add app.py and requirements

app.py

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+import requests
+import pandas as pd
+import datetime
+import time
+import gradio as gr
+import os
+
+###########
+# other API's of interest: https://medium.com/@imdipto/best-free-alternatives-to-the-wunderground-weather-api-21acb22450e6
+##########
+OPENWEATHER_API_KEY = os.environ.get('OPENWEATHER_API_KEY')
+WEATHERAPI_KEY = os.environ.get('WEATHERAPI_KEY')
+
+
+def openweather_to_result(lat, lon, gmt_time):
+    """    
+    API docs: https://openweathermap.org/api/one-call-api#current
+    
+    Parameters
+    ------------
+    lat [float]: decimal valued latitude
+    lon [float]: decimal valued longitude
+    gmt_time [datetime object]: time of desired forecast, in gmt and as python datetime object
+    
+    Returns
+    --------
+    cloud_pct Tuple(List, List): list of cloud percent and corresponding time for times within 1.5 hours of input GMT time
+    """
+    exclude_parts = 'current,minutely,daily,alerts'
+    request_url = f'https://api.openweathermap.org/data/2.5/onecall?lat={lat}&lon={lon}&exclude={exclude_parts}&appid={OPENWEATHER_API_KEY}'
+
+    response = requests.get(request_url)
+
+    data = response.json()
+
+    cloud_pct = []
+    forecast_times = []
+
+    # timeframe around input time to check cloud % for
+    timeframe = datetime.timedelta(hours=1, minutes=30)
+    for hour in data['hourly']:
+        # dt property is unix utc time of forecasted data - convert this to python datetime object
+        forecast_time = datetime.datetime.fromtimestamp(
+            hour['dt'], tz=datetime.timezone.utc)
+        if abs(forecast_time - gmt_time) <= timeframe:
+            # cloud pct is stored in each hour at top level
+            cloud_pct.append(hour['clouds'])
+            forecast_times.append(forecast_time)
+
+    return cloud_pct, forecast_times
+
+
+def weatherapi_to_result(lat, lon, gmt_time):
+    """    
+    API docs: https://www.weatherapi.com/docs/
+    TODO: implement wrapper instead https://github.com/weatherapicom/weatherapi-Python
+    
+    Parameters
+    ------------
+    lat [float]: decimal valued latitude
+    lon [float]: decimal values longitude
+    gmt_time [datetime object]: time of desired forecast, in gmt and as python datetime object
+    
+    Returns
+    --------
+    cloud_pct Tuple(List, List): list of cloud percent and corresponding time for times within 1.5 hours of input GMT time
+    """
+    request_url = f'http://api.weatherapi.com/v1/forecast.json?key={WEATHERAPI_KEY}&q={lat},{lon}&days=2&alerts=no'
+    response = requests.get(request_url)
+
+    data = response.json()
+
+    timezone = data['location']['tz_id']
+
+    cloud_pct = []
+    forecast_times = []
+
+    # quick error handling to make sure input time python object has "timezone" property attached
+    try:
+        gmt_time = gmt_time.astimezone(datetime.timezone.utc)
+    except:
+        gmt_time = gmt_time.tz_localize('utc')
+
+    # timeframe around input time to check cloud % for
+    timeframe = datetime.timedelta(hours=1, minutes=30)
+
+    # this api is first divided into days, then hours
+    for day in data['forecast']['forecastday']:
+        for hour in day['hour']:
+            # time_epoch contains unix epoch time in GMT/UTC
+            #forecast_time = datetime.datetime.fromtimestamp(hour['time_epoch'], ZoneInfo(timezone))
+            forecast_time = datetime.datetime.fromtimestamp(
+                hour['time_epoch'], datetime.timezone.utc)
+            if abs(forecast_time - gmt_time) <= timeframe:
+                cloud_pct.append(hour['cloud'])
+                forecast_times.append(
+                    forecast_time.astimezone(datetime.timezone.utc))
+
+    return cloud_pct, forecast_times
+
+
+def met_to_result(lat, lon, gmt_time):
+    """    
+    API doc: https://api.met.no/weatherapi/locationforecast/2.0/documentation
+    How to: https://api.met.no/doc/locationforecast/HowTO
+    
+    Parameters
+    ------------
+    lat [float]: decimal valued latitude
+    lon [float]: decimal values longitude
+    gmt_time [datetime object]: time of desired forecast, in gmt and as python datetime object
+    
+    Returns
+    --------
+    cloud_pct Tuple(List, List): list of cloud percent and corresponding time for times within 1.5 hours of input GMT time
+    """
+
+    # set user agent https://stackoverflow.com/questions/10606133/sending-user-agent-using-requests-library-in-python
+    # must be unique per API Terms of Service https://api.met.no/doc/TermsOfService
+    headers = {
+        'User-Agent': 'NASAEarthScienceRemoteSensingUnit [email protected]'}
+
+    request_url = f'https://api.met.no/weatherapi/locationforecast/2.0/compact?lat={lat}&lon={lon}'
+
+    response = requests.get(request_url, headers=headers)
+
+    data = response.json()
+
+    cloud_pct = []
+    forecast_times = []
+
+    # timeframe around input time to check cloud % for
+    timeframe = datetime.timedelta(hours=1, minutes=30)
+
+    # walk through json return
+    for hour in data['properties']['timeseries']:
+        # time is utc formatted time https://api.met.no/doc/locationforecast/FAQ
+        forecast_time = datetime.datetime.strptime(
+            hour['time'], '%Y-%m-%dT%H:%M:%SZ').replace(tzinfo=datetime.timezone.utc)
+        # check if time of forecast is withing "timeframe" of desired time
+        if abs(forecast_time - gmt_time) <= timeframe:
+            # grab cloud pct from location within the nested json, add to list
+            cloud_pct.append(hour['data']['instant']
+                             ['details']['cloud_area_fraction'])
+            # add time of forecast to list. Should be an "on the hour" time
+            forecast_times.append(forecast_time)
+
+    return cloud_pct, forecast_times
+
+################
+# generate text
+################
+
+
+def file_to_cloud_listing(input_file, services):
+    """
+
+    Args:
+        input_file (Union[str, gradio FileType]): input csv file with LAT, LON, SITE, GMT cols
+        services (List): list of weather api servies to check 
+
+    Returns:
+        str: formatted string with weather predictions for locations
+    """
+    # this works if the input is from gradio. Then the file has an name property
+    try:
+        sites = pd.read_csv(input_file.name, parse_dates=['GMT'])
+        using_gradio = True
+    except:
+        # this is for input from a script or command line
+        sites = pd.read_csv(input_file, parse_dates=['GMT'])
+        using_gradio = False
+    start = time.perf_counter()
+    date_format = "%H:%M"
+    text = ''
+    # each row is a site. Get weather data and then print it for each service for each site.
+    for row_idx, row in sites.iterrows():
+        #time_of_interest = datetime.datetime.strptime(row.GMT, '%m/%d/%y %H:%M')
+        text += check_row(row, services, date_format)
+        text += f'{"="*60}\n'
+
+    return text
+
+
+def check_row(row, services, date_format="%H:%M"):
+    """Check a row of data (a pd.Series with LAT, LON, GMT, SITE cols)
+
+    Args:
+        row (pd.Series): pd.Series with LAT, LON, GMT, SITE cols)
+        services (List): List of weather services (['OpenWeather', 'MET (Norwegian)', 'WeatherAPI'] or subset)
+        date_format (str, optional): Format for printing time of site pass over. Defaults to "%H:%M".
+
+    Returns:
+        str: formatted str of text for weather vals
+    """
+    text = ""
+
+    text += f'{"Location":13}:\t\t{row.SITE} @ {row["GMT"].strftime(date_format)} GMT\n'
+
+    if not isinstance(row.GMT, datetime.datetime):
+        GMT = row["GMT"].to_pydatetime()
+    else:
+        GMT = row["GMT"]
+    GMT = GMT.replace(tzinfo=datetime.timezone.utc)
+    if 'OpenWeather' in services:
+        try:
+            cldp, times = openweather_to_result(row.LAT, row.LON, GMT)
+            text += format_cldp_and_time("OpenWeather", cldp=cldp, times=times)
+        except Exception as e:
+            text += f'OpenWeather:\t\tError {e} in API processing\n'
+    if 'MET (Norwegian)' in services:
+        try:
+            cldp, times = met_to_result(row.LAT, row.LON, GMT)
+            text += format_cldp_and_time("Norwegian", cldp=cldp)
+        except Exception as e:
+            text += f'Norwegian:\t\tError {e} in API processing\n'
+    if 'WeatherAPI' in services:
+        try:
+            cldp, times = weatherapi_to_result(row.LAT, row.LON, GMT)
+            text += format_cldp_and_time("WeatherAPI", cldp=cldp)
+        except Exception as e:
+            text += f'WeatherAPI:\t\tError {e} in API processing\n'
+
+    return text
+
+
+def format_cldp_and_time(api_name, cldp, times=None):
+    """Formats output text for lists of cloud percents and forecast times
+
+    Args:
+        api_name ([type]): Name of weather source. 
+        cldp (List): List of floating point cloud percentage values.
+        times (List, optional): List of forecast times, as datetime objects. Defaults to None.
+
+    Returns:
+        str: formatted text for printing
+    """
+    text = ''
+    date_format = "%H:%M"
+    if times is not None:
+        text += f'{"Forecast Time:":13}\t\t' + '  '.join(time.strftime(date_format)
+                                                         for time in times) + "\n"
+
+    text += f'{api_name:13}:\t\t{" ".join(f"{p:<6.0f}" for p in cldp)}\n'
+    return text
+
+
+if __name__ == '__main__':
+    inputs = [gr.inputs.File(label='Site File with Lat/Lon and GMT Time'), gr.inputs.CheckboxGroup(label='Weather Services',
+                                                                                                       choices=['OpenWeather', 'MET (Norwegian)', 'WeatherAPI'], default=['OpenWeather', 'MET (Norwegian)'])]
+    outputs = gr.outputs.Textbox(
+        label='Cloud % for hour before, hour of, hour after')
+        css = """* {
+                font-family: "Lucida Console", "Courier New", monospace !important;/* <-- fonts */
+            }"""
+        gr.Interface(fn=file_to_cloud_listing, inputs=inputs, css=css, outputs=outputs,
+                     allow_screenshot=False).launch(auth=("es", 'rs'), share=True)
+

requirements.txt

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+pandas
+gradio
+requests