max_records = 2000 # <markdowncell> # ### Is data available for the basic oceanography variables in the CSW endpoints for multiple locations? # # #### Check the CSW endpoints for each variable and location # <markdowncell> # <div class="warning"><strong>This next cell takes a long time to process!</strong> <br>Go grab a coffee</div> # <codecell> # Add a waitbar to monitor status divid = insert_progress_bar(title='Searching catalogs. Please wait...', color='red') # Save all of the results in a list of Dataframes results = {} all_data = [] count = 0 # Loop through the csw endpoints for endpoint in endpoints: print '\n' + endpoint csw = CatalogueServiceWeb(endpoint, timeout=60) # loop through the variables for var_name in names_dict: # print '\n' + var_name.upper() num_recs = []
# <div class="error"><strong>Processing long time series</strong> - # The CO-OPS Server responds really slow (> 30 secs, for what should be # a 5 sec request) to multiple requests, so getting long time series # data is almost impossible.</div> # <markdowncell> # <div class="info"> # <strong>Use NDBC DAP endpoints to get time-series data</strong> - # The DAP server for met data is available for NDBC, we use that # to get long time series data.</div> # <codecell> divid = insert_progress_bar(title='Please wait...', color='red') # Used to define the number of days allowable by the service. coops_point_max_days = ndbc_point_max_days = 30 print("start & end dates: %s, %s\n" % (jd_start, jd_stop)) num_stations = len(st_list.keys()) count = 0 for station in st_list.keys(): count += 1 # Set it so we can use it later. st = station.split(":")[-1] print('[%s]: %s' % (st_list[station]['source'], st)) if st_list[station]['source'] == 'coops': # Coops fails for large requests. master_df = pd.DataFrame() elif st_list[station]['source'] == 'ndbc':