list so we can loop through it.
    groups = list(groups)

    # Outputting status updates for your reference
    print("Here are all groups within the CSV:")
    print(groups)
    print(" ")

    # Now we loop through the groups
    for group in groups:
        payload = ""
        # You can comment this out if you want. This just confirms the loops is moving through all the groups.
        print(group)

        # Creating a temporary variable for one group at a time
        tmp_group = data[data.Group == group]

        # For that group, grab all the emails using the column called "Email"
        people = list(tmp_group["Email"])

        # Making sure the emails don't have commas or extra spaces.
        group = str(tmp_group["Group"].unique())[2:-2]

        # Show you how many people are in that group! We're making progress!
        print(f"Group --> {group} ...  Amount of People --> {len(people)}")

        # Now let's prepare the actual API call.
        url = f"{BASEURL}bulk/people"

        # The reason we are checking for length is because our bulk endpoints can't take more than 1500 parameters at a time.
        # So if the amount of people in this group (remember, we're still in the for loop!) is greater than 1500, we'll have to break it up
        if len(people) > 1500:

            # Take 1500 people at a time, and add them to a mini payload (called mini load) and then we'll insert that into the bigger payload.
            for chunk in range(0, len(people), 1500):
                i = chunk
                payload_1 = []
                i_to_add = people[i : i + 1500]
                for person in i_to_add:
                    miniload = {"email": person, "groups": group}
                    payload_1.append(miniload)

                # This print statement should show 1500 people.
                print(f"The long length {group} payload has {len(payload_1)}")

                # Here's where we add the mini-payload list to the formatted payload that the API needs
                payload = {"data": {"attributes": {"people": payload_1}}}

                # And here we go! Making the call to our endpoint
                response = requests.post(url, headers=HEADERS, json=payload)

                # Printing the status code for your awareness
                print(f"Completed. Status code is {response.status_code}")

        # What if the amount of all the people per group is less than 1500? Well, let's run this code block/else statement!
        else:
            payload_1 = []
            # Pretty straight forward, we don't need to do any chunking, so just add everyone to the mini-payload, as above.
            for person in people:
                miniload = {"email": person, "groups": group}
                payload_1.append(miniload)

            # Same print statement as above for continuity.
            print(f"The {group} payload has {len(payload_1)}")

            # Constructing the payload the API endpoint expects!
            payload = {"data": {"attributes": {"people": payload_1}}}

            # And here we go again! Pushing the data to your academy.
            response = requests.post(url, headers=HEADERS, json=payload)

            # Showing you the status code - you should expect 200.
            print(f"Completed. Status code is {response.status_code}")
            print(response.text)

        # Next, we need to add all the properties (the Agency Name) to each person.
        # The reason why we use time.sleep() is to just give the application a few minutes to fully add everyone.
        # It's not really needed, but better to be safe than sorry
        print("Running add props from func...")
        time.sleep(3)
        add_props_from_func(people, data, group)


def add_props_from_func(people, data, group):
    # Creating an empty list of emails that cause errors, to be filled if an error arises.
    errorlist = []

    # Move through all the people
    for learner_email in people:
        # Grab the Agency name from the original dataframe, looking for the column called "AgencyName"
        agency_name = data.loc[data["Email"] == learner_email, "AgencyName"]

        # Clean up white space and commas
        agname = str(agency_name.values)[2:-2]

        # Print out confirmation that the email, agency, and group all align.
        print(f"Learner: {learner_email} --> Agency: {agname} from Group: {group}")

        # We first need the learner's UUID since that isn't passed in the CSV and is required for the properties endpoint.
        ppl_search = f"{BASEURL}people?filter[email][eq]={learner_email}"
        ppl_response = requests.get(ppl_search, headers=HEADERS)

        # Let's give it a shot to see if the person exists (they should, we just added them!)
        # If they exist, grab the ID and go straight into adding their properties via a different endpoint.
        try:
            ppl_data = ppl_response.json()
            learner_uuid = ppl_data["data"][0]["id"]

            # Now update the props
            prop_url = f"{BASEURL}properties/people/bulk"
            payload = {
                "data": [
                    {
                        "attributes": {"properties": {"agency_name": agname}},
                        "id": learner_uuid,
                        "type": "person_properties",
                    }
                ]
            }

            # This is the actual call for adding the property to the person
            propresponse = requests.post(prop_url, json=payload, headers=HEADERS)

            # However, if we don't get a 200 status code, let's add the person to the error list for later investigation.
            if propresponse.status_code != 200:
                error_tupe = (learner_uuid, learner_email, agname)
                errorlist.append(error_tupe)

            # But, if the status code is 200, then we're good! And we output that it was successful.
            else:
                print(f"Looks like {learner_email} and {agname} was successful. Received status code: {propresponse.status_code}.")
        except (TypeError, IndexError) as e:
            error_tupe = (0, learner_email, agency_name)
            errorlist.append(error_tupe)
            print(f"{e} has occurred with {learner_email}")
        finally:
            pass

    # As one last print, show the error list. It should be empty!
    print(f"Error list: {errorlist}")

if __name__ == "__main__":
    bulk_invite_and_group()