Steam市场解析

Question

我有一个link

它最后有“_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 解析项目链接，这会给我随机价格的项目，即升序排序不起作用

我做错了什么？

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因为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，主题标签是某种页面标记的指示符，这里有一个 link 给出了完整的解释。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)

这不会导致执行排序的 javascript 函数调用。我强烈推荐主题标签上的链接，因为它在解释方面比我做得更好。

---

现在关于如何实现你想要的，你有两个选择：

1. 使用 selenium 库来模拟浏览器
2. 继续使用您正在使用的数据，并自己手动对数据进行排序（这很简单，您将了解更多信息）

我个人会推荐方法 2，因为学习 selenium 可能有点让人头疼，而且通常不值得……在我看来。

Answer 2

此页面使用 JavaScript 获取排序数据，但 BeautifulSoup/urllib 无法运行 JavaScript

但是在Firefox/Chrome中使用DevTools（标签：Network，过滤器：XHR）我发现JavaScript从某个url读取JSON数据，并且有带有排序数据的HTML -所以你可以使用这个 url 和 BeautifulSoup 来获取排序数据。

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，它从旧网址读取并在 Python 中排序。但它只能对第一页上的数据进行排序。为了获得更好的结果，它必须阅读所有页面 - 这需要很多时间。

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))