加載csv并將每個值傳遞給url引數？

我正在嘗試從 nba.com 匯總 NBA 球員資料。我有一個 csv 中的玩家 ID 串列。我想加載每個玩家 ID 并將其傳遞到引數串列中。然后在requests.get 中使用引數串列。當我直接輸入玩家 ID 作為引數時，request.get 起作用。對 csv 回圈通過該函式的測驗似乎有效。但是，我無法成功將 playerids 傳遞到引數串列中。我試過查看類似的 nba python 代碼，但看不出我哪里出錯了。

'''

import pandas as pd
import requests
import csv

best_db=pd.DataFrame()


def table_Scrape():
    
    global best_db 
    
    with open("SHORT_ID_plyr.csv", "r") as f_urls: 
        f_urls_list = csv.reader(f_urls, delimiter=',') 
        next(f_urls_list)    
        
        ##step5. open 1st url from .csv
        for lines in f_urls_list:        
            u = lines[0]
            print(u) #<loop test
            # import requests
            player_id = u
            
            url = """
            http://stats.nba.com/stats/playergamelogs?DateFrom=&DateTo=&GameSegment=&LastNGames=0&LeagueID=00&Location=&MeasureType=Base&Month=0&OpponentTeamID=0&Outcome=&PORound=0&PaceAdjust=N&PerMode=Totals&Period=0&PlayerID=203932&PlusMinus=N&Rank=N&Season=2021-22&SeasonSegment=&SeasonType=Regular Season&ShotClockRange=&VsConference=&VsDivision=
            """
                #url = """
                #https://stats.nba.com/stats/leaguedashplayerstats?College=&Conference=&Country=&DateFrom=&DateTo=&Division=&DraftPick=&DraftYear=&GameScope=&GameSegment=&Height=&LastNGames=0&LeagueID=00&Location=&MeasureType=Base&Month=0&OpponentTeamID=0&Outcome=&PORound=0&PaceAdjust=N&PerMode=Totals&Period=0&PlayerExperience=&PlayerPosition=&PlusMinus=N&Rank=N&Season=2021-22&SeasonSegment=&SeasonType=Regular Season&ShotClockRange=&StarterBench=&TeamID=0&TwoWay=0&VsConference=&VsDivision=&Weight=
                #"""
            header_dict = {
                'User-Agent': 'Mozilla/5.0',
                'x-nba-stats-origin': 'stats',
                'x-nba-stats-token': 'true',
                'Referer': 'https://stats.nba.com',
                'Connection': 'keep-alive',
                'Pragma': 'no-cache',
                'Cache-Control': 'no-cache',
                'Host': 'stats.nba.com'
            }

            params = {
                'LastNGames': '0',
                'LeagueID': '00',
                'MeasureType': 'Base',
                'Month': '0',
                'OpponentTeamID': '0',
                'PORound': '0',
                'PaceAdjust': 'N',
                'PerMode': 'Totals',
                'Period': '0',
                'PlayerID': u,
                'PlusMinus': 'N',
                'Rank': 'N',
                'Season': '2021-22',
                'SeasonType': 'Regular Season'
                }

            res = requests.get(url, headers=header_dict, params=params)
            json_set = res.json()
            headers = json_set['resultSets'][0]['headers']
            data_set = json_set['resultSets'][0]['rowSet']
            df = pd.DataFrame(columns=headers)
            df.head #test the dataframe NOTE: does not appear to be working either
            
table_Scrape() #call the function

uj5u.com熱心網友回復：

您正在將有效負載傳遞到已經具有硬編碼播放器 ID 的有效負載的 url。將 palyer_id 變數放入 url

import pandas as pd
import requests


best_db=pd.DataFrame()


def table_Scrape():
    
    df = pd.read_csv('SHORT_ID_plyr.csv')
    player_id_list = list(df['PLAYER_ID'])
        
    for player_id in player_id_list:
        print(player_id)
        url = f"""http://stats.nba.com/stats/playergamelogs?DateFrom=&DateTo=&GameSegment=&LastNGames=0&LeagueID=00&Location=&MeasureType=Base&Month=0&OpponentTeamID=0&Outcome=&PORound=0&PaceAdjust=N&PerMode=Totals&Period=0&PlayerID={player_id}&PlusMinus=N&Rank=N&Season=2021-22&SeasonSegment=&SeasonType=Regular Season&ShotClockRange=&VsConference=&VsDivision="""

        header_dict = {
            'User-Agent': 'Mozilla/5.0',
            'x-nba-stats-origin': 'stats',
            'x-nba-stats-token': 'true',
            'Referer': 'https://stats.nba.com',
            'Connection': 'keep-alive',
            'Pragma': 'no-cache',
            'Cache-Control': 'no-cache',
            'Host': 'stats.nba.com'
        }

        res = requests.get(url, headers=header_dict)
        print(res.text)
        json_set = res.json()
        headers = json_set['resultSets'][0]['headers']
        data_set = json_set['resultSets'][0]['rowSet']
        df = pd.DataFrame(data_set,columns=headers)
        print(df.head()) #test the dataframe NOTE: does not appear to be working either
            
table_Scrape() #call the function

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