research.py

import os
import csv
import collections
from typing import List

data = []

Record = collections.namedtuple(
    'Record',
    'date,actual_mean_temp,actual_min_temp,actual_max_temp,'
    'average_min_temp,average_max_temp,record_min_temp,record_max_temp,'
    'record_min_temp_year,record_max_temp_year,actual_precipitation,'
    'average_precipitation,record_precipitation'
)


def init():
    base_folder = os.path.dirname(__file__)
    filename = os.path.join(base_folder, 'data', 'seattle.csv')

    with open(filename, 'r', encoding='utf-8') as fin:
        reader = csv.DictReader(fin)

        data.clear()
        for row in reader:
            record = parse_row(row)
            data.append(record)


def parse_row(row):
    row['actual_mean_temp'] = int(row['actual_mean_temp'])
    row['actual_min_temp'] = int(row['actual_min_temp'])
    row['actual_max_temp'] = int(row['actual_max_temp'])
    row['average_min_temp'] = int(row['average_min_temp'])
    row['average_max_temp'] = int(row['average_max_temp'])
    row['record_min_temp'] = int(row['record_min_temp'])
    row['record_max_temp'] = int(row['record_max_temp'])
    row['record_min_temp_year'] = int(row['record_min_temp_year'])
    row['record_max_temp_year'] = int(row['record_max_temp_year'])
    row['actual_precipitation'] = float(row['actual_precipitation'])
    row['average_precipitation'] = float(row['average_precipitation'])
    row['record_precipitation'] = float(row['record_precipitation'])

    return Record(**row)


def hot_days() -> List[Record]:
    return sorted(data, key=lambda r: -r.actual_max_temp)


def cold_days() -> List[Record]:
    return sorted(data, key=lambda r: r.actual_min_temp)


def wet_days() -> List[Record]:
    return sorted(data, key=lambda r: -r.actual_precipitation)