I have found that documentation to be less than helpful.

In my experience, the assets do not show in the response for a user or a user view, despite what that documentation says.

We are doing something similar to what you’re asking, but had to do it in two parts.

1. We created an asset view of devices that are assigned to a user (Filter: Asset Owner - Exclude “Not Assigned”) and called that via API to retrieve the users and their asset(s) to update in our SIS.
2. To handle the deltas, there are a couple of options:
   1. During the first part above, compare all users in your SIS to the output from that API call for the asset view, any user that’s not in the response doesn’t have a device - update your SIS accordingly.   OR
   2. Create a user view of users without an asset (Filter: User Attribute - Exclude “Has assigned device”) and call that view via API to get your output of users without a device to update your SIS accordingly.

​@RMoeller 967aff3 emsd63 Thank you for submitting your question to our community!

As ​@jclark is our resident API expert, I hope this is what you are looking for. Thanks J!!

​@jclark Sorry, I figured out a workaround late yesterday and hadn’t posted an update yet. What I ended up doing is similar to what you propose. I created an asset view of assigned devices, and then used the filter to pull in that view along with another view that gives me a list of users:

iiq_users_apiURL = f"https://{iiq_domain}/api/v1.0/users/view/{iiq_users_view_id}{iiq_post_params}"
iiq_assets_apiURL = f"https://{iiq_domain}/api/v1.0/assets{iiq_post_params}"

iiq_assets_payload = {
    "Filters": r
        {
            "Facet": "View",
            "Id": iiq_assets_view_id
        }
    ]
}

I then group the asset data by owner and put the asset data into a list of dicts, and merge the users and assets data into one pandas dataframe:

iiq_assets_grouped_df = iiq_assets_df.groupby('OwnerId').apply(lambda s: s s'AssetId', 'AssetTag', 'Name']].to_dict(orient='records'),include_groups=False).reset_index(name="Assets")


iiq_df = iiq_users_df.merge(iiq_assets_grouped_df, how="left", left_on="UserId", right_on="OwnerId").fillna("")

Then I compare that with the data in my SIS and update as needed. Thanks!