Dash Ag Grid : multiple row model types possible (infinity + client side)?

Dash Python
1

Hi all, I have an app that updates the columns and data in an ag grid using callbacks that correspond to a user selected process with a dropdown. All processes use the default client side rowModelType; however, one process uses infinite.

So naturally, I added the rowModelType property as an output to this processes’ callback however, this does not work for me and I’m not sure why (example below).

Is there any other way I can update rowModelType or am I suck just using one type as defined when I first declare/initialize ag grid?

*Running dash 2.14.2 and dash-ag-grid 2.4.0

@callback(
Output(“infinite-row-sort-filter-select”, “getRowsResponse”),
Output(“infinite-row-sort-filter-select”, “rowModelType”),
Input(“infinite-row-sort-filter-select”, “getRowsRequest”),
)
def infinite_scroll(request):
dff = df.copy()

if request:
    if request["filterModel"]:
        filters = request["filterModel"]
        for f in filters:
            try:
                if "operator" in filters[f]:
                    if filters[f]["operator"] == "AND":
                        dff = filter_df(dff, filters[f]["condition1"], f)
                        dff = filter_df(dff, filters[f]["condition2"], f)
                    else:
                        dff1 = filter_df(dff, filters[f]["condition1"], f)
                        dff2 = filter_df(dff, filters[f]["condition2"], f)
                        dff = pd.concat([dff1, dff2])
                else:
                    dff = filter_df(dff, filters[f], f)
            except:
                pass

    if request["sortModel"]:
        sorting = []
        asc = []
        for sort in request["sortModel"]:
            sorting.append(sort["colId"])
            if sort["sort"] == "asc":
                asc.append(True)
            else:
                asc.append(False)
        dff = dff.sort_values(by=sorting, ascending=asc)

    lines = len(dff.index)
    if lines == 0:
        lines = 1

    partial = dff.iloc[request["startRow"]: request["endRow"]]
    return {"rowData": partial.to_dict("records"), "rowCount": lines}, "infinite"