Merge pull request #111 from MylesPerHour201/main

Add more data

README.md

@@ -61,7 +61,9 @@ Wave Period:  9.8
 | color / c   | Choose color of wave art. Ex: `color=light_blue`   | 
 | json / j   | Output the data in JSON format. Must be the only argument  | 
 | gpt / g   | Activates the GPT surf report. Change the `GPT_PROMPT` variable in `.env` to customize responses. Default = off  |
-
+| show_cloud_cover / scc   | Show the hourly cloud cover   |
+| show_visibility / sv   | Show the hourly visibility   |
+
 **Examples**
 * Arguments are seperated by commas.
 * `curl localhost:8000`

src/api.py

@@ -4,6 +4,7 @@
 
 from http import HTTPStatus
 
+import numpy as np
 import openmeteo_requests
 import pandas as pd
 import requests
@@ -298,6 +299,61 @@ def forecast(lat, long, decimal, days=0):
     return forecast_data
 
 
+def get_hourly_forecast(lat, long, days=1, unit="fahrenheit"):
+    """
+    Gets hourly weather data
+    """
+    # Setup the Open-Meteo API client with cache and retry on error
+    cache_session = requests_cache.CachedSession(".cache", expire_after=3600)
+    retry_session = retry(cache_session, retries=5, backoff_factor=0.2)
+    openmeteo = openmeteo_requests.Client(session=retry_session)
+
+    # Make sure all required weather variables are listed here
+    # The order of variables in hourly or daily is important
+    # to assign them correctly below
+    url = "https://api.open-meteo.com/v1/forecast"
+    params = {
+        "latitude": lat,
+        "longitude": long,
+        "hourly": ["cloud_cover", "visibility"],
+        "temperature_unit": unit,
+        "wind_speed_unit": "mph",
+        "precipitation_unit": "inch",
+        "forecast_days": days,
+    }
+
+    responses = openmeteo.weather_api(url, params=params)
+    response = responses[0]
+
+    hourly = response.Hourly()
+    hourly_cloud_cover = hourly.Variables(0).ValuesAsNumpy()
+    hourly_visibility = hourly.Variables(1).ValuesAsNumpy()
+
+    hourly_data = pd.DataFrame({
+        "date": pd.date_range(
+            start=pd.to_datetime(hourly.Time(), unit="s", utc=True),
+            end=pd.to_datetime(hourly.TimeEnd(), unit="s", utc=True),
+            freq=pd.Timedelta(seconds=hourly.Interval()),
+            inclusive="left",
+        ),
+        "cloud_cover": hourly_cloud_cover,
+        "visibility": hourly_visibility,
+    })
+
+    # Sets variable to get current time
+    current_time = pd.Timestamp.now(tz="UTC")
+
+    # Sets variable to find index of current hour
+    curr_hour = np.argmin(np.abs(hourly_data["date"] - current_time))
+
+    # Creates dictionary for the current hour's weather data
+    curr_hour_data = {}
+    for i in ["cloud_cover", "visibility"]:
+        curr_hour_data[i] = round(float(hourly_data[i].iloc[curr_hour]), 1)
+
+    return curr_hour_data
+
+
 def gather_data(lat, long, arguments):
     """
     Calls APIs though python files,
@@ -312,6 +368,8 @@ def gather_data(lat, long, arguments):
 
     wind_temp = current_wind_temp(lat, long, arguments["decimal"])
 
+    hourly_dict = get_hourly_forecast(lat, long, arguments["decimal"])
+
     rain_data = get_rain(lat, long, arguments["decimal"])
     air_temp, wind_speed, wind_dir = wind_temp[0], wind_temp[1], wind_temp[2]
     rain_sum, precipitation_probability_max = rain_data[0], rain_data[1]
@@ -337,6 +395,8 @@ def gather_data(lat, long, arguments):
         "Unit": arguments["unit"],
         "Rain Sum": rain_sum,
         "Precipitation Probability Max": precipitation_probability_max,
+        "Cloud Cover": hourly_dict["cloud_cover"],
+        "Visibility": hourly_dict["visibility"],
     }
     return ocean_data_dict
 

src/cli.py

@@ -46,7 +46,7 @@ def run(lat=0, long=0, args=None):
     if arguments["json_output"] == 0:
         # Response prints all the outputs & returns the GPT response
         response = helper.print_outputs(
-            city, ocean_data_dict, arguments, gpt_prompt, gpt_info
+            ocean_data_dict, arguments, gpt_prompt, gpt_info
         )
         # Returns ocean data, GPT response
         return ocean_data_dict, response

src/helper.py

@@ -40,6 +40,8 @@ def arguments_dictionary(lat, long, city, args):
         "forecast_days": get_forecast_days(args),
         "color": get_color(args),
         "gpt": 0,
+        "show_cloud_cover": 0,
+        "show_visibility": 0,
     }
     # Updates the arguments dict with the values from the CLI args
     arguments = set_output_values(args, arguments)
@@ -87,6 +89,10 @@ def set_output_values(args, arguments_dictionary):  # noqa
         "srs": ("show_rain_sum", 1),
         "show_precipitation_prob": ("show_precipitation_prob", 1),
         "spp": ("show_precipitation_prob", 1),
+        "show_cloud_cover": ("show_cloud_cover", 1),
+        "scc": ("show_cloud_cover", 1),
+        "show_visibility": ("show_visibility", 1),
+        "sv": ("show_visibility", 1),
     }
 
     # Update arguments_dictionary based on the cli arguments in args
@@ -155,6 +161,8 @@ def print_ocean_data(arguments_dict, ocean_data_dict):
             "Precipitation Probability Max",
             "Precipitation Probability Max: ",
         ),
+        ("show_cloud_cover", "Cloud Cover", "Cloud Cover: "),
+        ("show_visibility", "Visibility", "Visibility: "),
     ]
 
     # arg_key example: "show_height : 1" from arguments_dict
@@ -256,14 +264,12 @@ def json_output(data_dict):
     return data_dict
 
 
-def print_outputs(city, ocean_data_dict, arguments, gpt_prompt, gpt_info):
+def print_outputs(ocean_data_dict, arguments, gpt_prompt, gpt_info):
     """
     Basically the main printing function,
     calls all the other printing functions
     """
     print("\n")
-    if city == "No data":
-        print("No location found")
     if ocean_data_dict["Height"] == "No data":
         print(ocean_data_dict["Lat"], ocean_data_dict["Long"])
         print("No ocean data at this location.")
@@ -286,6 +292,7 @@ def print_outputs(city, ocean_data_dict, arguments, gpt_prompt, gpt_info):
     )
     # Prints the forecast(if activated in CLI args)
     print_forecast(arguments, forecast)
+
     # Checks if GPT in args, prints GPT response if True
     gpt_response = None
     if arguments["gpt"] == 1: