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Update download-trade.py #344

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203 changes: 113 additions & 90 deletions python/download-trade.py
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Original file line number Diff line number Diff line change
@@ -1,114 +1,137 @@
#!/usr/bin/env python
#!/usr/bin/env python3

"""
script to download trades.
set the absoluate path destination folder for STORE_DIRECTORY, and run

e.g. STORE_DIRECTORY=/data/ ./download-trade.py

Enhanced script to download trades.
Set the absolute path destination folder for STORE_DIRECTORY, and run

e.g. STORE_DIRECTORY=/data/ ./download-trade.py

New features:
- Multithreading for faster downloads
- Progress bar for better visibility
- Improved error handling and logging
- Rate limiting to avoid overwhelming the server
- Automatic retries for failed downloads
- CSV export option for downloaded data summary
"""

import sys
from datetime import *
import os
from datetime import datetime, timedelta
import pandas as pd
from concurrent.futures import ThreadPoolExecutor, as_completed
import requests
from requests.exceptions import RequestException
from tqdm import tqdm
import time
import logging
import csv
from enums import *
from utility import download_file, get_all_symbols, get_parser, get_start_end_date_objects, convert_to_date_object, \
get_path

from utility import download_file, get_all_symbols, get_parser, get_start_end_date_objects, convert_to_date_object, get_path

# Configure logging
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)

# Constants
MAX_RETRIES = 3
RATE_LIMIT = 0.5 # seconds between requests

def download_with_retry(path, file_name, date_range, folder, max_retries=MAX_RETRIES):
for attempt in range(max_retries):
try:
download_file(path, file_name, date_range, folder)
time.sleep(RATE_LIMIT) # Rate limiting
return True
except RequestException as e:
logger.warning(f"Attempt {attempt + 1} failed: {e}")
if attempt == max_retries - 1:
logger.error(f"Failed to download {file_name} after {max_retries} attempts")
return False
time.sleep(2 ** attempt) # Exponential backoff

def download_monthly_trades(trading_type, symbols, num_symbols, years, months, start_date, end_date, folder, checksum):
current = 0
date_range = None

if start_date and end_date:
date_range = start_date + " " + end_date

if not start_date:
start_date = START_DATE
else:
start_date = convert_to_date_object(start_date)

if not end_date:
end_date = END_DATE
else:
end_date = convert_to_date_object(end_date)

print("Found {} symbols".format(num_symbols))

for symbol in symbols:
print("[{}/{}] - start download monthly {} trades ".format(current+1, num_symbols, symbol))
for year in years:
for month in months:
current_date = convert_to_date_object('{}-{}-01'.format(year, month))
if current_date >= start_date and current_date <= end_date:
path = get_path(trading_type, "trades", "monthly", symbol)
file_name = "{}-trades-{}-{}.zip".format(symbol.upper(), year, '{:02d}'.format(month))
download_file(path, file_name, date_range, folder)

if checksum == 1:
checksum_path = get_path(trading_type, "trades", "monthly", symbol)
checksum_file_name = "{}-trades-{}-{}.zip.CHECKSUM".format(symbol.upper(), year, '{:02d}'.format(month))
download_file(checksum_path, checksum_file_name, date_range, folder)
tasks = []

current += 1
with ThreadPoolExecutor(max_workers=10) as executor:
for symbol in symbols:
for year in years:
for month in months:
current_date = convert_to_date_object(f'{year}-{month}-01')
if start_date <= current_date <= end_date:
path = get_path(trading_type, "trades", "monthly", symbol)
file_name = f"{symbol.upper()}-trades-{year}-{month:02d}.zip"
tasks.append(executor.submit(download_with_retry, path, file_name, f"{start_date} {end_date}", folder))

if checksum:
checksum_path = get_path(trading_type, "trades", "monthly", symbol)
checksum_file_name = f"{file_name}.CHECKSUM"
tasks.append(executor.submit(download_with_retry, checksum_path, checksum_file_name, f"{start_date} {end_date}", folder))

return [task.result() for task in tqdm(as_completed(tasks), total=len(tasks), desc="Downloading monthly trades")]

def download_daily_trades(trading_type, symbols, num_symbols, dates, start_date, end_date, folder, checksum):
current = 0
date_range = None

if start_date and end_date:
date_range = start_date + " " + end_date

if not start_date:
start_date = START_DATE
else:
start_date = convert_to_date_object(start_date)

if not end_date:
end_date = END_DATE
else:
end_date = convert_to_date_object(end_date)
tasks = []

print("Found {} symbols".format(num_symbols))

for symbol in symbols:
print("[{}/{}] - start download daily {} trades ".format(current+1, num_symbols, symbol))
for date in dates:
current_date = convert_to_date_object(date)
if current_date >= start_date and current_date <= end_date:
path = get_path(trading_type, "trades", "daily", symbol)
file_name = "{}-trades-{}.zip".format(symbol.upper(), date)
download_file(path, file_name, date_range, folder)

if checksum == 1:
checksum_path = get_path(trading_type, "trades", "daily", symbol)
checksum_file_name = "{}-trades-{}.zip.CHECKSUM".format(symbol.upper(), date)
download_file(checksum_path, checksum_file_name, date_range, folder)

current += 1
with ThreadPoolExecutor(max_workers=10) as executor:
for symbol in symbols:
for date in dates:
current_date = convert_to_date_object(date)
if start_date <= current_date <= end_date:
path = get_path(trading_type, "trades", "daily", symbol)
file_name = f"{symbol.upper()}-trades-{date}.zip"
tasks.append(executor.submit(download_with_retry, path, file_name, f"{start_date} {end_date}", folder))

if checksum:
checksum_path = get_path(trading_type, "trades", "daily", symbol)
checksum_file_name = f"{file_name}.CHECKSUM"
tasks.append(executor.submit(download_with_retry, checksum_path, checksum_file_name, f"{start_date} {end_date}", folder))

return [task.result() for task in tqdm(as_completed(tasks), total=len(tasks), desc="Downloading daily trades")]

def export_summary(symbols, start_date, end_date, monthly_results, daily_results):
summary_file = "download_summary.csv"
with open(summary_file, 'w', newline='') as csvfile:
writer = csv.writer(csvfile)
writer.writerow(["Symbol", "Start Date", "End Date", "Monthly Downloads", "Daily Downloads", "Total Downloads"])

for symbol in symbols:
monthly_count = sum(1 for result in monthly_results if result)
daily_count = sum(1 for result in daily_results if result)
total_count = monthly_count + daily_count
writer.writerow([symbol, start_date, end_date, monthly_count, daily_count, total_count])

logger.info(f"Download summary exported to {summary_file}")

if __name__ == "__main__":
parser = get_parser('trades')
args = parser.parse_args(sys.argv[1:])

if not args.symbols:
print("fetching all symbols from exchange")
symbols = get_all_symbols(args.type)
num_symbols = len(symbols)
logger.info("Fetching all symbols from exchange")
symbols = get_all_symbols(args.type)
num_symbols = len(symbols)
else:
symbols = args.symbols
num_symbols = len(symbols)
print("fetching {} symbols from exchange".format(num_symbols))
symbols = args.symbols
num_symbols = len(symbols)
logger.info(f"Fetching {num_symbols} symbols from exchange")

start_date, end_date = get_start_end_date_objects(args.startDate, args.endDate)

if args.dates:
dates = args.dates
dates = args.dates
else:
period = convert_to_date_object(datetime.today().strftime('%Y-%m-%d')) - convert_to_date_object(
PERIOD_START_DATE)
dates = pd.date_range(end=datetime.today(), periods=period.days + 1).to_pydatetime().tolist()
dates = [date.strftime("%Y-%m-%d") for date in dates]
if args.skip_monthly == 0:
download_monthly_trades(args.type, symbols, num_symbols, args.years, args.months, args.startDate, args.endDate, args.folder, args.checksum)
dates = pd.date_range(start=start_date, end=end_date).strftime("%Y-%m-%d").tolist()

monthly_results = []
daily_results = []

if args.skip_monthly == 0:
monthly_results = download_monthly_trades(args.type, symbols, num_symbols, args.years, args.months, start_date, end_date, args.folder, args.checksum)

if args.skip_daily == 0:
download_daily_trades(args.type, symbols, num_symbols, dates, args.startDate, args.endDate, args.folder, args.checksum)

daily_results = download_daily_trades(args.type, symbols, num_symbols, dates, start_date, end_date, args.folder, args.checksum)

export_summary(symbols, start_date.strftime("%Y-%m-%d"), end_date.strftime("%Y-%m-%d"), monthly_results, daily_results)

logger.info("Download completed successfully!")