我现在向您道歉，因为我确定问题的格式和所提供的信息与本网站的预期不符。我已经对SQL和VBA进行编码已有几年了，我正在尝试采用第三种语言来增强我的技能。随着时间的流逝，我会变得更好。
现在是我的问题...
我正在尝试使用在BasketballReference.com上使用过的代码来刮取一系列表格，但是在NBA.com上，该代码什么也没有带来。进一步挖掘时，make_soup不包含在浏览器中检查表时看到的tr和td标签。下面是我使用的代码，并提供了我的csv文件外观的图片作为参考。
import urllib
import urllib.request
from bs4 import BeautifulSoup
import os
import csv
import time
def make_soup(url):
thepage = urllib.request.urlopen(url)
soupdata = BeautifulSoup(thepage, "html.parser")
return soupdata
with open('PlayTypeKey.csv', 'r') as PlaytypeData:
csv_reader = csv.reader(PlaytypeData)
a = []
b = []
c = []
d = []
next(csv_reader)
for row in csv_reader:
a1 = row[0]
b1 = row[1]
c1 = row[2]
d1 = row[3]
a.append(a1)
b.append(b1)
c.append(c1)
d.append(d1)
playerdatasaved = ""
i = 0
while i < 5:
soup = make_soup("http://stats.nba.com/players/"+a[i]+"/?Season="+b[i]+"&SeasonType=Regular%20Season&PerMode="+c[i]+"&OD="+d[i])
for record in soup.findAll('tr'):
playerdata = b[i]+ a[i] + ","
for data in record.findAll('td'):
playerdata=playerdata+","+data.text
playerdatasaved = playerdatasaved + "\n" + playerdata[1:]
i=i+1
header = "Season,PlayType,PLAYER,TEAM,GP,POSS,FREQ,PPP,PTS,FGM,FGA,FG%,EFG%,FT-Freq,TO-Freq,SF-Freq,AND ONE-Freq,SCORE-Freq,PERCENTILE"
file = open(os.path.expanduser("BasketballPlayTypeData.csv"), "wb")
file.write(bytes(header, encoding="ascii", errors='ignore'))
file.write(bytes(playerdatasaved, encoding="ascii", errors='ignore'))
PlayTypeKey.csv数据：
PlayType Season Mode OffDef
isolation 2015-16 Totals offensive
isolation 2016-17 Totals offensive
isolation 2017-18 Totals offensive
transition 2015-16 Totals offensive
transition 2016-17 Totals offensive
transition 2017-18 Totals offensive
我有限的故障排除能力告诉我，当我从URL中提取汤时，表数据不会恢复。当打印汤的文本时，我得到了...
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NBA.com/Stats | Players Isolation
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{{ team.city }} {{ team.name }}
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{{ t.city }} {{ t.name }}
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{{ t.city }} {{ t.name }}
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Search For A Player or Team
No Results Found
{{ ::item.city }} {{ ::item.name }}
{{ ::item.fn }} {{ ::item.ln }}
{{ ::item.fn }} {{ ::item.ln }}
See More Results
Stats Home
/
Players
/
Playtype
/
Isolation
{{ alpha }}
Sortable Player Stats
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{{ betaText }}
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{{ gammaText }}
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{{ gammaText }}
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Minimum of 10 min/game and 10 possessions per play type to qualify.
provided by Synergy
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上面粘贴的内容的底部是表头，但表本身没有相应的文本或代码。我不会用打印HTML时得到的内容来弄乱这篇文章，但是搜索tr或td标签时却没有任何结果。
在此先感谢所有花时间研究此问题的人，我只想说这个网站对我来说已经非常有价值。
答案 0 :(得分：0)
该网页不包含任何带有TR和TD的表。页面首先显示该数据，然后通过单独的调用请求所有数据，然后使用Javascript呈现该数据。通常，您需要使用诸如硒之类的东西来完成此操作，但是更快的方法是使用浏览器监视网络请求并使用Python重新创建它们。
在这种情况下，请求导致所有数据以JSON格式返回，这比需要BeautifulSoup解析起来容易得多。只需使用Python的JSON库加载它，您便会将所有播放器数据作为一个大的Python数据结构。
在读取CSV文件时，一次只使用一行信息会比尝试构建多个列表然后在单独的循环中建立索引要容易得多。
您需要的JSON请求所使用的参数与尝试获取的HTML页面的参数略有不同（通过监视浏览器中的网络活动可以看出），因此需要更新CSV文件：
PlayType,Season,Mode,OffDef
isolation,2015,Totals,offensive
isolation,2016,Totals,offensive
isolation,2017,Totals,offensive
transition,2015,Totals,offensive
transition,2016,Totals,offensive
transition,2017,Totals,offensive
获取数据的脚本如下：
import urllib
import urllib.request
import os
import csv
import json
from operator import itemgetter
fieldnames = ["PlayerFirstName", "PlayerLastName", "TeamNameAbbreviation", "GP", "Poss"]
req_fields = itemgetter(*fieldnames)
with open("PlayTypeKey.csv", "r", newline="") as f_input, \
open(os.path.expanduser("BasketballPlayTypeData.csv"), "w", newline="") as f_output:
csv_input = csv.reader(f_input)
next(csv_input)
csv_output = csv.writer(f_output)
csv_output.writerow(fieldnames)
for play_type, season, mode, off_def in csv_input:
url = f"http://stats-prod.nba.com/wp-json/statscms/v1/synergy/player/?category={play_type}&limit=500&names={off_def}&season={season}&seasonType=Reg"
print(url)
json_data = urllib.request.urlopen(url).read()
data = json.loads(json_data)
for player in data['results']:
row = [season, play_type] + list(req_fields(player))
csv_output.writerow(row)
如果您要打印json_data，则将看到每个玩家可用的所有可能数据。我已经展示了如何提取前几列。 itemgetter()用作从每个玩家条目中提取所需位的快捷方式。
此脚本将为您提供一个输出CSV文件，开始于：
PlayerFirstName,PlayerLastName,TeamNameAbbreviation,GP,Poss
2015,isolation,Aaron,Gordon,ORL,78,30
2015,isolation,Norman,Powell,TOR,49,9
2015,isolation,Al,Jefferson,CHA,47,9
您显然可以修改输出，使其与您的其他站点相同。这种方法的最大优势在于，您只需一次调用即可获得所有播放器数据，而无需循环浏览多个页面。