Steam市场解析

Question

我有一个link

最后有“ _price_asc”，它进行升序排序。当我在浏览器中点击此链接时，排序工作正常。

但是！如果我尝试使用bs4解析商品链接，这会为我提供随机价格的商品，即升序排序不起作用

我在做什么错了？

from urllib.request import urlopen
from bs4 import BeautifulSoup

link = 'https://steamcommunity.com/market/search?q=&category_730_ItemSet%5B%5D=any&category_730_ProPlayer%5B%5D=any&category_730_StickerCapsule%5B%5D=any&category_730_TournamentTeam%5B%5D=any&category_730_Weapon%5B%5D=any&category_730_Type%5B%5D=tag_CSGO_Type_Knife&appid=730#p1_price_asc'

total_links = ''

page = urlopen(link)
bs_page = BeautifulSoup(page.read(), features="html.parser")
objects = bs_page.findAll(class_="market_listing_row_link")

for g in range(10):
    total_links += str(objects[g]["href"]) + '\n'
print(total_links)

Answer 1

发生这种情况的原因是，如果您查看以下链接

https://steamcommunity.com/market/search?q=&category_730_ItemSet%5B%5D=any&category_730_ProPlayer%5B%5D=any&category_730_StickerCapsule%5B%5D=any&category_730_TournamentTeam%5B%5D=any&category_730_Weapon%5B%5D=any&category_730_Type%5B%5D=tag_CSGO_Type_Knife&appid=730#p1_price_asc

链接以“ ＃p1_price_asc ”结尾，井号是各种页面标记的指示符，此处是link说明。基本上，URL中的“＃”通常由javascript函数调用。

由于您正在使用以下方式下载页面：

page = urlopen(link)

这不会导致进行排序的javascript函数调用。我强烈建议主题标签上的链接，因为这样做比我做的要好得多。

---

现在关于如何实现所需的目标，您有两个选择：

1. 使用硒库来模拟浏览器
2. 继续使用您正在使用的内容，然后自己手动对数据进行排序（这是微不足道的，您将学到更多）

我个人会推荐方法2，因为学习硒可能会让人有些痛苦，而且通常不值得……我认为。

Answer 2

此页面使用JavaScript获取排序的数据，但是BeautifulSoup / urllib无法运行JavaScript

但是在DevTools / Firefox中使用Chrome（标签：Network，过滤器：XHR），我发现JavaScript读取JSON某些网址中的数据，并且HTML中包含已排序的数据-因此您可以将此网址与BeautifulSoup一起使用以获取已排序的数据。

from urllib.request import urlopen
from bs4 import BeautifulSoup
import json

# new url 

link = 'https://steamcommunity.com/market/search/render/?query=&start=0&count=10&search_descriptions=0&sort_column=price&sort_dir=asc&appid=730&category_730_ItemSet%5B%5D=any&category_730_ProPlayer%5B%5D=any&category_730_StickerCapsule%5B%5D=any&category_730_TournamentTeam%5B%5D=any&category_730_Weapon%5B%5D=any&category_730_Type%5B%5D=tag_CSGO_Type_Knife'

page = urlopen(link)

data = json.loads(page.read().decode())
html = data['results_html']

bs_page = BeautifulSoup(html, features="html.parser")
objects = bs_page.findAll(class_="market_listing_row_link")

data = []

for g in objects:
    link  = g["href"]
    price = g.find('span', {'data-price': True}).text
    data.append((price, link))

print("\n".join(f"{price} | {link}" for price, link in data))

结果：

$67.43 USD | https://steamcommunity.com/market/listings/730/%E2%98%85%20Navaja%20Knife%20%7C%20Urban%20Masked%20%28Field-Tested%29
$67.70 USD | https://steamcommunity.com/market/listings/730/%E2%98%85%20Navaja%20Knife%20%7C%20Night%20Stripe%20%28Field-Tested%29
$69.00 USD | https://steamcommunity.com/market/listings/730/%E2%98%85%20Navaja%20Knife%20%7C%20Night%20Stripe%20%28Minimal%20Wear%29
$69.52 USD | https://steamcommunity.com/market/listings/730/%E2%98%85%20Navaja%20Knife%20%7C%20Scorched%20%28Battle-Scarred%29
$69.48 USD | https://steamcommunity.com/market/listings/730/%E2%98%85%20Navaja%20Knife%20%7C%20Safari%20Mesh%20%28Field-Tested%29
$70.32 USD | https://steamcommunity.com/market/listings/730/%E2%98%85%20Navaja%20Knife%20%7C%20Forest%20DDPAT%20%28Battle-Scarred%29
$70.90 USD | https://steamcommunity.com/market/listings/730/%E2%98%85%20Navaja%20Knife%20%7C%20Night%20Stripe%20%28Well-Worn%29
$70.52 USD | https://steamcommunity.com/market/listings/730/%E2%98%85%20Navaja%20Knife%20%7C%20Forest%20DDPAT%20%28Field-Tested%29
$71.99 USD | https://steamcommunity.com/market/listings/730/%E2%98%85%20Navaja%20Knife%20%7C%20Boreal%20Forest%20%28Field-Tested%29
$72.08 USD | https://steamcommunity.com/market/listings/730/%E2%98%85%20Navaja%20Knife%20%7C%20Scorched%20%28Field-Tested%29

---

顺便说一句：：这是我的第一个版本，它是从旧的url中读取并使用Python进行排序的。但是它只能对首页上的数据进行排序。为了获得更好的结果，必须阅读所有页面-这将花费大量时间。

from urllib.request import urlopen
from bs4 import BeautifulSoup

link = 'https://steamcommunity.com/market/search?q=&category_730_ItemSet%5B%5D=any&category_730_ProPlayer%5B%5D=any&category_730_StickerCapsule%5B%5D=any&category_730_TournamentTeam%5B%5D=any&category_730_Weapon%5B%5D=any&category_730_Type%5B%5D=tag_CSGO_Type_Knife&appid=730#p1_price_asc'
page = urlopen(link)

bs_page = BeautifulSoup(page.read(), features="html.parser")
objects = bs_page.findAll(class_="market_listing_row_link")

data = []

for g in objects:
    link  = g["href"]
    price = g.find('span', {'data-price': True})['data-price']
    price = int(price)
    data.append((price,link))

data = sorted(data)

print("\n".join(f"${price/100} USD | {link}" for price, link in data))