| Algorithm: Evolution Strategies | |
| Code & explanation available at: | |
| https://github.com/alirezamika/bipedal-es | |
Here we want to scrape product name, price and rating from ebay product pages:
url = 'https://www.ebay.com/itm/Sony-PlayStation-4-PS4-Pro-1TB-4K-Console-Black/203084236670'
wanted_list = ['Sony PlayStation 4 PS4 Pro 1TB 4K Console - Black', 'US $349.99', '4.8']
scraper.build(url, wanted_list)
| from autoscraper import AutoScraper | |
| url = 'https://www.ebay.com/sch/i.html?_nkw=iphone' | |
| wanted_list = ['Apple iPhone X 64GB Factory Unlocked Smartphone', '$389.99', 'https://www.ebay.com/itm/Apple-iPhone-X-64GB-Factory-Unlocked-Smartphone/254187579586?epid=238944741&hash=item3b2ec2a8c2:g:ZPQAAOSwD6VdpL~9'] | |
| scraper = AutoScraper() | |
| result = scraper.build(url=url, wanted_list=wanted_list) |
| scraper.set_rule_aliases({'rule_0aok': 'title', 'rule_vn5z': 'price', 'rule_buz1': 'url'}) | |
| scraper.keep_rules(['rule_0aok', 'rule_vn5z', 'rule_buz1']) | |
| scraper.save('ebay-search') |
| url = 'https://www.etsy.com/search?q=macbook' | |
| wanted_dict = { | |
| 'title': [ | |
| 'Apple MacBook Pro i9 32GB 500GB Radeon 560X 15.4 2018 Touch Bar 2.9GHz 6-Core', | |
| 'Laptop MacBook Premium Ergonomic Wood Stand Holder Computer Gift Nerd Tech Geek Mens, woodworking gift, Home office workspace accessories', | |
| ], | |
| 'price': ['1,500.00', '126.65'], | |
| 'url': ['851553172'] | |
| } |
| scraper.keep_rules(['rule_705x', 'rule_70m8', 'rule_d9wp', 'rule_kv6p']) | |
| scraper.save('etsy-search') |
| from autoscraper import AutoScraper | |
| from flask import Flask, request | |
| ebay_scraper = AutoScraper() | |
| etsy_scraper = AutoScraper() | |
| ebay_scraper.load('ebay-search') | |
| etsy_scraper.load('etsy-search') | |
| app = Flask(__name__) |
| class TicTacToe: | |
| def __init__(self, render=True): | |
| self.board = [[0, 0, 0] for _ in range(3)] | |
| self.player = 1 | |
| self.repr = {0: ".", 1: "x", -1: "o"} | |
| self.render = render | |
| def _get_winner(self): | |
| # check horizontal | |
| for i in range(3): |
| from collections import defaultdict | |
| class Q: | |
| def __init__(self, alpha=0.5, discount=0.5): | |
| self.alpha = alpha | |
| self.discount = discount | |
| self.values = defaultdict(lambda: defaultdict(lambda: 0.0)) | |
| def update(self, state, action, next_state, reward): |
| import random | |
| from q import Q | |
| from tictactoe import TicTacToe | |
| class Agent: | |
| def __init__(self): | |
| self.eps = 1.0 | |
| self.qlearner = Q() |