2 files changed, 404 insertions, 0 deletions

diff --git a/library.py b/library.py
new file mode 100644
index 0000000..ff5735e
--- /dev/null
+++ b/library.py
@@ -0,0 +1,351 @@
+#!/usr/bin/env python3
+import datetime, requests, json, pytz
+from geopy.geocoders import Nominatim, GeoNames
+
+def get_lat_long(location):
+    # Converts a location into latitude and longitude
+    geolocator = Nominatim(user_agent="pywttr")
+    location = geolocator.geocode(location)
+    return location.latitude, location.longitude
+
+def get_time_zone(latitude, longitude):
+    #TODO
+    pass
+
+
+def get_grid_data(latitude, longitude):
+    # Returns id,x,y for a given latitude and longitude
+    grid_data = json.loads(requests.get(f"https://api.weather.gov/points/{latitude},{longitude}").text)
+    grid_id = grid_data["properties"]["gridId"]
+    grid_x = grid_data["properties"]["gridX"]
+    grid_y = grid_data["properties"]["gridY"]
+    return {"grid_id": grid_id, "grid_x": grid_x, "grid_y":grid_y}
+
+
+def get_raw_data(grid_id, grid_x, grid_y):
+    raw_data = json.loads(requests.get(f"https://api.weather.gov/gridpoints/{grid_id}/{grid_x},{grid_y}").text)
+    return raw_data
+
+
+def get_raw_forecast(grid_id, grid_x, grid_y):
+    raw_data = json.loads(requests.get(f"https://api.weather.gov/gridpoints/{grid_id}/{grid_x},{grid_y}/forecast", user_agent="my-test-app").text)
+    return raw_data
+
+
+def get_current_rounded_time():
+    tz = pytz.timezone("America/New_York") #temp
+    cur_time = datetime.datetime.now(tz=tz)
+    cur_time_rounded = cur_time.replace(second=0, microsecond=0, minute=0, hour=cur_time.hour) + datetime.timedelta(hours=cur_time.minute//30)
+    return cur_time_rounded
+
+
+def set_timezone(values):
+    # Takes a list of weather data values
+    # and converts all times to proper timezone
+    
+    ret = []
+    tz = pytz.timezone("America/New_York") #temp
+    for val in values:
+        val["time"] = val["time"].astimezone(tz)
+        ret.append(val)
+    return ret
+
+
+def make_current(values):
+    # Takes a list of weather data values 
+    # and removes items from before the current time
+    # (to the nearest hour)
+    ret = []
+    cur_time_rounded = get_current_rounded_time()
+    for val in values:
+        if val["time"] >= cur_time_rounded:
+            ret.append(val)
+    return ret
+
+
+def fill_gaps(values):
+    # Takes a list of weather data values 
+    # and fills gaps left by duration periods of longer
+    # than 1 hour
+    ret = []
+    for val in values:
+        ret.append(val)
+        duration_hours = int((val["duration"].seconds / 3600) + (val["duration"].days * 24))
+        if duration_hours > 1:
+            for _ in range(0, duration_hours - 1):
+                copy = val.copy()
+                copy["time"] = val["time"] + datetime.timedelta(hours=1)
+                copy["duration"] = datetime.timedelta(hours=1)
+                ret.append(copy)
+    return ret
+
+
+def normalize(values):
+    values = set_timezone(values)
+    values = make_current(values)
+    values = fill_gaps(values)
+    return values
+
+
+def celcius_to_fahrenheit(celcius):
+    fahrenheit = int(celcius * 9/5 + 32)
+    return fahrenheit
+
+    
+def parse_duration(duration_str):
+    #Parses time duration string and returns timedelta
+
+    duration_str = duration_str[1:] # strip off leading P
+    period_str, time_str = duration_str.split('T')
+    if len(period_str) > 0:
+        days = int(period_str[0])
+    else:
+        days = 0
+    hours = int(time_str[0:len(time_str)-1])
+    delta = datetime.timedelta(hours=hours, days=days)
+    return delta
+
+
+def get_daily_highs(raw_data):
+    daily_highs_raw = raw_data["properties"]["maxTemperature"]["values"]
+
+    daily_highs = []
+
+    for high in daily_highs_raw:
+        high_celc = high["value"]
+        high_fahr = celcius_to_fahrenheit(high_celc)
+
+        time_str, duration_str = high["validTime"].split('/')
+        time = datetime.datetime.strptime(time_str, "%Y-%m-%dT%H:%M:%S%z")
+        duration = parse_duration(duration_str)
+        daily_highs.append({"time":time,"duration":duration,"high_celc":high_celc,"high_fahr":high_fahr})
+
+    return daily_highs
+
+
+def get_daily_lows(raw_data):
+    daily_lows_raw = raw_data["properties"]["minTemperature"]["values"]
+
+    daily_lows = []
+
+    for low in daily_lows_raw:
+        low_celc = low["value"]
+        low_fahr = celcius_to_fahrenheit(low_celc)
+        time_str, duration_str = low["validTime"].split('/')
+        time = datetime.datetime.strptime(time_str, "%Y-%m-%dT%H:%M:%S%z")
+        duration = parse_duration(duration_str)
+        daily_lows.append({"time":time,"duration":duration,"low_celc":low_celc,"low_fahr":low_far})
+
+    return daily_lows
+
+
+def get_temperature(raw_data):
+    raw_values = raw_data["properties"]["temperature"]["values"]
+    ret = []
+
+    for val in raw_values:
+        val_celc = val["value"]
+        val_fahr = celcius_to_fahrenheit(val_celc)
+        time_str, duration_str = val["validTime"].split('/')
+        time = datetime.datetime.strptime(time_str, "%Y-%m-%dT%H:%M:%S%z")
+        duration = parse_duration(duration_str)
+        ret.append({"time":time,"duration":duration,"value_celc":val_celc,"value_fahr":val_fahr})
+
+    return normalize(ret)
+
+
+def get_apparent_temperature(raw_data):
+    raw_values = raw_data["properties"]["apparentTemperature"]["values"]
+    ret = []
+    
+
+    for val in raw_values:
+        val_celc = val["value"]
+        val_fahr = celcius_to_fahrenheit(val_celc)
+        time_str, duration_str = val["validTime"].split('/')
+        time = datetime.datetime.strptime(time_str, "%Y-%m-%dT%H:%M:%S%z")
+        duration = parse_duration(duration_str)
+        ret.append({"time":time,"duration":duration,"value_celc":val_celc,"value_fahr":val_far})
+
+    return normalize(ret)
+
+
+def get_humidity(raw_data):
+    raw_values = raw_data["properties"]["relativeHumidity"]["values"]
+    ret = []
+
+    for val in raw_values:
+        time_str, duration_str = val["validTime"].split('/')
+        time = datetime.datetime.strptime(time_str, "%Y-%m-%dT%H:%M:%S%z")
+        duration = parse_duration(duration_str)
+        ret.append({"time":time,"duration":duration,"value":val["value"]})
+
+    return normalize(ret)
+
+
+def get_wind_chill(raw_data):
+    raw_values = raw_data["properties"]["windChill"]["values"]
+    ret = []
+
+    for val in raw_values:
+        val_celc = val["value"]
+        val_fahr = celcius_to_fahrenheit(val_celc)
+        time_str, duration_str = val["validTime"].split('/')
+        time = datetime.datetime.strptime(time_str, "%Y-%m-%dT%H:%M:%S%z")
+        duration = parse_duration(duration_str)
+        ret.append({"time":time,"duration":duration,"value_celc":val_celc,"value_fahr":val_fahr})
+
+    return normalize(ret)
+
+
+def get_wind_speed(raw_data):
+    raw_values = raw_data["properties"]["windSpeed"]["values"]
+    ret = []
+
+    for val in raw_values:
+        time_str, duration_str = val["validTime"].split('/')
+        time = datetime.datetime.strptime(time_str, "%Y-%m-%dT%H:%M:%S%z")
+        duration = parse_duration(duration_str)
+        ret.append({"time":time,"duration":duration,"value":val["value"]})
+
+    return normalize(ret)
+
+
+def get_wind_gust(raw_data):
+    raw_values = raw_data["properties"]["windGust"]["values"]
+    ret = []
+
+    for val in raw_values:
+        time_str, duration_str = val["validTime"].split('/')
+        time = datetime.datetime.strptime(time_str, "%Y-%m-%dT%H:%M:%S%z")
+        duration = parse_duration(duration_str)
+        ret.append({"time":time,"duration":duration,"value":val["value"]})
+
+    return normalize(ret)
+
+
+def get_precip_chance(raw_data):
+    raw_values = raw_data["properties"]["probabilityOfPrecipitation"]["values"]
+    ret = []
+
+    for val in raw_values:
+        time_str, duration_str = val["validTime"].split('/')
+        time = datetime.datetime.strptime(time_str, "%Y-%m-%dT%H:%M:%S%z")
+        duration = parse_duration(duration_str)
+        ret.append({"time":time,"duration":duration,"value":val["value"]})
+
+    return normalize(ret)
+
+
+def get_precip_amount(raw_data):
+    raw_values = raw_data["properties"]["quantitativePrecipitation"]["values"]
+    ret = []
+
+    for val in raw_values:
+        time_str, duration_str = val["validTime"].split('/')
+        time = datetime.datetime.strptime(time_str, "%Y-%m-%dT%H:%M:%S%z")
+        duration = parse_duration(duration_str)
+        ret.append({"time":time,"duration":duration,"value":val["value"]})
+
+    return normalize(ret)
+
+
+def get_snowfall_amount(raw_data):
+    raw_values = raw_data["properties"]["snowfallAmount"]["values"]
+    ret = []
+
+    for val in raw_values:
+        time_str, duration_str = val["validTime"].split('/')
+        time = datetime.datetime.strptime(time_str, "%Y-%m-%dT%H:%M:%S%z")
+        duration = parse_duration(duration_str)
+        ret.append({"time":time,"duration":duration,"value":val["value"]})
+
+    return normalize(ret)
+
+
+def get_snow_level(raw_data):
+    raw_values = raw_data["properties"]["snowLevel"]["values"]
+    ret = []
+
+    for val in raw_values:
+        time_str, duration_str = val["validTime"].split('/')
+        time = datetime.datetime.strptime(time_str, "%Y-%m-%dT%H:%M:%S%z")
+        duration = parse_duration(duration_str)
+        ret.append({"time":time,"duration":duration,"value":val["value"]})
+
+    return normalize(ret)
+
+
+def get_visibility(raw_data):
+    raw_values = raw_data["properties"]["visibility"]["values"]
+    ret = []
+
+    for val in raw_values:
+        time_str, duration_str = val["validTime"].split('/')
+        time = datetime.datetime.strptime(time_str, "%Y-%m-%dT%H:%M:%S%z")
+        duration = parse_duration(duration_str)
+        ret.append({"time":time,"duration":duration,"value":val["value"]})
+
+    return normalize(ret)
+
+
+def get_wind_direction(raw_data):
+    raw_values = raw_data["properties"]["windDirection"]["values"]
+    ret = []
+
+    for val in raw_values:
+        time_str, duration_str = val["validTime"].split('/')
+        time = datetime.datetime.strptime(time_str, "%Y-%m-%dT%H:%M:%S%z")
+        duration = parse_duration(duration_str)
+
+        def degrees_to_cardinal(d):
+            dirs = ['N', 'NNE', 'NE', 'ENE', 'E', 'ESE', 'SE', 'SSE', 'S', 'SSW', 'SW', 'WSW', 'W', 'WNW', 'NW', 'NNW']
+            ix = round(d / (360. / len(dirs)))
+            return dirs[ix % len(dirs)]
+
+        direction_str = degrees_to_cardinal(val["value"])
+
+        ret.append({"time":time,"duration":duration,"value":direction_str})
+
+    return normalize(ret)
+
+
+def get_dewpoint(raw_data):
+    raw_values = raw_data["properties"]["dewpoint"]["values"]
+    ret = []
+
+    for val in raw_values:
+        val_celc = val["value"]
+        val_fahr = celcius_to_fahrenheit(val_celc)
+        time_str, duration_str = val["validTime"].split('/')
+        time = datetime.datetime.strptime(time_str, "%Y-%m-%dT%H:%M:%S%z")
+        duration = parse_duration(duration_str)
+        ret.append({"time":time,"duration":duration,"value_celc":val_celc,"value_fahr":val_fahr})
+
+    return normalize(ret)
+
+
+def get_hourly_data(raw_data, end_time):
+    temps = get_temperature(raw_data)
+    precip_chance = get_precip_chance(raw_data)
+    precip_amount = get_precip_amount(raw_data)
+    humidity = get_humidity(raw_data)
+    wind_speed = get_wind_speed(raw_data)
+    wind_direction = get_wind_direction(raw_data)
+
+    ret = []
+    i = 0
+    while i < len(temps) and temps[i]["time"] < end_time:
+        val_dict = { "time": temps[i]["time"],
+                     "temp": int(temps[i]["value_fahr"]),
+                     "humidity": int(humidity[i]["value"]),
+                     "precip_chance": int(precip_chance[i]["value"]),
+                     "precip_amount": int(precip_amount[i]["value"]),
+                     "wind_speed": int(wind_speed[i]["value"]),
+                     "wind_direction": wind_direction[i]["value"] }
+        ret.append(val_dict)
+        i+=1
+
+    return ret
+
+
diff --git a/main.py b/main.py
new file mode 100644
index 0000000..3fbf3e7
--- /dev/null
+++ b/main.py
@@ -0,0 +1,53 @@
+#!/usr/bin/env python3
+import json, requests, datetime, argparse, pytz
+
+import library
+
+def parse_args():
+    parser = argparse.ArgumentParser()
+    parser.add_argument('-d', '--days', type=int)
+    parser.add_argument('-H', '--hours', type=int)
+    parser.add_argument('-l', '--location', type=str, required=True)
+    return parser.parse_args()
+
+
+def hourly_forecast(args, raw_data):
+
+    init_time = library.get_current_rounded_time()
+    if args.hours is not None:
+        delta = datetime.timedelta(hours=args.hours)
+    elif args.days is not None:
+        delta = datetime.timedelta(days=args.days)
+    else:
+        delta = datetime.timedelta(hours=(24-init_time.hour))
+    end_time = init_time + delta
+
+    hourly_data = library.get_hourly_data(raw_data, end_time)
+
+    for point in hourly_data:
+        print(point["time"].strftime("%a %x %I:%M %p"))
+        print(f'\t Temperature - { point["temp"] }°F')
+        print(f'\t Humidity - { point["humidity"] }%')
+        print(f'\t Chance of Precipitation - { point["precip_chance"] }%')
+        print(f'\t Precipitation Amount - { point["precip_amount"] } in')
+        print(f'\t Wind Speed - { point["wind_speed"] } MPH')
+        print(f'\t Wind Direction - { point["wind_direction"] }')
+        print('\n')
+
+
+
+def daily_forecast(raw_data):
+    pass
+
+
+def main():
+    args = parse_args()
+    latitude, longitude = library.get_lat_long(args.location)
+    grid_data = library.get_grid_data(latitude, longitude)
+    raw_data = library.get_raw_data(grid_data["grid_id"], grid_data["grid_x"], grid_data["grid_y"])
+    hourly_forecast(args, raw_data)
+
+
+
+if __name__ == '__main__':
+    main()