From 95b4cd9439ec7bef0ed35dec20201bcacce6efe0 Mon Sep 17 00:00:00 2001 From: MuslemRahimi Date: Sat, 15 Jun 2024 15:17:25 +0200 Subject: [PATCH] add retail volume --- app/cron_retail_volume.py | 102 ++++++++++++++++++++++++++++++++++++++ app/main.py | 18 +++++++ 2 files changed, 120 insertions(+) create mode 100644 app/cron_retail_volume.py diff --git a/app/cron_retail_volume.py b/app/cron_retail_volume.py new file mode 100644 index 0000000..fb09f5c --- /dev/null +++ b/app/cron_retail_volume.py @@ -0,0 +1,102 @@ +import ujson +import asyncio +import aiohttp +import sqlite3 +from datetime import datetime,timedelta +from tqdm import tqdm +from dotenv import load_dotenv +import os +load_dotenv() +api_key = os.getenv('NASDAQ_API_KEY') + + +# Get today's date +today = datetime.now() +# Calculate the date six months ago +six_months_ago = today - timedelta(days=6*30) # Rough estimate, can be refined + + +async def save_json(symbol, data): + with open(f"json/retail-volume/companies/{symbol}.json", 'w') as file: + ujson.dump(data, file) + + +# Function to filter the list +def filter_past_six_months(data): + filtered_data = [] + for entry in data: + entry_date = datetime.strptime(entry['date'], '%Y-%m-%d') + if entry_date >= six_months_ago: + filtered_data.append(entry) + sorted_data = sorted(filtered_data, key=lambda x: datetime.strptime(x['date'], '%Y-%m-%d')) + return sorted_data + + +async def get_data(ticker_list): + ticker_str = ','.join(ticker_list) + async with aiohttp.ClientSession() as session: + url = f"https://data.nasdaq.com/api/v3/datatables/NDAQ/RTAT?api_key={api_key}&ticker={ticker_str}" + async with session.get(url) as response: + if response.status == 200: + data = (await response.json())['datatable']['data'] + return data + else: + return [] + + + +async def run(): + con = sqlite3.connect('stocks.db') + etf_con = sqlite3.connect('etf.db') + + cursor = con.cursor() + cursor.execute("PRAGMA journal_mode = wal") + cursor.execute("SELECT DISTINCT symbol FROM stocks") + stocks_symbols = [row[0] for row in cursor.fetchall()] + + etf_cursor = etf_con.cursor() + etf_cursor.execute("PRAGMA journal_mode = wal") + etf_cursor.execute("SELECT DISTINCT symbol FROM etfs") + etf_symbols = [row[0] for row in etf_cursor.fetchall()] + + con.close() + etf_con.close() + + + total_symbols = stocks_symbols+etf_symbols + + chunk_size = len(total_symbols) // 70 # Divide the list into N chunks + chunks = [total_symbols[i:i + chunk_size] for i in range(0, len(total_symbols), chunk_size)] + + most_retail_volume = [] + + for chunk in tqdm(chunks): + data = await get_data(chunk) + # Transforming the list of lists into a list of dictionaries + transformed_data = [ + { + 'date': entry[0], + 'symbol': entry[1], + 'traded': entry[2]*30*10**9, #data is normalized to $30B per day + 'sentiment': entry[3] + } + for entry in data + ] + for symbol in chunk: + try: + filtered_data = [item for item in transformed_data if symbol == item['symbol']] + res = filter_past_six_months(filtered_data) + most_retail_volume.append({'assetType': 'stocks' if res[-1]['symbol'] in stocks_symbols else 'etf','symbol': res[-1]['symbol'], 'traded': res[-1]['traded'], 'sentiment': res[-1]['sentiment']}) + await save_json(symbol, res) + except: + pass + + most_retail_volume = sorted(most_retail_volume, key=lambda x: x['traded'], reverse=True)[:100] # top 100 retail volume stocks + + with open(f"json/retail-volume/data.json", 'w') as file: + ujson.dump(most_retail_volume, file) + +try: + asyncio.run(run()) +except Exception as e: + print(e) \ No newline at end of file diff --git a/app/main.py b/app/main.py index 95cff0a..10e70c2 100755 --- a/app/main.py +++ b/app/main.py @@ -2820,6 +2820,24 @@ async def get_most_shorted_stocks(): except: res = [] + redis_client.set(cache_key, ujson.dumps(res)) + redis_client.expire(cache_key, 3600*3600) # Set cache expiration time to 1 day + return res + + +@app.post("/retail-volume") +async def get_retail_volume(data:TickerData): + ticker = data.ticker.upper() + cache_key = f"retail-volume-{ticker}" + cached_result = redis_client.get(cache_key) + if cached_result: + return ujson.loads(cached_result) + try: + with open(f"json/retail-volume/companies/{ticker}.json", 'r') as file: + res = ujson.load(file) + except: + res = [] + redis_client.set(cache_key, ujson.dumps(res)) redis_client.expire(cache_key, 3600*3600) # Set cache expiration time to 1 day return res \ No newline at end of file