'''
    temps.py
    DS2000
    Spring 2022
    

    <<<UPDATED with finished code!>>>>

    We added to this during class:
     - Write  a main function that calls our csv_to_dct function,

       calls our dct_to_weather function, and creates a scatterplot
       of all our weather locations, using current temperature data
    
    <<<original starter notes>>>>
    
    There's nothing new in here, don't worry! Just reusing two functions
    we've done a lot recently: 
        1 - csv_to_dct, read a CSV file into a list of dictionaries
            (one dictionary per row in file, keys come from first row)
        2 - dct_to_weather, turn a list of dictionaries into objects
            (in this case, we're making Weather objects, but the function
             is basically the same as making Movie objects, and Review objects)
            
'''


import csv
import matplotlib.pyplot as plt
from weather import Weather

LOCATIONS  = "locations.csv"

def csv_to_dict(filename):
    ''' Function: csv_to_dict
        Parameter: filename, a string
        Returns: a list of dictionaries where each dictionary reps one row
                 of the file; keys of all dictionaries are file's first row
    '''
    data = []
    with open(filename, "r") as infile:
        csvfile = csv.reader(infile, delimiter = ",")
        keys = next(csvfile)
        for row in csvfile:
            d = {}
            for i in range(len(row)):
                d[keys[i]] = row[i]
            data.append(d)
    return data

def dct_to_weather(list_of_dct):
    ''' Function: dct_to_objs
        Parameters: list of dictionaries, where each one reps one location
        Returns: list of Weather objects
    '''
    weathers = []
    for d in list_of_dct:
        lat = float(d["latitude"])
        long = float(d["longitude"])
        w = Weather(lat, long)
        weathers.append(w)
    return weathers         


def main():
    # Step one -- gather data from the file
    data = csv_to_dict(LOCATIONS)
    
    # Step two --- turn list of dictionaries into objects
    weathers = dct_to_weather(data)
    
    # Step three -- commmunicate! Make the weather map
    lats = [w.lat for w in weathers]
    longs = [w.long for w in weathers]
    colors = [w.color for w in weathers]
    plt.scatter(longs, lats, color = colors)
             
    
    
main()