'''
    DS2000
    Spring 2020
    Source code from class - file processing

    This example has structured data; the
    input file is a csv (comma-separated values)
'''

import csv

DATE = 0
TIME = 1
LAT = 2
LONG = 3
WIND = 4
PRESSURE = 5

CAT5 = 157
CAT4 = 130
CAT3 = 111
CAT2 = 96

def process_file(filename):
    ''' Function: process_file
        Parameter: Name of the file (a string)
        Returns: nested list of strings, the contents
                 of the file
        Does: assumes the file to be read is a CSV file
    '''
    data = []
    counter = 0
    with open(filename) as infile:
        csv_contents = csv.reader(infile, delimiter = ',')
        for row in csv_contents:
            if counter == 0:
                counter += 1
            else:
                data.append(row)
    return data

def when_landfall(data, long):
    ''' Function: when_landfall
        Parameter: nested list of strings, longitude to cross going west (float)
        Return: date/time when hurricane made landfall (string)
        Assumes: data is in chronological order
    '''
    for row in data:
        if float(row[LONG]) < long:
            return row[DATE] + ' ' + row[TIME]
    return 'never'

def worst_cat(data):
    ''' Function: worst_cat
        Parameters: nested list of strings for hurricane data
        Returns: The worst category hit (int)
    '''
    worst_wind = 0
    for row in data:
        if int(row[WIND]) > worst_wind:
            worst_wind = int(row[WIND])
    # Now that we have the max wind, find the
    # category it belongs in (this is really similar
    # to the grading problem in HW3!!!)
    if worst_wind >= CAT5:
        return 5
    elif worst_wind >= CAT4:
        return 4
    elif worst_wind >= CAT3:
        return 3
    elif worst_wind >= CAT2:
        return 2
    else:
        return 1

     
def main():

    # Step One: Read the file and save it in a nested list of strings
    hurricane_data = process_file('irma.csv')

    # Question: When did Irma first make landfall in Florida
    # (assumes the data are in chronological order)
    landfall = when_landfall(hurricane_data, -80)
    print('Irma made landfall at:', landfall)

    # Question: What category did Irma get to?
    cat = worst_cat(hurricane_data)
    print('At its worst, Hurricane Irma got to a category', cat)

    # Question: How big is the timeline that our data comes from?
    print('Data starts on', hurricane_data[0][DATE])
    print('Data ends on', hurricane_data[-1][DATE])
main()