286 lines
10 KiB
Python
Executable File
286 lines
10 KiB
Python
Executable File
from datetime import date, datetime, timedelta, time
|
|
import ujson
|
|
import orjson
|
|
import sqlite3
|
|
import pandas as pd
|
|
import asyncio
|
|
import aiohttp
|
|
import pytz
|
|
from utils.helper import check_market_hours
|
|
|
|
from GetStartEndDate import GetStartEndDate
|
|
|
|
#Update Market Movers Price, ChangesPercentage, Volume and MarketCap regularly
|
|
berlin_tz = pytz.timezone('Europe/Berlin')
|
|
|
|
from dotenv import load_dotenv
|
|
import os
|
|
load_dotenv()
|
|
api_key = os.getenv('FMP_API_KEY')
|
|
|
|
|
|
market_cap_threshold = 10E9
|
|
volume_threshold = 50_000
|
|
price_threshold = 10
|
|
|
|
def check_market_hours():
|
|
|
|
holidays = ['2025-01-01', '2025-01-09','2025-01-20', '2025-02-17', '2025-04-18', '2025-05-26', '2025-06-19', '2025-07-04', '2025-09-01', '2025-11-27', '2025-12-25']
|
|
|
|
# Get the current date and time in ET (Eastern Time)
|
|
et_timezone = pytz.timezone('America/New_York')
|
|
current_time = datetime.now(et_timezone)
|
|
current_date_str = current_time.strftime('%Y-%m-%d')
|
|
current_hour = current_time.hour
|
|
current_minute = current_time.minute
|
|
current_day = current_time.weekday() # Monday is 0, Sunday is 6
|
|
|
|
# Check if the current date is a holiday or weekend
|
|
is_weekend = current_day >= 5 # Saturday (5) or Sunday (6)
|
|
is_holiday = current_date_str in holidays
|
|
|
|
# Determine the market status
|
|
if is_weekend or is_holiday:
|
|
return 0 #Closed
|
|
elif current_hour < 9 or (current_hour == 9 and current_minute < 30):
|
|
return 1 # Pre-Market
|
|
elif 9 <= current_hour < 16 or (current_hour == 16 and current_minute == 0):
|
|
return 0 #"Market hours."
|
|
elif 16 <= current_hour < 24:
|
|
return 2 #"After-market hours."
|
|
else:
|
|
return 0 #"Market is closed."
|
|
|
|
market_status = check_market_hours()
|
|
|
|
async def get_quote_of_stocks(ticker_list):
|
|
res_list = []
|
|
for symbol in ticker_list:
|
|
try:
|
|
with open(f"json/quote/{symbol}.json") as file:
|
|
data = orjson.loads(file.read())
|
|
res_list.append(data)
|
|
except:
|
|
pass
|
|
|
|
return res_list
|
|
|
|
def deep_copy(data):
|
|
if isinstance(data, dict):
|
|
return {key: deep_copy(value) for key, value in data.items()}
|
|
elif isinstance(data, list):
|
|
return [deep_copy(item) for item in data]
|
|
else:
|
|
return data # Base case for non-nested elements (e.g., int, float, str)
|
|
|
|
|
|
|
|
async def get_gainer_loser_active_stocks(symbols):
|
|
res_list = []
|
|
|
|
for symbol in symbols:
|
|
try:
|
|
# Load the main quote JSON file
|
|
with open(f"json/quote/{symbol}.json", "r") as file:
|
|
data = orjson.loads(file.read())
|
|
market_cap = int(data.get('marketCap', 0))
|
|
name = data.get('name', None)
|
|
volume = data.get('volume', 0)
|
|
changes_percentage = data.get("changesPercentage", None)
|
|
price = data.get("price", None)
|
|
|
|
# Ensure the stock meets criteria
|
|
if market_cap >= market_cap_threshold and price >= price_threshold:
|
|
if price and changes_percentage:
|
|
res_list.append({
|
|
"symbol": symbol,
|
|
"name": name,
|
|
"price": price,
|
|
"volume": volume,
|
|
"changesPercentage": changes_percentage,
|
|
"marketCap": market_cap
|
|
})
|
|
except Exception as e:
|
|
print(f"Error processing symbol {symbol}: {e}")
|
|
continue
|
|
|
|
# Load past market movers data
|
|
query_market_movers = """
|
|
SELECT
|
|
gainer, loser, most_active
|
|
FROM
|
|
market_movers
|
|
"""
|
|
past_gainer = pd.read_sql_query(query_market_movers, con)
|
|
gainer_json = eval(past_gainer['gainer'].iloc[0])
|
|
loser_json = eval(past_gainer['loser'].iloc[0])
|
|
active_json = eval(past_gainer['most_active'].iloc[0])
|
|
|
|
# Initialize final data structure
|
|
final_data = {
|
|
'gainers': gainer_json.copy(),
|
|
'losers': loser_json.copy(),
|
|
'active': active_json.copy()
|
|
}
|
|
|
|
# Process current data
|
|
current_data = {
|
|
'gainers': sorted([x for x in res_list if x['changesPercentage'] > 0],
|
|
key=lambda x: x['changesPercentage'],
|
|
reverse=True),
|
|
'losers': sorted([x for x in res_list if x['changesPercentage'] < 0],
|
|
key=lambda x: x['changesPercentage']),
|
|
'active': sorted([x for x in res_list if x['volume'] > 0],
|
|
key=lambda x: x['volume'],
|
|
reverse=True)
|
|
}
|
|
|
|
# Update latest quotes for current data
|
|
unique_symbols = {stock["symbol"] for category in current_data.values() for stock in category}
|
|
latest_quote = await get_quote_of_stocks(list(unique_symbols))
|
|
|
|
# Update market cap and volume with latest data
|
|
for category in current_data.keys():
|
|
for stock in current_data[category]:
|
|
symbol = stock["symbol"]
|
|
quote_stock = next((item for item in latest_quote if item["symbol"] == symbol), None)
|
|
if quote_stock:
|
|
stock['marketCap'] = quote_stock.get('marketCap', stock['marketCap'])
|
|
stock['volume'] = quote_stock.get('volume', stock['volume'])
|
|
|
|
# Add fresh rankings to current data
|
|
for category, stocks in current_data.items():
|
|
# Sort again after updates
|
|
if category == 'gainers':
|
|
stocks.sort(key=lambda x: x['changesPercentage'], reverse=True)
|
|
elif category == 'losers':
|
|
stocks.sort(key=lambda x: x['changesPercentage'])
|
|
elif category == 'active':
|
|
stocks.sort(key=lambda x: x['volume'], reverse=True)
|
|
|
|
# Apply sequential rankings
|
|
for i, stock in enumerate(stocks, 1):
|
|
stock['rank'] = i
|
|
|
|
# Update the 1D data in final_data
|
|
final_data[category]['1D'] = stocks
|
|
|
|
|
|
categories = ['gainers', 'losers','active']
|
|
#super weird bug that is only fixed with deep_copy for the ranking
|
|
for category in categories:
|
|
for period in ['1D', '1W', '1M', '1Y', '3Y', '5Y']:
|
|
for rank, item in enumerate(final_data[category][period], start=1):
|
|
# Create a deep copy of the item to avoid overwriting shared references
|
|
final_data[category][period][rank - 1] = deep_copy(item)
|
|
final_data[category][period][rank - 1]['rank'] = rank
|
|
|
|
|
|
return final_data
|
|
|
|
|
|
|
|
|
|
async def get_pre_after_market_movers(symbols):
|
|
res_list = []
|
|
|
|
# Loop through the symbols and load the corresponding JSON files
|
|
for symbol in symbols:
|
|
try:
|
|
# Load the main quote JSON file
|
|
with open(f"json/quote/{symbol}.json", "r") as file:
|
|
data = orjson.loads(file.read())
|
|
market_cap = int(data.get('marketCap', 0))
|
|
name = data.get('name',None)
|
|
|
|
if market_cap >= market_cap_threshold:
|
|
with open(f"json/pre-post-quote/{symbol}.json", "r") as file:
|
|
pre_post_data = orjson.loads(file.read())
|
|
price = pre_post_data.get("price", None)
|
|
changes_percentage = pre_post_data.get("changesPercentage", None)
|
|
with open(f"json/one-day-price/{symbol}.json", 'rb') as file:
|
|
one_day_price = orjson.loads(file.read())
|
|
# Filter out entries where 'close' is None
|
|
filtered_prices = [price for price in one_day_price if price['close'] is not None]
|
|
|
|
if price and changes_percentage and len(filtered_prices) > 100: #300
|
|
res_list.append({
|
|
"symbol": symbol,
|
|
"name": name,
|
|
"price": price,
|
|
"changesPercentage": changes_percentage
|
|
})
|
|
except:
|
|
pass
|
|
|
|
|
|
gainers = sorted([x for x in res_list if x['changesPercentage'] > 0], key=lambda x: x['changesPercentage'], reverse=True)
|
|
losers = sorted([x for x in res_list if x['changesPercentage'] < 0], key=lambda x: x['changesPercentage'])
|
|
|
|
|
|
for index, item in enumerate(gainers, start=1):
|
|
item['rank'] = index # Add rank field
|
|
for index, item in enumerate(losers, start=1):
|
|
item['rank'] = index # Add rank field
|
|
|
|
data = {'gainers': gainers, 'losers': losers}
|
|
|
|
unique_symbols = set()
|
|
|
|
# Iterate through categories and symbols
|
|
for category in data.keys():
|
|
# Add rank and process symbols
|
|
for index, stock_data in enumerate(data[category], start=1):
|
|
stock_data['rank'] = index # Add rank field
|
|
symbol = stock_data["symbol"]
|
|
unique_symbols.add(symbol)
|
|
|
|
# Convert the set to a list if needed
|
|
unique_symbols_list = list(unique_symbols)
|
|
|
|
# Get the latest quote of all unique symbols and map it back to the original data list to update all values
|
|
latest_quote = await get_quote_of_stocks(unique_symbols_list)
|
|
|
|
# Updating values in the data list based on matching symbols from the quote list
|
|
for category in data.keys():
|
|
for stock_data in data[category]:
|
|
symbol = stock_data["symbol"]
|
|
quote_stock = next((item for item in latest_quote if item["symbol"] == symbol), None)
|
|
if quote_stock:
|
|
stock_data['marketCap'] = quote_stock['marketCap']
|
|
stock_data['volume'] = quote_stock['volume']
|
|
|
|
return data
|
|
|
|
|
|
try:
|
|
con = sqlite3.connect('stocks.db')
|
|
cursor = con.cursor()
|
|
cursor.execute("PRAGMA journal_mode = wal")
|
|
cursor.execute("SELECT DISTINCT symbol FROM stocks WHERE symbol NOT LIKE '%.%'")
|
|
symbols = [row[0] for row in cursor.fetchall()]
|
|
#Filter out tickers
|
|
#symbols = [symbol for symbol in symbols if symbol != "STEC"]
|
|
|
|
|
|
data = asyncio.run(get_gainer_loser_active_stocks(symbols))
|
|
for category in data.keys():
|
|
with open(f"json/market-movers/markethours/{category}.json", 'w') as file:
|
|
file.write(orjson.dumps(data[category]).decode("utf-8"))
|
|
|
|
|
|
|
|
data = asyncio.run(get_pre_after_market_movers(symbols))
|
|
if market_status == 1:
|
|
for category in data.keys():
|
|
with open(f"json/market-movers/premarket/{category}.json", 'w') as file:
|
|
file.write(orjson.dumps(data[category]).decode("utf-8"))
|
|
elif market_status == 2:
|
|
for category in data.keys():
|
|
with open(f"json/market-movers/afterhours/{category}.json", 'w') as file:
|
|
file.write(orjson.dumps(data[category]).decode("utf-8"))
|
|
|
|
|
|
con.close()
|
|
except Exception as e:
|
|
print(e) |