How to download an Argo float configuration from the Euro-Argo Fleet Monitoring API

get_float_config.py

import urllib.request
import json
import numpy as np
import pandas as pd

def get_float_config(wmo, cyc=None):
    
    def id_mission(missionCycles, a_cyc):
        this_mission = None
        for im, mission in enumerate(missionCycles):
            cycles = missionCycles[mission]
            if str(a_cyc) in cycles:
                this_mission = mission
        return this_mission

    # Download floats meta-data from EA API:
    URI = "https://fleetmonitoring.euro-argo.eu/floats/%s" % wmo
    with urllib.request.urlopen(URI) as url:
        data = json.load(url)
    
    # Get the list of cycles covered:
    all_cycles = []
    for mission in data['configurations']['missionCycles']:
        cycles = data['configurations']['missionCycles'][mission]
        cycles = np.sort([int(cyc) for cyc in cycles])
        [all_cycles.append(cyc) for cyc in cycles]
        cycles = [str(cyc) for cyc in cycles]
        # print("mission #%s: from #%s to #%s" % (mission, cycles[0], cycles[-1]))
        # print(cycles[0],"-",cycles[-1])
        # print(",".join(cycles) in data['configurations']['cycles'])
        data['configurations']['cycles'][",".join(cycles)]
    all_cycles = np.sort(all_cycles)
    
    # Create a dataframe with all mission config at each cycles:
    CONFIG = {'CONFIG_MissionID': []}
    for item in data['configurations']['cycles'][list(data['configurations']['cycles'].keys())[0]]:
        CONFIG[item['argoCode']] = []
    for a_cyc in all_cycles:
        for im, mission_cycles in enumerate(data['configurations']['cycles']):
            if a_cyc in [int(cyc) for cyc in mission_cycles.split(',')]:
                CONFIG['CONFIG_MissionID'].append(id_mission(data['configurations']['missionCycles'], a_cyc))
                this_mission = data['configurations']['cycles'][mission_cycles]
                for item in this_mission:
                    CONFIG[item['argoCode']].append(item['value'])                       
    df = pd.DataFrame(CONFIG, index=all_cycles)
    df.index.name = 'CYCLE_NUMBER'   
    
    if cyc is not None:
        df = df.loc[cyc]
    
    return df

get_float_config(6902919)
get_float_config(6902919, 12)