add more rules

app/cron_info_text.py

@@ -542,6 +542,13 @@ data = {
     "sharesYoY": {
         "text": "The change in the number of shares outstanding, comparing the most recent quarter to the same quarter a year ago.",
     },
+    "floatShares": {
+        "text": "Float is the amount of shares that are considered available for trading. It subtracts closely held shares by insiders and restricted stock from the total number of shares outstanding."
+    },
+    "interestCoverage": {
+        "text": "The interest coverage ratio is a measure of the ability of a company to pay its interest expenses. It is calculated by dividing the company's Earnings Before Interest and Taxes (EBIT) by its interest expenses.",
+        "equation": "Interest Coverage Ratio = EBIT / Interest Expense"
+    }
 }
 
 

app/cron_statistics.py

@@ -1,21 +1,42 @@
-from datetime import datetime, timedelta
+from datetime import datetime
 import orjson
-import time
 import sqlite3
 import asyncio
-import aiohttp
-import random
 from tqdm import tqdm
-from dotenv import load_dotenv
-import os
 
 
+# Load stock screener data
+with open(f"json/stock-screener/data.json", 'rb') as file:
+    stock_screener_data = orjson.loads(file.read())
 stock_screener_data_dict = {item['symbol']: item for item in stock_screener_data}
 
 
+async def save_json(symbol, data):
+    """Save JSON data to a file."""
+    with open(f"json/statistics/{symbol}.json", 'wb') as file:
+        file.write(orjson.dumps(data))
+
+
+async def get_data(symbol):
+    """Extract specified columns data for a given symbol."""
+    columns = ['sharesOutStanding', 'sharesQoQ', 'sharesYoY','institutionalOwnership','floatShares',
+    'priceEarningsRatio','forwardPE','priceToSalesRatio','forwardPS','priceToBookRatio','priceToFreeCashFlowsRatio',
+    'sharesShort','shortOutStandingPercent','shortFloatPercent','shortRatio',
+    'enterpriseValue','evEarnings','evSales','evEBITDA','evEBIT','evFCF',
+    'currentRatio','quickRatio','debtRatio','debtEquityRatio',]
+    
+    if symbol in stock_screener_data_dict:
+        result = {}
+        for column in columns:
+            result[column] = stock_screener_data_dict[symbol].get(column, None)
+        return result
+    return {}
+
 
 
 async def run():
+    """Main function to run the data extraction process."""
+    # Connect to SQLite database
     con = sqlite3.connect('stocks.db')
     cursor = con.cursor()
     cursor.execute("PRAGMA journal_mode = wal")
@@ -23,8 +44,12 @@ async def run():
     total_symbols = [row[0] for row in cursor.fetchall()]
     con.close()
     
+    # Process symbols with progress bar
+    for symbol in tqdm(total_symbols, desc="Extracting dividend data"):
+        data = await get_data(symbol)
+        if data:  # Only save if we have data
+            await save_json(symbol, data)
     
-
 if __name__ == "__main__":
     loop = asyncio.get_event_loop()
     loop.run_until_complete(run())

app/restart_json.py

@@ -93,6 +93,7 @@ def filter_data_quarterly(data):
 def calculate_share_changes(symbol, item, con):
     item['sharesQoQ'] = None
     item['sharesYoY'] = None
+    item['floatShares'] = None
     try: 
         # Execute query and load data
         df = pd.read_sql_query(query_shares, con, params=(symbol,))
@@ -109,7 +110,8 @@ def calculate_share_changes(symbol, item, con):
         ]
 
         shareholder_statistics = sorted(shareholder_statistics, key=lambda x: datetime.strptime(x['date'], '%Y-%m-%d'), reverse=False)
-
+        #Add latest float shares for statistics page
+        item['floatShares'] = shareholder_statistics[-1]['floatShares']
         historical_shares = filter_data_quarterly(shareholder_statistics)
         
         latest_data = historical_shares[-1]['outstandingShares']
@@ -121,6 +123,7 @@ def calculate_share_changes(symbol, item, con):
     except:
         item['sharesQoQ'] = None
         item['sharesYoY'] = None
+        item['floatShares'] = None
 
 
 # Replace NaN values with None in the resulting JSON object