function to return nearest met sites to snow Ex sites

[beautah]

as a developer I need to know what n # of met sites are closest to any given snow ex sites.

The function should take a lat/long of a snow ex site, a input geojson (mostly snotels, but any sites) and a n # of sites and return a geojson representation of the n # of snotels that are closest to that snow ex site. The calculation does not need to be exact but should be accurate enough to be trusted and with low computational overhead.

A snippet which may help taken from another project takes a input gdf and returns other sites within that gdf that are closest to a given site. Just need to modify it to use a lat and long as input rather than a reference to another site

def nearest_sites(df_meta, resp_site=None, pred_sites=None, num_sites=10):
    try:
        num_sites = int(num_sites)
    except ValueError:
        num_sites = 10
    tx = df_meta[df_meta["triplet"] == resp_site]["latitude"]
    ty = df_meta[df_meta["triplet"] == resp_site]["longitude"]

    def calc_dist(row, tx=tx, ty=ty):
        return (row["latitude"] - tx) ** 2 + (row["longitude"] - ty) ** 2

    df_meta["proximity"] = df_meta.apply(calc_dist, axis=1)
    df_meta.sort_values(by="proximity", inplace=True)
    df_nearest = df_meta.head(num_sites + 1).copy()
    triplets_in_use = tuple(set([i for i in (resp_site,) + pred_sites if i]))
    df_in_use = df_meta[df_meta["triplet"].isin(triplets_in_use)]
    df = pd.concat([df_nearest, df_in_use]).drop_duplicates(ignore_index=True)
    return df