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124 lines
3.8 KiB
Python
124 lines
3.8 KiB
Python
"""
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Scrapes the Louisiana lottery website for scratch-off ticket
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data and calculates the expected value for each game.
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Louisiana publishes the number of tickets printed and how many
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tickets are printed at each prize level.
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We can calculated the expected value of a game by summing
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the value of all the prizes and dividing that by the cost
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of all the tickets.
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The louisianalottery website has an "top prizes remaining" or an "index" page that
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has links to every game that could still be profitable.
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Each individual game has a section for the "game rules" page and a prize table.
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We can use each individual game page to gather the important data, and
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then run our calculations.
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Website that we'll be scraping:
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https://louisianalottery.com/scratch-offs/top-prizes-remaining
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Example usage:
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python -m louisiana
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Or:
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LOGLEVEL=DEBUG USE_CACHE=True python -m louisiana
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The following behavior is configurable through shell environment variables.
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Set LOGLEVEL to print useful debug info to console.
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LOGLEVEL=[DEBUG,INFO,WARNING,ERROR,CRITICAL]
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Defaults to WARNING.
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Set USE_CACHE to cache responses. This speeds up development
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and is nice to the servers we're hitting.
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USE_CACHE=[True]
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Defaults to False. Note: Setting this env variable to the string False
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will cause it to use cache because the string "False" evaluates to Truthy.
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Either set it to True or don't set it.
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"""
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import sys
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import traceback
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from copy import deepcopy
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import locale
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import logging
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import os
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import re
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from bs4 import BeautifulSoup as bs
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import requests
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import pandas as pd
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from lottery_data_scraper.schemas import GameSchema
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from lottery_data_scraper.util import fetch_html
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logger = logging.getLogger(__name__)
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# It's worth assigning to constants values that are used in many
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# places throughout a script.
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BASE_URL = "http://www.louisianalottery.com"
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INDEX_URL = "https://louisianalottery.com/scratch-offs/top-prizes-remaining"
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def parse_index(html):
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soup = bs(html, "lxml")
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table = soup.find("table")
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game_hrefs = table.select("tr > td > a")
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game_urls = list(map(lambda x: "https:" + x.attrs["href"], game_hrefs))
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return game_urls
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# TODO: convert pandas to beautiful soup
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def parse_game(url, html):
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soup = bs(html, "lxml")
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price = soup.select('div[id="scratch-off-prize-info"] td')[1].text.replace("$", "")
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name = soup.find(class_="scratch-off-title").text
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num = url.split("/")[-2]
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grand_prize_row = soup.select(
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'div[id="scratch-off-table-tier"] table > tbody > tr'
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)[0]
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grand_prize_odds = float(
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grand_prize_row.select("td")[1].text.split(" in ")[1].replace(",", "",)
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)
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grand_prize_num = int(grand_prize_row.select("td")[2].text)
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num_tx = int(grand_prize_odds * grand_prize_num)
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table = soup.find_all("table")[2]
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df = pd.read_html(str(table))[0]
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df = df.replace("TICKET", price)
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prizes = [
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{
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"prize": prize,
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"value": float(prize.replace("$", "").replace(",", "")),
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"claimed": int(claimed),
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"available": int(total) - int(claimed),
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}
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for prize, _, total, claimed in [list(r[1])[:4] for r in df.iterrows()]
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]
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game = {
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"name": name,
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"game_id": num,
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"url": url,
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"state": "la",
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"price": float(price),
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"num_tx_initial": num_tx,
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"prizes": prizes,
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}
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return game
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def main():
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index_html = fetch_html(INDEX_URL)
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game_urls = parse_index(index_html)
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url_htmls = zip(game_urls, [fetch_html(url) for url in game_urls])
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games = []
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for url, html in url_htmls:
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try:
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game = parse_game(url, html)
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except Exception as e:
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logger.error("Unable to parse {}.\n{}".format(url, e))
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continue
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games.append(game)
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return games
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if __name__ == "__main__":
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games = main()
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schema = GameSchema(many=True)
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print(schema.dumps(games))
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