0a17745389
Standardize formatting with black and apply ruff auto-fixes. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
141 lines
3.7 KiB
Python
141 lines
3.7 KiB
Python
from selenium import webdriver
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from selenium.webdriver.common.by import By
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from selenium.webdriver.support.ui import WebDriverWait
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from selenium.webdriver.support import expected_conditions as EC
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import pandas as pd
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import time
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def get_fangraphs_splits_data():
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"""
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Extract all 8 chunks of baseball splits data from FanGraphs
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"""
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# Initialize Chrome driver
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driver = webdriver.Chrome()
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# Base parameters
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base_params = {
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"autoPt": "false",
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"splitTeams": "false",
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"statType": "player",
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"startDate": "2025-03-01",
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"endDate": "2025-11-01",
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"players": "",
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"filter": "",
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"groupBy": "season",
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"sort": "22,1",
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}
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# Define the 8 configurations
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configs = [
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{
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"name": "Batting_vLHP_Standard",
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"position": "B",
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"splitArr": "1",
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"statgroup": "1",
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},
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{
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"name": "Batting_vLHP_BattedBalls",
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"position": "B",
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"splitArr": "1",
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"statgroup": "3",
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},
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{
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"name": "Batting_vRHP_Standard",
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"position": "B",
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"splitArr": "2",
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"statgroup": "1",
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},
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{
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"name": "Batting_vRHP_BattedBalls",
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"position": "B",
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"splitArr": "2",
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"statgroup": "3",
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},
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{
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"name": "Pitching_vLHH_Standard",
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"position": "P",
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"splitArr": "5",
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"statgroup": "1",
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},
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{
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"name": "Pitching_vLHH_BattedBalls",
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"position": "P",
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"splitArr": "5",
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"statgroup": "3",
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},
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{
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"name": "Pitching_vRHH_Standard",
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"position": "P",
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"splitArr": "6",
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"statgroup": "1",
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},
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{
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"name": "Pitching_vRHH_BattedBalls",
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"position": "P",
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"splitArr": "6",
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"statgroup": "3",
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},
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]
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all_data = {}
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try:
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for config in configs:
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print(f"Fetching {config['name']}...")
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# Build URL
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url_params = {
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**base_params,
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"position": config["position"],
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"splitArr": config["splitArr"],
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"statgroup": config["statgroup"],
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}
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param_string = "&".join([f"{k}={v}" for k, v in url_params.items()])
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url = (
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f"https://www.fangraphs.com/leaders/splits-leaderboards?{param_string}"
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)
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# Navigate to URL
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driver.get(url)
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# Wait for table to load (wait for table element)
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wait = WebDriverWait(driver, 10)
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table = wait.until(EC.presence_of_element_located((By.TAG_NAME, "table")))
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# Additional wait for data to populate
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time.sleep(2)
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# Extract table using pandas
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tables = pd.read_html(driver.page_source)
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if tables:
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# The main data table is typically the largest one
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df = max(tables, key=lambda x: len(x))
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all_data[config["name"]] = df
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print(f" ✓ Got {len(df)} rows")
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else:
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print(" ✗ No tables found")
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return all_data
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finally:
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driver.quit()
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# Usage
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if __name__ == "__main__":
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data = get_fangraphs_splits_data()
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# Save to CSV files
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for name, df in data.items():
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df.to_csv(f"{name}.csv", index=False)
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print(f"Saved {name}.csv")
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# Or work with the dataframes directly
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# Example: print first few rows of batting vs LHP
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print("\\nBatting vs LHP (Standard) - First 5 rows:")
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print(data["Batting_vLHP_Standard"].head())
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