Files
nbaStats/nba_data/nba_scraper_advanced.py
T

109 lines
3.6 KiB
Python

import os
import sys
import django
import requests
from bs4 import BeautifulSoup
import csv
import json
import time
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'nba_stats.settings')
django.setup()
from nba_data.models import PlayerAdvancedData
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']
team_abbreviations = ['ATL', 'BOS', 'BRK', 'CHI', 'CHO', 'CLE', 'DAL', 'DEN', 'DET', 'GSW', 'HOU', 'IND', 'LAC', 'LAL', 'MEM', 'MIA', 'MIL', 'MIN', 'NOP', 'NYK', 'OKC', 'ORL', 'PHI', 'PHO', 'POR', 'SAC', 'SAS', 'TOR', 'UTA', 'WAS']
# team = input('What team? ')
# OMIT above. Will now only ask for season and iterate thru teams list.
season = input('What season? ')
for team in teams:
url_make = 'https://www.basketball-reference.com/teams/' + team + '/' + season + '.html'
response = requests.get(url_make)
soup = BeautifulSoup(response.text, "html.parser")
table = soup.find("table", {"id": "advanced"})
if table is None:
print(f"Table not found for team {team} and season {season}.")
# sys.exit(1)
continue
header_row = table.find("thead").find("tr")
rows = table.find("tbody").find_all("tr")
# Extract coloumn headers
headers = [col.text.strip() for col in header_row.find_all("th")][1:]
headers.extend(['team', 'season']) # Add 'team' and 'season' fields to headers
# Extract rows as dictionaries
data = []
for row in rows:
cols = row.find_all("td")
cols = [col.text.strip() for col in cols]
row_dict = {header: (None if col == "" else col) for header, col in zip(headers, cols)}
row_dict['team'] = team
row_dict['season'] = season
data.append(row_dict)
# locate current directory
script_dir = os.path.dirname(os.path.abspath(__file__))
# save as CSV file
csv_output_path = os.path.join(script_dir, '..', 'data', f'{team}_{season}_advanced_output.csv')
with open(csv_output_path, "w", newline="") as csvfile:
writer = csv.DictWriter(csvfile, fieldnames=headers)
writer.writeheader()
for row in data:
writer.writerow(row)
# Save as JSON
json_output_path = os.path.join(script_dir, '..', 'data', f'{team}_{season}_advanced_output.json')
with open(json_output_path, 'w') as jsonfile:
json.dump(data, jsonfile)
# # save data to database
# for row in data:
# player_data = PlayerData(
# name=row['Player'],
# age=row['Age'],
# games=row['G'],
# games_started=row['GS'],
# minutes_pg=row['MP'],
# field_goals=row['FG'],
# field_attempts=row['FGA'],
# field_percent=row['FG%'],
# three_fg=row['3P'],
# three_attempts=row['3PA'],
# three_percent=row['3P%'],
# two_fg=row['2P'],
# two_attempts=row['2PA'],
# two_percent=row['2P%'],
# effect_fg_percent=row['eFG%'],
# ft=row['FT'],
# fta=row['FTA'],
# ft_percent=row['FT%'],
# ORB=row['ORB'],
# DRB=row['DRB'],
# TRB=row['TRB'],
# AST=row['AST'],
# STL=row['STL'],
# BLK=row['BLK'],
# TOV=row['TOV'],
# PF=row['PF'],
# PTS=row['PTS'],
# team=row['team'],
# season=row['season'],
# )
# player_data.save()