mirror of
https://github.com/OpenBB-finance/OpenBB.git
synced 2026-11-14 05:14:19 +00:00
a37d9032e3
* Fix plot look when using eval and add query to choices (#3881)
* convert index to datetime and update choices
* uncomment economy integration test
* fix treasury concat bug
* fix datasets concat on duplciates
* Lock ruff version so that new lints dont break our CI (#3905)
* Lock ruff version so that new lints dont break our CI
* Bumped pre-commit ruff version
* returning always a dataframe
* Revert "returning always a dataframe"
This reverts commit d5dbf3132f.
* black everything
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119 lines
3.1 KiB
Python
119 lines
3.1 KiB
Python
"""Tradingview model"""
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__docformat__ = "numpy"
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import logging
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import pandas as pd
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from tradingview_ta import TA_Handler
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from openbb_terminal import config_terminal as cfg
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from openbb_terminal.decorators import log_start_end
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from openbb_terminal.helper_funcs import request
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logger = logging.getLogger(__name__)
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INTERVALS = {
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"1m": "1 min",
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"5m": "5 min",
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"15m": "15 min",
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"1h": "1 hour",
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"4h": "4 hours",
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"1d": "1 day",
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"1W": "1 week",
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"1M": "1 month",
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}
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SCREENERS = [
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"australia",
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"brazil",
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"cfd",
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"crypto",
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"euronext",
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"forex",
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"france",
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"germany",
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"hongkong",
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"india",
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"indonesia",
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"malaysia",
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"philippines",
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"russia",
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"ksa",
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"rsa",
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"korea",
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"spain",
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"sweden",
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"taiwan",
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"thailand",
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"turkey",
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"uk",
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"america",
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"vietnam",
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]
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@log_start_end(log=logger)
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def get_tradingview_recommendation(
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symbol: str, screener: str = "america", exchange: str = "", interval: str = ""
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) -> pd.DataFrame:
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"""Get tradingview recommendation based on technical indicators
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Parameters
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----------
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symbol : str
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Ticker symbol to get the recommendation from tradingview based on technical indicators
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screener : str
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Screener based on tradingview docs https://python-tradingview-ta.readthedocs.io/en/latest/usage.html
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exchange: str
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Exchange based on tradingview docs https://python-tradingview-ta.readthedocs.io/en/latest/usage.html
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interval: str
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Interval time to check technical indicators and correspondent recommendation
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Returns
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-------
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df_recommendation: pd.DataFrame
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Dataframe of tradingview recommendations based on technical indicators
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"""
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if not exchange:
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s_req = f"https://www.alphavantage.co/query?function=OVERVIEW&symbol={symbol}&apikey={cfg.API_KEY_ALPHAVANTAGE}"
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result = request(s_req, stream=True)
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data = result.json()
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if not data:
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return pd.DataFrame()
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exchange = data["Exchange"]
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if interval:
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intervals = [interval]
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else:
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intervals = ["1M", "1W", "1d", "4h", "1h", "15m", "5m", "1m"]
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df_recommendation = pd.DataFrame()
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index_recommendation = []
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for an_interval in intervals:
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if exchange:
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stock_recommendation = TA_Handler(
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symbol=symbol,
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screener=screener,
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exchange=exchange,
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interval=an_interval,
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)
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d_recommendation = stock_recommendation.get_analysis().summary
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df_recommendation = pd.concat(
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[
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pd.DataFrame.from_dict(d_recommendation, orient="index").T,
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df_recommendation,
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],
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axis=0,
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)
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index_recommendation.append(INTERVALS[an_interval])
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df_recommendation.index = index_recommendation
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df_recommendation[["BUY", "NEUTRAL", "SELL"]] = df_recommendation[
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["BUY", "NEUTRAL", "SELL"]
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].astype(int)
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df_recommendation.index.name = "Interval"
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return df_recommendation
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