0

I will apologize now as I am sure the format of my question and the information I provide will not be up to par with what is expected on this site. I have been coding SQL and VBA for several years and I am trying to pick up a 3rd language to enhance my skill set. I will get better with time.

Now to my issue...

I am trying to scrape a series of tables with code that has worked on BasketballReference.com however on NBA.com the code brings back nothing. When digging further the make_soup does not contain the tr and td tags that I see when inspecting the table in my browser. Below is the code I am using and for reference a picture of what my csv file looks like.

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 data:

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

My limited ability to trouble shoot tells me that the table data is not coming back when I make the soup out of the URL. When printing the text of the soup I get this...

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{{ ::item.city }} {{ ::item.name }}
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Towards the bottom of what is pasted above are the headers of the table but no corresponding text or code for the table itself. I won't clutter this post with what I get when printing the HTML but I get no hits when searching for the tr or td tags.

Thanks in advance for anyone that spends time looking into this and I just want to say this site has already been immensely valuable to me.

4

1 回答 1

0

该网页不包含任何带有TR和的表格TD。它由页面显示,首先通过单独的调用请求所有数据,然后使用 Javascript 呈现。通常,您需要使用 selenium 之类的东西来完成此操作,但更快的方法是使用浏览器监控网络请求并使用 Python 重新创建它们。

在这种情况下,请求导致所有数据都以 JSON 格式返回,这比需要 BeautifulSoup 更容​​易解析。只需使用 Python 的 JSON 库加载它,您就可以将所有玩家数据作为一个大的 Python 数据结构。

读取 CSV 文件时,一次使用一行信息会更容易,而不是尝试构建多个列表,然后在单独的循环中对它们进行索引。

您需要的 JSON 请求与您尝试获取的 HTML 页面的参数稍有不同(如在浏览器中监控网络活动所见),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,您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:

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以使其与您的其他站点相同。这种方法的一大优势是您将在一次调用中获取所有玩家数据,无需循环浏览多个页面。

于 2018-08-29T17:20:31.713 回答