139 lines
5.1 KiB
Python
139 lines
5.1 KiB
Python
from datetime import datetime, timedelta
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import ujson
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import sqlite3
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import asyncio
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import aiohttp
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from tqdm import tqdm
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import os
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from dotenv import load_dotenv
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from aiohttp import TCPConnector
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load_dotenv()
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api_key = os.getenv('FMP_API_KEY')
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def date_range_days(steps=20):
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end_date = datetime.utcnow()
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start_date = end_date - timedelta(days=180) # 6 months ago
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while start_date < end_date:
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next_date = start_date + timedelta(days=steps)
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yield start_date.strftime("%Y-%m-%d"), min(next_date, end_date).strftime("%Y-%m-%d")
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start_date = next_date
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async def get_data_batch(session, symbol, url_list):
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tasks = []
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for url in url_list:
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tasks.append(fetch_data(session, url))
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results = await asyncio.gather(*tasks)
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data = []
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for result in results:
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if result:
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data.extend(result)
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return data
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def get_existing_data(symbol, interval):
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file_path = f"json/export/price/{interval}/{symbol}.json"
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if os.path.exists(file_path):
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with open(file_path, 'r') as file:
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return ujson.load(file)
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return []
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def get_missing_date_ranges(existing_data, start_date, end_date):
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existing_dates = {item['date'].split()[0] for item in existing_data} # Use a set for O(1) lookup time
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start_date = datetime.strptime(start_date, "%Y-%m-%d")
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end_date = datetime.strptime(end_date, "%Y-%m-%d")
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missing_ranges = []
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current_date = start_date
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range_start = None
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while current_date <= end_date:
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date_str = current_date.strftime("%Y-%m-%d")
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if date_str not in existing_dates:
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if range_start is None:
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range_start = current_date
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else:
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# If we found an existing date, and we have a start for a missing range, add it
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if range_start:
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missing_ranges.append((range_start.strftime("%Y-%m-%d"), date_str))
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range_start = None
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current_date += timedelta(days=1)
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# If the loop ends and we still have an open range, add it
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if range_start:
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missing_ranges.append((range_start.strftime("%Y-%m-%d"), end_date.strftime("%Y-%m-%d")))
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return missing_ranges
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async def fetch_data(session, url):
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try:
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async with session.get(url) as response:
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if response.status == 200:
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return await response.json()
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else:
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return []
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except Exception as e:
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print(f"Error fetching data from {url}: {e}")
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return []
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async def get_data(session, symbol, time_period):
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steps = 20 if time_period == '30min' else 40
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existing_data = get_existing_data(symbol, time_period)
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res_list = existing_data
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urls_to_fetch = []
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for start_date, end_date in date_range_days(steps=steps):
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missing_ranges = get_missing_date_ranges(existing_data, start_date, end_date)
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for missing_start, missing_end in missing_ranges:
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url = f"https://financialmodelingprep.com/api/v3/historical-chart/{time_period}/{symbol}?serietype=bar&extend=false&from={missing_start}&to={missing_end}&apikey={api_key}"
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urls_to_fetch.append(url)
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if urls_to_fetch:
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fetched_data = await get_data_batch(session, symbol, urls_to_fetch)
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res_list.extend(fetched_data)
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if res_list:
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current_datetime = datetime.utcnow()
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filtered_data = {item['date']: item for item in res_list if datetime.strptime(item['date'], "%Y-%m-%d %H:%M:%S") <= current_datetime}
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sorted_data = sorted(filtered_data.values(), key=lambda x: x['date'], reverse=False)
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await save_json(symbol, sorted_data, time_period)
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async def save_json(symbol, data, interval):
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os.makedirs(f"json/export/price/{interval}", exist_ok=True)
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with open(f"json/export/price/{interval}/{symbol}.json", 'w') as file:
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ujson.dump(data, file)
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async def process_symbol(session, symbol):
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# Process both 30min and 60min intervals
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await get_data(session, symbol, '30min')
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await get_data(session, symbol, '1hour')
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async def run():
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con = sqlite3.connect('stocks.db')
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cursor = con.cursor()
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cursor.execute("PRAGMA journal_mode = wal")
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cursor.execute("SELECT DISTINCT symbol FROM stocks")
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stock_symbols = [row[0] for row in cursor.fetchall()]
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etf_con = sqlite3.connect('etf.db')
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etf_cursor = etf_con.cursor()
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etf_cursor.execute("SELECT DISTINCT symbol FROM etfs")
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etf_symbols = [row[0] for row in etf_cursor.fetchall()]
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con.close()
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etf_con.close()
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total_symbols = stock_symbols + etf_symbols
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# Use aiohttp connector with a higher limit for performance
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connector = TCPConnector(limit=100)
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async with aiohttp.ClientSession(connector=connector) as session:
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for i, symbol in enumerate(tqdm(total_symbols), 1):
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await process_symbol(session, symbol)
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if i % 100 == 0:
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print(f'Sleeping after processing {i} symbols')
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await asyncio.sleep(60)
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if __name__ == "__main__":
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asyncio.run(run())
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