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update score cron job

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This commit is contained in:
MuslemRahimi 2024-10-09 19:16:43 +02:00
parent 3f99870301
commit 401279d35e
1 changed files with 19 additions and 5 deletions
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24
app/cron_ai_score.py
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@ -28,6 +28,16 @@ async def save_json(symbol, data):
with open(f"json/ai-score/companies/{symbol}.json", 'wb') as file: with open(f"json/ai-score/companies/{symbol}.json", 'wb') as file:
file.write(orjson.dumps(data)) file.write(orjson.dumps(data))
# Function to delete all files in a directory
def delete_files_in_directory(directory):
for filename in os.listdir(directory):
file_path = os.path.join(directory, filename)
try:
if os.path.isfile(file_path):
os.remove(file_path)
except Exception as e:
print(f"Failed to delete {file_path}. Reason: {e}")
async def fetch_historical_price(ticker): async def fetch_historical_price(ticker):
url = f"https://financialmodelingprep.com/api/v3/historical-price-full/{ticker}?from=1995-10-10&apikey={api_key}" url = f"https://financialmodelingprep.com/api/v3/historical-price-full/{ticker}?from=1995-10-10&apikey={api_key}"
async with aiohttp.ClientSession() as session: async with aiohttp.ClientSession() as session:
@ -311,9 +321,12 @@ async def fine_tune_and_evaluate(ticker, con, start_date, end_date, skip_downloa
gc.collect() # Force the garbage collector to release unreferenced memory gc.collect() # Force the garbage collector to release unreferenced memory
async def run(): async def run():
train_mode = False # Set this to False for fine-tuning and evaluation train_mode = True # Set this to False for fine-tuning and evaluation
skip_downloading = False skip_downloading = False
save_data = True save_data = True
delete_data = True
if delete_data:
delete_files_in_directory("ml_models/training_data/ai-score")
con = sqlite3.connect('stocks.db') con = sqlite3.connect('stocks.db')
cursor = con.cursor() cursor = con.cursor()
@ -325,10 +338,11 @@ async def run():
stock_symbols = [row[0] for row in cursor.fetchall()] stock_symbols = [row[0] for row in cursor.fetchall()]
print('Training for:', stock_symbols) print('Training for:', stock_symbols)
predictor = await warm_start_training(stock_symbols, con, skip_downloading, save_data) predictor = await warm_start_training(stock_symbols, con, skip_downloading, save_data)
else:
# Fine-tuning and evaluation for all stocks #else:
cursor.execute("SELECT DISTINCT symbol FROM stocks WHERE marketCap >= 500E6 AND symbol NOT LIKE '%.%'") # Evaluation for all stocks
stock_symbols = [row[0] for row in cursor.fetchall()] #cursor.execute("SELECT DISTINCT symbol FROM stocks WHERE marketCap >= 500E6 AND symbol NOT LIKE '%.%'")
#stock_symbols = [row[0] for row in cursor.fetchall()]
print(f"Total tickers for fine-tuning: {len(stock_symbols)}") print(f"Total tickers for fine-tuning: {len(stock_symbols)}")
start_date = datetime(1995, 1, 1).strftime("%Y-%m-%d") start_date = datetime(1995, 1, 1).strftime("%Y-%m-%d")