update cronjob

app/cron_financial_statements.py

@@ -11,14 +11,37 @@
 
 # Configurations
 include_current_quarter = False
-max_concurrent_requests = 100  # Limit concurrent requests
-
-async def fetch_data(session, url, symbol, attempt=0):
+max_concurrent_requests = 100
+
+class RateLimiter:
+    def __init__(self, max_requests, time_window):
+        self.max_requests = max_requests
+        self.time_window = time_window
+        self.requests = 0
+        self.last_reset = asyncio.get_event_loop().time()
+
+    async def acquire(self):
+        current_time = asyncio.get_event_loop().time()
+        if current_time - self.last_reset >= self.time_window:
+            self.requests = 0
+            self.last_reset = current_time
+
+        if self.requests >= self.max_requests:
+            wait_time = self.time_window - (current_time - self.last_reset)
+            if wait_time > 0:
+                print(f"\nRate limit reached. Waiting {wait_time:.2f} seconds...")
+                await asyncio.sleep(wait_time)
+                self.requests = 0
+                self.last_reset = asyncio.get_event_loop().time()
+
+        self.requests += 1
+
+async def fetch_data(session, url, symbol, rate_limiter):
+    await rate_limiter.acquire()
     try:
         async with session.get(url) as response:
             if response.status == 200:
-                data = await response.json()
-                return data
+                return await response.json()
             else:
                 print(f"Error fetching data for {symbol}: HTTP {response.status}")
                 return None
@@ -31,7 +54,6 @@ async def save_json(symbol, period, data_type, data):
     with open(f"json/financial-statements/{data_type}/{period}/{symbol}.json", 'w') as file:
         ujson.dump(data, file)
 
-
 async def calculate_margins(symbol):
     for period in ['annual', 'quarter']:
         try:
@@ -49,39 +71,35 @@ async def calculate_margins(symbol):
             ratios_path = f"json/financial-statements/ratios/{period}/{symbol}.json"
             with open(ratios_path, "r") as file:
                 ratio_data = ujson.load(file)
-            # Ensure all datasets are available and iterate through the items
+
             if income_data and cash_flow_data and ratio_data:
                 for ratio_item, income_item, cash_flow_item in zip(ratio_data, income_data, cash_flow_data):
-                    # Extract required data
                     revenue = income_item.get('revenue', 0)
-                    ebitda = income_item.get('ebitda',0)
+                    ebitda = income_item.get('ebitda', 0)
                     free_cash_flow = cash_flow_item.get('freeCashFlow', 0)
 
-                    # Calculate freeCashFlowMargin if data is valid
-                    if revenue != 0:  # Avoid division by zero
+                    if revenue != 0:
                         ratio_item['freeCashFlowMargin'] = round((free_cash_flow / revenue) * 100, 2)
-                        ratio_item['ebitdaMargin'] = round((ebitda / revenue) * 100,2)
-                        ratio_item['grossProfitMargin'] = round(ratio_item['grossProfitMargin']*100,2)
-                        ratio_item['operatingProfitMargin'] = round(ratio_item['operatingProfitMargin']*100,2)
-                        ratio_item['pretaxProfitMargin'] = round(ratio_item['pretaxProfitMargin']*100,2)
-                        ratio_item['netProfitMargin'] = round(ratio_item['netProfitMargin']*100,2)
+                        ratio_item['ebitdaMargin'] = round((ebitda / revenue) * 100, 2)
+                        ratio_item['grossProfitMargin'] = round(ratio_item['grossProfitMargin'] * 100, 2)
+                        ratio_item['operatingProfitMargin'] = round(ratio_item['operatingProfitMargin'] * 100, 2)
+                        ratio_item['pretaxProfitMargin'] = round(ratio_item['pretaxProfitMargin'] * 100, 2)
+                        ratio_item['netProfitMargin'] = round(ratio_item['netProfitMargin'] * 100, 2)
                     else:
-                        ratio_item['freeCashFlowMargin'] = None  # Handle missing or zero revenue
+                        ratio_item['freeCashFlowMargin'] = None
                         ratio_item['ebitdaMargin'] = None
                         ratio_item['grossProfitMargin'] = None
                         ratio_item['operatingProfitMargin'] = None
                         ratio_item['pretaxProfitMargin'] = None
                         ratio_item['netProfitMargin'] = None
 
-                # Save the updated ratios data back to the JSON file
-
                 with open(ratios_path, "w") as file:
-                    ujson.dump(ratio_data,file)
+                    ujson.dump(ratio_data, file)
 
         except Exception as e:
-            print(e)
+            print(f"Error calculating margins for {symbol}: {e}")
 
-async def get_financial_statements(session, symbol, semaphore, request_counter):
+async def get_financial_statements(session, symbol, semaphore, rate_limiter):
     base_url = "https://financialmodelingprep.com/api/v3"
     periods = ['quarter', 'annual']
     financial_data_types = ['key-metrics', 'income-statement', 'balance-sheet-statement', 'cash-flow-statement', 'ratios']
@@ -92,46 +110,30 @@ async def get_financial_statements(session, symbol, semaphore, request_counter):
             # Fetch regular financial statements
             for data_type in financial_data_types:
                 url = f"{base_url}/{data_type}/{symbol}?period={period}&apikey={api_key}"
-                data = await fetch_data(session, url, symbol)
+                data = await fetch_data(session, url, symbol, rate_limiter)
                 if data:
                     await save_json(symbol, period, data_type, data)
-
-                request_counter[0] += 1  # Increment the request counter
-                if request_counter[0] >= 500:
-                    await asyncio.sleep(60)  # Pause for 60 seconds
-                    request_counter[0] = 0  # Reset the request counter after the pause
 
             # Fetch financial statement growth data
             for growth_type in growth_data_types:
                 growth_url = f"{base_url}/{growth_type}/{symbol}?period={period}&apikey={api_key}"
-                growth_data = await fetch_data(session, growth_url, symbol)
+                growth_data = await fetch_data(session, growth_url, symbol, rate_limiter)
                 if growth_data:
                     await save_json(symbol, period, growth_type, growth_data)
 
-                request_counter[0] += 1  # Increment the request counter
-                if request_counter[0] >= 500:
-                    await asyncio.sleep(60)  # Pause for 60 seconds
-                    request_counter[0] = 0  # Reset the request counter after the pause
-
-
+        # Fetch TTM metrics
         url = f"https://financialmodelingprep.com/api/v3/key-metrics-ttm/{symbol}?apikey={api_key}"
-        data = await fetch_data(session, url, symbol)
+        data = await fetch_data(session, url, symbol, rate_limiter)
         if data:
             await save_json(symbol, 'ttm', 'key-metrics', data)
 
         # Fetch owner earnings data
         owner_earnings_url = f"https://financialmodelingprep.com/api/v4/owner_earnings?symbol={symbol}&apikey={api_key}"
-        owner_earnings_data = await fetch_data(session, owner_earnings_url, symbol)
+        owner_earnings_data = await fetch_data(session, owner_earnings_url, symbol, rate_limiter)
         if owner_earnings_data:
             await save_json(symbol, 'quarter', 'owner-earnings', owner_earnings_data)
 
         await calculate_margins(symbol)
-        request_counter[0] += 1  # Increment the request counter
-        if request_counter[0] >= 500:
-            await asyncio.sleep(60)  # Pause for 60 seconds
-            request_counter[0] = 0  # Reset the request counter after the pause
-
-
 
 async def run():
     con = sqlite3.connect('stocks.db')
@@ -141,13 +143,13 @@ async def run():
     symbols = [row[0] for row in cursor.fetchall()]
     con.close()
 
+    rate_limiter = RateLimiter(max_requests=500, time_window=60)
     semaphore = asyncio.Semaphore(max_concurrent_requests)
-    request_counter = [0]  # Using a list to keep a mutable counter across async tasks
 
     async with aiohttp.ClientSession() as session:
         tasks = []
         for symbol in tqdm(symbols):
-            task = asyncio.create_task(get_financial_statements(session, symbol, semaphore, request_counter))
+            task = asyncio.create_task(get_financial_statements(session, symbol, semaphore, rate_limiter))
             tasks.append(task)
 
         await asyncio.gather(*tasks)

app/cron_options_hottest_contracts.py

@@ -11,6 +11,7 @@
 load_dotenv()
 
 api_key = os.getenv('UNUSUAL_WHALES_API_KEY')
+headers = {"Accept": "application/json, text/plain", "Authorization": api_key}
 
 # Connect to the databases
 con = sqlite3.connect('stocks.db')
@@ -29,20 +30,9 @@
 
 con.close()
 etf_con.close()
-# Combine the lists of stock and ETF symbols
-total_symbols = stocks_symbols + etf_symbols
 
 
 def get_tickers_from_directory(directory: str):
-    """
-    Retrieves all tickers from JSON filenames in the specified directory.
-
-    Args:
-        directory (str): Path to the directory containing JSON files.
-
-    Returns:
-        list: A list of tickers extracted from filenames.
-    """
     try:
         # Ensure the directory exists
         if not os.path.exists(directory):
@@ -58,6 +48,8 @@ def get_tickers_from_directory(directory: str):
 directory_path = "json/hottest-contracts/companies"
 total_symbols = get_tickers_from_directory(directory_path)
 
+if len(total_symbols) < 100:
+    total_symbols = stocks_symbols+etf_symbols
 
 def save_json(data, symbol,directory="json/hottest-contracts/companies"):
     os.makedirs(directory, exist_ok=True)  # Ensure the directory exists
@@ -92,53 +84,119 @@ def prepare_data(data, symbol):
 
     res_list = []
     for item in data:
-        if float(item['volume']) > 0:
-            # Parse option_symbol
-            date_expiration, option_type, strike_price = parse_option_symbol(item['option_symbol'])
-
-            # Round numerical and numerical-string values
-            new_item = {
-                key: safe_round(value) if isinstance(value, (int, float, str)) else value
-                for key, value in item.items()
-            }
+        try:
+            if float(item['volume']) > 0:
+                # Parse option_symbol
+                date_expiration, option_type, strike_price = parse_option_symbol(item['option_symbol'])
+
+                # Round numerical and numerical-string values
+                new_item = {
+                    key: safe_round(value) if isinstance(value, (int, float, str)) else value
+                    for key, value in item.items()
+                }
+
+                # Add parsed fields
+                new_item['date_expiration'] = date_expiration
+                new_item['option_type'] = option_type
+                new_item['strike_price'] = strike_price
+
+                # Calculate open_interest_change
+                new_item['open_interest_change'] = safe_round(
+                    new_item.get('open_interest', 0) - new_item.get('prev_oi', 0)
+                )
+
+                res_list.append(new_item)
+        except:
+            pass
 
-            # Add parsed fields
-            new_item['date_expiration'] = date_expiration
-            new_item['option_type'] = option_type
-            new_item['strike_price'] = strike_price
+    if res_list:
+        highest_volume = sorted(res_list, key=lambda x: x['volume'], reverse=True)[:10]
+        highest_open_interest = sorted(res_list, key=lambda x: x['open_interest'], reverse=True)[:10]
+        res_dict = {'volume': highest_volume, 'openInterest': highest_open_interest}
+        save_json(res_dict, symbol,"json/hottest-contracts/companies")
+
+
+def get_hottest_contracts():
+    counter = 0
+    for symbol in tqdm(total_symbols):
+        try:
+
+            url = f"https://api.unusualwhales.com/api/stock/{symbol}/option-contracts"
+
+            response = requests.get(url, headers=headers)
+            if response.status_code == 200:
+                data = response.json()['data']
+                prepare_data(data, symbol)
+                counter +=1
+            # If 50 chunks have been processed, sleep for 60 seconds
+            if counter == 100:
+                print("Sleeping...")
+                time.sleep(30)  # Sleep for 60 seconds
+                counter = 0
+
+        except Exception as e:
+            print(f"Error for {symbol}:{e}")
+
+
+def get_single_contract_historical_data(contract_id):
+    keys_to_remove = {'high_price', 'low_price', 'iv_low', 'iv_high', 'last_tape_time'}
+
+    url = f"https://api.unusualwhales.com/api/option-contract/{contract_id}/historic"
+    response = requests.get(url, headers=headers)
+    data = response.json()['chains']
+    data = sorted(data, key=lambda x: datetime.strptime(x.get('date', ''), '%Y-%m-%d'))
+    res_list = []
+    for i, item in enumerate(data):
+        new_item = {
+            key: safe_round(value) if isinstance(value, (int, float, str)) else value
+            for key, value in item.items()
+        }
+
+        # Compute open interest change and percent if not the first item
+        if i > 0:
+            previous_open_interest = safe_round(data[i-1].get('open_interest', 0))
+            open_interest = safe_round(item.get('open_interest', 0))
 
-            # Calculate open_interest_change
-            new_item['open_interest_change'] = safe_round(
-                new_item.get('open_interest', 0) - new_item.get('prev_oi', 0)
-            )
+            if previous_open_interest > 0:
+                new_item['open_interest_change'] = safe_round(open_interest - previous_open_interest)
+                new_item['open_interest_change_percent'] = safe_round((open_interest / previous_open_interest - 1) * 100)
+            else:
+                new_item['open_interest_change'] = 0
+                new_item['open_interest_change_percent'] = 0
 
-            res_list.append(new_item)
+        res_list.append(new_item)
 
     if res_list:
-        save_json(res_list, symbol,"json/hottest-contracts/companies")
+        res_list = [{key: value for key, value in item.items() if key not in keys_to_remove} for item in res_list]
+        res_list = sorted(res_list, key=lambda x: datetime.strptime(x.get('date', ''), '%Y-%m-%d'), reverse=True)
 
+        save_json(res_list, contract_id,"json/hottest-contracts/contracts")
 
-counter = 0
-for symbol in tqdm(total_symbols):
-    try:
-
-        url = f"https://api.unusualwhales.com/api/stock/{symbol}/option-contracts"
-
-        headers = {
-            "Accept": "application/json, text/plain",
-            "Authorization": api_key
-        }
-
-        response = requests.get(url, headers=headers)
-        if response.status_code == 200:
-            data = response.json()['data']
-            prepare_data(data, symbol)
-            counter +=1
-        # If 50 chunks have been processed, sleep for 60 seconds
-        if counter == 100:
-            print("Sleeping...")
-            time.sleep(30)  # Sleep for 60 seconds
-            counter = 0
-
-    except Exception as e:
-        print(f"Error for {symbol}:{e}")
+
+if __name__ == '__main__':
+    get_hottest_contracts()
+
+    '''
+    total_symbols = get_tickers_from_directory(directory_path)
+
+    contract_id_set = set()  # Use a set to ensure uniqueness
+    for symbol in total_symbols:
+        try:
+            with open(f"json/hottest-contracts/companies/{symbol}.json", "r") as file:
+                data = orjson.loads(file.read())
+                for item in data:
+                    try:
+                        contract_id_set.add(item['option_symbol'])  # Add to the set
+                    except KeyError:
+                        pass  # Handle missing 'option_symbol' keys gracefully
+        except FileNotFoundError:
+            pass  # Handle missing files gracefully
+
+    # Convert the set to a list if needed
+    contract_id_list = list(contract_id_set)
+    
+    print(len(contract_id_list))
+    print(contract_id_list[0])
+
+    get_single_contract_historical_data('GME250117C00125000')
+    '''