mirror of
https://github.com/nprasad2077/nbaStats.git
synced 2026-11-04 09:15:35 +00:00
104 lines
3.3 KiB
Python
104 lines
3.3 KiB
Python
import os
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import sys
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import django
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import requests
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from bs4 import BeautifulSoup, Comment
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import csv
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import json
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import time
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import re
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sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'nba_stats.settings')
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django.setup()
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from nba_data.models import PlayerSalaryData
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# Change CHO to CHA 2014 and prior.
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# Change NOP to NOH for 2013 and prior.
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# Change OKC to SEA for 2008 and prior.
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# Change NOH to NOK for 2007 and 2006
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# Change NOK to NOH for 2005 and prior.
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# Change NOH to CHH for 2002 and prior. NOLA did not have a team before 2003.
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# Change WAS to WSB for 1997 and prior.
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# Change BRK to NJN for 2012 and prior.
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# Change MEM to VAN for 2001 and prior.
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# Change LAC to SDC for 1984 and prior.
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teams = ['HOU' ,'PHI', 'BOS', 'NYK', 'BRK', 'TOR', 'MEM', 'NOP', 'DAL', 'SAS', 'DEN', 'MIN', 'OKC', 'UTA', 'POR', 'MIL', 'CLE', 'CHI', 'IND', 'DET', 'SAC', 'PHO', 'GSW', 'LAC', 'LAL', 'MIA', 'ATL', 'WAS', 'ORL', 'CHO']
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teams_test = ['HOU', 'PHI', 'BOS']
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season = input('What season? ')
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for team in teams:
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url_make = 'https://www.basketball-reference.com/teams/' + team + '/' + season + '.html'
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response = requests.get(url_make)
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soup = BeautifulSoup(response.text, "html.parser")
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comment = soup.find(string=lambda text: isinstance(text, Comment) and "salaries2" in text)
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table_soup = BeautifulSoup(comment, "html.parser")
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table = table_soup.find("table", {'class': 'suppress_all stats_table', 'id': 'salaries2'})
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if table is None:
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print(f"Table not found for team {team} and season {season}.")
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# sys.exit(1)
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continue
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header_row = table.find("thead").find("tr")
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rows = table.find("tbody").find_all("tr")
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# Extract coloumn headers
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headers = ['player_name']
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headers.extend([col.text.strip() for col in header_row.find_all("th")][2:])
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headers.extend(['team', 'season']) # Add 'team' and 'season' fields to headers
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# Extract rows as dictionaries
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data = []
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for row in rows:
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cols = row.find_all("td")
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cols = [col.text.strip() for col in cols]
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row_dict = {header: (None if col == "" else col) for header, col in zip(headers, cols)}
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row_dict['team'] = team
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row_dict['season'] = season
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data.append(row_dict)
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# locate current directory
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script_dir = os.path.dirname(os.path.abspath(__file__))
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# save as CSV file
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csv_output_path = os.path.join(script_dir, '..', 'data', f'{team}_{season}_player_salary_output.csv')
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with open(csv_output_path, "w", newline="") as csvfile:
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writer = csv.DictWriter(csvfile, fieldnames=headers)
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writer.writeheader()
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for row in data:
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writer.writerow(row)
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# Save as JSON
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json_output_path = os.path.join(script_dir, '..', 'data', f'{team}_{season}_player_salary_output.json')
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with open(json_output_path, 'w') as jsonfile:
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json.dump(data, jsonfile)
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# save data to database
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for row in data:
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row['Salary'] = int(row['Salary'].replace(',', '').replace('$', '')) if row['Salary'] else None
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player_data = PlayerSalaryData(
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player_name = row['player_name'],
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salary = row['Salary'],
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team = row['team'],
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season = row['season'],
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)
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player_data.save()
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print('success')
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