From 50372c9f9bd3c5b23f77e92f4f3670281aa0443b Mon Sep 17 00:00:00 2001 From: MuslemRahimi Date: Sun, 1 Dec 2024 12:46:31 +0100 Subject: [PATCH] add new list --- app/cron_list.py | 50 ++++++++++++++++++++++++++++++++++++++++++++++++ app/main.py | 2 +- 2 files changed, 51 insertions(+), 1 deletion(-) diff --git a/app/cron_list.py b/app/cron_list.py index cfc6259..8db3ce0 100644 --- a/app/cron_list.py +++ b/app/cron_list.py @@ -592,6 +592,55 @@ async def get_most_employees(): file.write(orjson.dumps(res_list)) +async def get_most_ftd_shares(): + with sqlite3.connect('stocks.db') as con: + cursor = con.cursor() + cursor.execute("PRAGMA journal_mode = wal") + cursor.execute("SELECT DISTINCT symbol FROM stocks WHERE symbol NOT LIKE '%.%' AND symbol NOT LIKE '%-%'") + symbols = [row[0] for row in cursor.fetchall()] + + res_list = [] + for symbol in symbols: + try: + # Load quote data from JSON file + relative_ftd = stock_screener_data_dict[symbol].get('relativeFTD',None) + ftd_shares = stock_screener_data_dict[symbol].get('failToDeliver',None) + country = stock_screener_data_dict[symbol].get('country',None) + if relative_ftd > 10 and ftd_shares > 10_000 and country == 'United States': + quote_data = await get_quote_data(symbol) + # Assign price and volume, and check if they meet the penny stock criteria + if quote_data: + price = round(quote_data.get('price',None), 2) + changesPercentage = round(quote_data.get('changesPercentage'), 2) + name = quote_data.get('name') + + # Append stock data to res_list if it meets the criteria + if changesPercentage != 0: + res_list.append({ + 'symbol': symbol, + 'name': name, + 'price': price, + 'changesPercentage': changesPercentage, + 'relativeFTD': relative_ftd, + 'failToDeliver': ftd_shares + }) + except: + pass + + if res_list: + # Sort by market cap in descending order + res_list = sorted(res_list, key=lambda x: x['relativeFTD'], reverse=True)[:100] + + # Assign rank to each stock + for rank, item in enumerate(res_list, start=1): + item['rank'] = rank + + # Write the filtered and ranked penny stocks to a JSON file + with open("json/stocks-list/list/most-ftd-shares.json", 'wb') as file: + file.write(orjson.dumps(res_list)) + + + async def etf_bitcoin_list(): try: with sqlite3.connect('etf.db') as etf_con: @@ -824,6 +873,7 @@ async def run(): get_highest_revenue(), get_highest_income_tax(), get_most_employees(), + get_most_ftd_shares(), ) diff --git a/app/main.py b/app/main.py index 850fc41..d99dad5 100755 --- a/app/main.py +++ b/app/main.py @@ -3968,7 +3968,7 @@ async def get_statistics(data: FilterStockList, api_key: str = Security(get_api_ category_type = 'sector' elif filter_list == 'reits': category_type = 'industry' - elif filter_list in ['highest-income-tax','most-employees','highest-revenue','top-rated-dividend-stocks','penny-stocks','overbought-stocks','oversold-stocks','faang','magnificent-seven','ca','cn','de','gb','il','in','jp','nyse','nasdaq','amex','dowjones','sp500','nasdaq100','all-stock-tickers']: + elif filter_list in ['most-ftd-shares','highest-income-tax','most-employees','highest-revenue','top-rated-dividend-stocks','penny-stocks','overbought-stocks','oversold-stocks','faang','magnificent-seven','ca','cn','de','gb','il','in','jp','nyse','nasdaq','amex','dowjones','sp500','nasdaq100','all-stock-tickers']: category_type = 'stocks-list' elif filter_list in ['dividend-kings','dividend-aristocrats']: category_type = 'dividends'