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| from distutils.command.sdist import sdist | |
| from numpy import tri | |
| import pandas as pd | |
| import json, requests | |
| import slack, time | |
| from datetime import datetime | |
| # from bs4 import BeautifulSoup | |
| from config import * | |
| def get_yahoo_finance_quote(symbol): | |
| # Get the symbol quote from yahoo finance, we are using Beautiful Soup for scraping | |
| URL = f"https://finance.yahoo.com/quote/{symbol}" | |
| headers = {'User-Agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.61 Safari/537.36'} | |
| page = requests.get(URL, headers = headers) | |
| soup = BeautifulSoup(page.text, "html.parser") | |
| price = soup.find('div',{'class':'D(ib) Mend(20px)'}).find_all('fin-streamer')[0].text | |
| return float(price.replace(",","")) | |
| def get_cnbc_data(symbol): | |
| ticker = symbol.replace(" ","") | |
| if ticker == "NASDAQ": | |
| ticker = "NDX" | |
| elif ticker == "NIFTY50": | |
| ticker = ".NSEI" | |
| # Get the symbol quote from yahoo finance, we are using Beautiful Soup for scraping | |
| df = pd.DataFrame(requests.get(f"https://ts-api.cnbc.com/harmony/app/charts/1Y.json?symbol={ticker}").json()["barData"]["priceBars"]) | |
| # df_1D = pd.DataFrame(requests.get(f"https://ts-api.cnbc.com/harmony/app/charts/1D.json?symbol={ticker}").json()["barData"]["priceBars"]) | |
| df["datetime"] = pd.to_datetime(df['tradeTimeinMills'],unit='ms') | |
| df["close"] = df["close"].astype(float) | |
| # df_1D["close"] = df_1D["close"].astype(float) | |
| df.set_index("datetime",inplace = True) | |
| dma200 = (df["close"].rolling(200).mean()).iloc[-1] | |
| close = (df["close"].iloc[-1]) | |
| return dma200, close | |
| client = slack.WebClient(token = SLACK_TOKEN) | |
| while True: | |
| df = pd.read_csv('watchlist.csv') | |
| df.set_index("Symbol",inplace = True) | |
| # df_crypto = pd.DataFrame(json.loads(requests.get("https://ftx.com/api/markets").text)["result"]) | |
| # df_crypto = df_crypto[df_crypto["quoteCurrency"].isin(["USD","USDT"])] | |
| # df_crypto.set_index("name",inplace = True) | |
| if len(df)>0: | |
| req_df_price = df[df["status"] == "Pending"] | |
| req_df_dma = df[df["dma_status"] == "Pending"] | |
| for symbol in req_df_price.index: | |
| if symbol in ["SPX","US 2Y","US 5Y","US 10Y","US 30Y","HYG","LQD","NASDAQ","VIX","NIFTY50"]: | |
| dma200, ltp= get_cnbc_data(symbol) | |
| # else: | |
| # ltp = df_crypto.loc[symbol]["last"] | |
| trigger_level = req_df_price.loc[symbol]["Trigger"] | |
| triggered = 0 | |
| if req_df_price.loc[symbol]["view_type"] == "Above": | |
| if trigger_level<=ltp: | |
| triggered = 1 | |
| elif req_df_price.loc[symbol]["view_type"] == "Below": | |
| if trigger_level>=ltp: | |
| triggered = 1 | |
| if triggered == 1: | |
| df.at[symbol,"status"] = "Triggered" | |
| client.chat_postMessage(channel = f"#{df.loc[symbol]['alert_type'].lower()}_signal", | |
| text = f"{datetime.now().strftime('%Y-%m-%d %H:%M:%S')} {symbol} is {df.loc[symbol]['view_type']} {trigger_level} at {ltp}") | |
| for symbol in req_df_dma.index: | |
| dma_check = req_df_dma.loc[symbol]["dma200"] | |
| if dma_check == False: | |
| continue | |
| triggered_dma200 = 0 | |
| dma200, ltp= get_cnbc_data(symbol) | |
| print(dma200) | |
| if req_df_dma.loc[symbol]["dma200_view_type"] == "Above": | |
| if dma200<=ltp: | |
| triggered_dma200 = 1 | |
| elif req_df_dma.loc[symbol]["dma200_view_type"] == "Below": | |
| if dma200>=ltp: | |
| triggered_dma200 = 1 | |
| if triggered_dma200 == 1: | |
| df.at[symbol,"dma_status"] = "Triggered" | |
| client.chat_postMessage(channel = f"#{df.loc[symbol]['alert_type'].lower()}_signal", | |
| text = f"{datetime.now().strftime('%Y-%m-%d %H:%M:%S')} {symbol} is {df.loc[symbol]['dma200_view_type']} DMA200 at {ltp}") | |
| df.to_csv("watchlist.csv") | |
| # Recheck again after 60 minutes | |
| time.sleep(60*60) |