Automated Munroe geohashing

munroe_geohashing.py

#!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# == Author ==
# Cristian Consonni
# This script was generated making extensive use of ChatGPT v3.5
#
# == License ==
#
# MIT License
#
# Copyright (c) 2023 Cristian Consonni
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.

import argparse
import geocoder
import hashlib
import requests
import webbrowser
import yfinance as yf

from datetime import datetime, timedelta


def get_current_date():
    # Get the current date and format it as YYYY-MM-DD
    return datetime.now().strftime('%Y-%m-%d')


def get_dow_jones(date=None):
    dow = yf.Ticker('^DJI')

    # Get the earliest and latest dates for which data is available
    earliest_date = dow.history(period='max').index[0]
    latest_date = dow.history(period='max').index[-1]

    # Convert the input date to datetime object
    if date is None:
        end_date = datetime.now()
    elif isinstance(date, str):
        end_date = datetime.strptime(date, '%Y-%m-%d').date()
    elif isinstance(date, datetime):
        end_date = date.date()

    # If the input date is outside the available range, 
    # get the closest available date
    if end_date < earliest_date:
        end_date = earliest_date
    elif end_date > datetime.today().date():
        end_date = latest_date

    start_date = end_date - timedelta(days=1)
    
    # Get the Dow Jones index for the selected date
    dow_data = dow.history(start=start_date, end=end_date)

    if len(dow_data) == 0:
        retries = 1
        while (len(dow_data) == 0) and (retries < 5):
            retries += 1

            # if no data is available for the selected date, get the day before
            new_end_date = end_date - timedelta(days=1)
            new_start_date = new_end_date - timedelta(days=1)
            dow_data = dow.history(start=new_start_date, end=new_end_date)

            start_date = new_start_date
            end_date = new_end_date

        # if nothing yet, pick a random date
        if len(dow_data) == 0:
            dow_data = dow.history(period='max').sample(n=1)

    # Return the Dow Jones index for the selected date and the actual date used
    return dow_data['Open'][-1], end_date


def get_city_coordinates(city):
    # Use the geocoder module to get the latitude and longitude of the city
    g = geocoder.osm(city)
    latitude = g.lat
    longitude = g.lng

    # Return the latitude and longitude as a tuple
    return (latitude, longitude)


def get_current_location():
    # Make a request to the IP Geolocation API
    response = requests.get('https://ipgeolocation.abstractapi.com/v1/'
                            '?api_key=<my_api_key>')

    # Parse the JSON response to get the latitude, longitude, and city name
    data = response.json()
    latitude = data['latitude']
    longitude = data['longitude']
    city = data['city']

    # Return the latitude, longitude, and city as a tuple
    return (latitude, longitude, city)


def geohash(latitude, longitude, datedow):
    '''Compute geohash() using the Munroe algorithm.
    >>> geohash(37.421542, -122.085589, b'2005-05-26-10458.68')
    37.857713 -122.544543
    '''
    # https://xkcd.com/426/
    h = hashlib.md5(datedow, usedforsecurity=False).hexdigest()
    p, q = [('%f' % float.fromhex('0.' + x)) for x in (h[:16], h[16:32])]
    
    newlat = float('%d%s' % (latitude, p[1:]))
    newlon = float('%d%s' % (longitude, q[1:]))

    return (newlat, newlon)


def gmaps(latitude, longitude):
    url = ("https://www.google.com/maps/search/"
           f"?api=1&query={latitude},{longitude}&zoom=5")

    webbrowser.open(url)


def main():
    parser = argparse.ArgumentParser(
        description='Generate geohash and display on Google Maps'
        )
    parser.add_argument(
        '--city',
        help='The name of the city to generate the geohash for'
        )
    parser.add_argument(
        '--date',
        help='The date to fetch the Dow Jones opening value for '
             'in the format YYYY-MM-DD'
        )

    args = parser.parse_args()

    if args.city:
        latitude, longitude = get_city_coordinates(args.city)
        print(f"The coordinates of {args.city} are ({latitude}, {longitude})")
    else:
        latitude, longitude, city = get_current_location()
        print(f"Your current location is ({latitude}, {longitude}) in {city}")

    if args.date:
        date = args.date
        print(f"Using date {date}")
    else:
        date = get_current_date()
        print(f"The current date is {date}")

    dow_value, actual_date = get_dow_jones(date)
    print(f"The opening value for the Dow Jones index on {date} was "
          f"{dow_value}")

    # combine values in datedow
    datedow = f'{date}-{dow_value}'.encode('utf-8')

    newlatitude, newlongitude = geohash(latitude, longitude, datedow)
    print(f"Munrow geohash: ({newlatitude}, {newlongitude})")

    gmaps(newlatitude, newlongitude)


if __name__ == '__main__':
    main()
    exit(0)