add after market and premarket to market movers
This commit is contained in:
MuslemRahimi
parent
15da925dc4
commit
cbb53bb129
@ -362,9 +362,15 @@ async def run():
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market_movers = {'gainers': data['gainers']['1D'][:5], 'losers': data['losers']['1D'][:5]}
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except:
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market_movers = {}
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else:
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elif market_status == 1:
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try:
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with open(f"json/market-movers/pre-post-data.json", 'r') as file:
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with open(f"json/market-movers/premarket.json", 'r') as file:
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market_movers = ujson.load(file)
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except:
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market_movers = {}
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elif market_status == 2:
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try:
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with open(f"json/market-movers/afterhours.json", 'r') as file:
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market_movers = ujson.load(file)
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except:
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market_movers = {}
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@ -20,6 +20,41 @@ api_key = os.getenv('FMP_API_KEY')
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market_cap_threshold = 1E6
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volume_threshold = 50_000
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def check_market_hours():
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holidays = [
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"2024-01-01", "2024-01-15", "2024-02-19", "2024-03-29",
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"2024-05-27", "2024-06-19", "2024-07-04", "2024-09-02",
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"2024-11-28", "2024-12-25"
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]
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# Get the current date and time in ET (Eastern Time)
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et_timezone = pytz.timezone('America/New_York')
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current_time = datetime.now(et_timezone)
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current_date_str = current_time.strftime('%Y-%m-%d')
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current_hour = current_time.hour
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current_minute = current_time.minute
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current_day = current_time.weekday() # Monday is 0, Sunday is 6
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# Check if the current date is a holiday or weekend
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is_weekend = current_day >= 5 # Saturday (5) or Sunday (6)
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is_holiday = current_date_str in holidays
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# Determine the market status
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if is_weekend or is_holiday:
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return 0 #Closed
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elif current_hour < 9 or (current_hour == 9 and current_minute < 30):
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return 1 # Pre-Market
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elif 9 <= current_hour < 16 or (current_hour == 16 and current_minute == 0):
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return 0 #"Market hours."
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elif 16 <= current_hour < 24:
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return 2 #"After-market hours."
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else:
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return 0 #"Market is closed."
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market_status = check_market_hours()
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async def get_todays_data(ticker):
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current_weekday = datetime.today().weekday()
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@ -87,7 +122,7 @@ def add_rank(data):
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for index, item in enumerate(data[key], start=1):
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item['rank'] = index
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return data
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async def get_gainer_loser_active_stocks():
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#Database read 1y and 3y data
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@ -265,7 +300,7 @@ async def get_historical_data():
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return res_list
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async def get_pre_post_market_movers(symbols):
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async def get_pre_after_market_movers(symbols):
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res_list = []
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# Loop through the symbols and load the corresponding JSON files
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@ -303,10 +338,42 @@ async def get_pre_post_market_movers(symbols):
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# Sort the list by changesPercentage in descending order and slice the top 10
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top_5_gainers = sorted(res_list, key=lambda x: x['changesPercentage'], reverse=True)[:5]
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top_5_losers = sorted(res_list, key=lambda x: x['changesPercentage'], reverse=False)[:5]
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gainers = sorted(res_list, key=lambda x: x['changesPercentage'], reverse=True)[:20]
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losers = sorted(res_list, key=lambda x: x['changesPercentage'], reverse=False)[:20]
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return {'gainers': top_5_gainers, 'losers': top_5_losers}
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for index, item in enumerate(gainers, start=1):
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item['rank'] = index # Add rank field
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for index, item in enumerate(losers, start=1):
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item['rank'] = index # Add rank field
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data = {'gainers': gainers, 'losers': losers}
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unique_symbols = set()
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# Iterate through categories and symbols
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for category in data.keys():
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# Add rank and process symbols
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for index, stock_data in enumerate(data[category], start=1):
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stock_data['rank'] = index # Add rank field
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symbol = stock_data["symbol"]
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unique_symbols.add(symbol)
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# Convert the set to a list if needed
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unique_symbols_list = list(unique_symbols)
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# Get the latest quote of all unique symbols and map it back to the original data list to update all values
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latest_quote = await get_quote_of_stocks(unique_symbols_list)
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# Updating values in the data list based on matching symbols from the quote list
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for category in data.keys():
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for stock_data in data[category]:
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symbol = stock_data["symbol"]
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quote_stock = next((item for item in latest_quote if item["symbol"] == symbol), None)
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if quote_stock:
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stock_data['marketCap'] = quote_stock['marketCap']
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stock_data['volume'] = quote_stock['volume']
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return data
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try:
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@ -319,19 +386,23 @@ try:
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symbols = [symbol for symbol in symbols if symbol != "STEC"]
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data = asyncio.run(get_gainer_loser_active_stocks())
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with open(f"json/market-movers/data.json", 'w') as file:
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ujson.dump(data, file)
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'''
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data = asyncio.run(get_historical_data())
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with open(f"json/mini-plots-index/data.json", 'w') as file:
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ujson.dump(data, file)
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data = asyncio.run(get_pre_post_market_movers(symbols))
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with open(f"json/market-movers/pre-post-data.json", 'w') as file:
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ujson.dump(data, file)
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'''
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data = asyncio.run(get_pre_after_market_movers(symbols))
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if market_status == 1:
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with open(f"json/market-movers/premarket.json", 'w') as file:
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ujson.dump(data, file)
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elif market_status == 2:
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with open(f"json/market-movers/afterhours.json", 'w') as file:
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ujson.dump(data, file)
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con.close()
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except Exception as e:
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41
app/main.py
41
app/main.py
@ -316,7 +316,8 @@ class HistoricalDate(BaseModel):
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class OptionsWatchList(BaseModel):
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optionsIdList: list
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class ParamsData(BaseModel):
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params: str
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# Replace NaN values with None in the resulting JSON object
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def replace_nan_inf_with_none(obj):
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@ -4219,6 +4220,44 @@ async def get_statistics(data: FilterStockList, api_key: str = Security(get_api_
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headers={"Content-Encoding": "gzip"}
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)
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@app.post("/pre-after-market-movers")
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async def get_statistics(data: ParamsData, api_key: str = Security(get_api_key)):
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params = data.params
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cache_key = f"pre-after-market-movers-{params}"
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cached_result = redis_client.get(cache_key)
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if cached_result:
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return StreamingResponse(
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io.BytesIO(cached_result),
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media_type="application/json",
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headers={"Content-Encoding": "gzip"}
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)
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if params == 'premarket':
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try:
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with open(f"json/market-movers/premarket.json", 'rb') as file:
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res = orjson.loads(file.read())
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except:
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res = {'gainers': [], 'losers': []}
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elif params == 'afterhours':
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try:
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with open(f"json/market-movers/afterhours.json", 'rb') as file:
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res = orjson.loads(file.read())
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except:
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res = {'gainers': [], 'losers': []}
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data = orjson.dumps(res)
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compressed_data = gzip.compress(data)
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redis_client.set(cache_key, compressed_data)
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redis_client.expire(cache_key,60*15)
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return StreamingResponse(
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io.BytesIO(compressed_data),
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media_type="application/json",
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headers={"Content-Encoding": "gzip"}
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)
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@app.get("/newsletter")
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async def get_newsletter():
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try:
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