mirror of
https://github.com/OpenBB-finance/OpenBB.git
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1ca7fd9beb
* Began the fax * Bumped ruff * Fixed a BUNCH of ruff errors * Fixed a lot of ruff errors * Simplify if statements * Fixed black * Updated some stuff * Updated some stuff * A lot more ruff fixes * Added a fix * Added a fix * Fixed mypy * Fixed some stuff * Reverted one thing * Small fix * Small fix * Small fix * Added fix * Added fix * Update requirements
302 lines
8.4 KiB
Python
302 lines
8.4 KiB
Python
"""Forex helper."""
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import argparse
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import logging
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import os
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import re
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from datetime import datetime, timedelta
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from typing import Dict, Iterable, List, Optional
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import pandas as pd
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import yfinance as yf
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from openbb_terminal.core.plots.plotly_ta.ta_class import PlotlyTA
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from openbb_terminal.decorators import log_start_end
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from openbb_terminal.forex import av_model, polygon_model
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from openbb_terminal.rich_config import console
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from openbb_terminal.stocks import stocks_helper
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CANDLE_SORT = [
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"adjclose",
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"open",
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"close",
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"high",
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"low",
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"volume",
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"logret",
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]
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FOREX_SOURCES: Dict = {
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"YahooFinance": "YahooFinance",
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"AlphaVantage": "AlphaAdvantage",
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"Polygon": "Polygon",
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"Oanda": "Oanda",
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}
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SOURCES_INTERVALS: Dict = {
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"YahooFinance": [
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"1min",
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"5min",
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"15min",
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"30min",
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"60min",
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"90min",
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"1hour",
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"1day",
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"5day",
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"1week",
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"1month",
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"3month",
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],
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"AlphaVantage": ["1min", "5min", "15min", "30min", "60min"],
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}
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INTERVAL_MAPS: Dict = {
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"YahooFinance": {
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"1min": "1m",
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"2min": "2m",
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"5min": "5m",
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"15min": "15m",
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"30min": "30m",
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"60min": "60m",
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"90min": "90m",
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"1hour": "60m",
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"1day": "1d",
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"5day": "5d",
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"1week": "1wk",
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"1month": "1mo",
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"3month": "3mo",
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},
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"AlphaVantage": {
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"1min": 1,
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"5min": 5,
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"15min": 15,
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"30min": 30,
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"60min": 60,
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"1day": 1,
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},
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}
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logger = logging.getLogger(__name__)
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@log_start_end(log=logger)
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def load(
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to_symbol: str,
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from_symbol: str,
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resolution: str = "d",
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interval: str = "1day",
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start_date: Optional[str] = None,
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end_date: Optional[str] = None,
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source: str = "YahooFinance",
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verbose: bool = False,
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) -> pd.DataFrame:
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"""Load forex for two given symbols.
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Parameters
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----------
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to_symbol : str
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The from currency symbol. Ex: USD, EUR, GBP, YEN
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from_symbol : str
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The from currency symbol. Ex: USD, EUR, GBP, YEN
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resolution : str, optional
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The resolution for the data, by default "d"
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interval : str, optional
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What interval to get data for, by default "1day"
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start_date : Optional[str], optional
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When to begin loading in data, by default last_year.strftime("%Y-%m-%d")
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end_date : Optional[str], optional
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When to end loading in data, by default None
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source : str, optional
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Where to get data from, by default "YahooFinance"
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verbose : bool, optional
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Display verbose information on what was the pair that was loaded, by default True
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Returns
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-------
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pd.DataFrame
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The loaded data
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Examples
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--------
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>>> from openbb_terminal.sdk import openbb
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>>> openbb.forex.load(from_symbol="EUR", to_symbol="USD", start_date="2020-11-30", end_date="2022-12-01")
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"""
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if start_date is None:
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start_date = (datetime.now() - timedelta(days=365)).strftime("%Y-%m-%d")
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if end_date is None:
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end_date = (datetime.now() + timedelta(days=1)).strftime("%Y-%m-%d")
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else:
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end_date = (
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datetime.strptime(end_date, "%Y-%m-%d") + timedelta(days=1)
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).strftime("%Y-%m-%d")
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if source in ["YahooFinance", "AlphaVantage"]:
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interval_map = INTERVAL_MAPS[source]
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if interval not in interval_map and resolution != "d":
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if verbose:
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console.print(
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f"Interval not supported by {FOREX_SOURCES[source]}."
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" Need to be one of the following options",
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list(interval_map.keys()),
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)
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return pd.DataFrame()
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# Check interval in multiple ways
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if interval in interval_map:
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clean_interval = interval_map[interval]
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elif interval in interval_map.values():
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clean_interval = interval
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else:
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console.print(f"[red]'{interval}' is an invalid interval[/red]\n")
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return pd.DataFrame()
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if source == "AlphaVantage":
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if "min" in interval:
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resolution = "i"
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df = av_model.get_historical(
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to_symbol=to_symbol,
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from_symbol=from_symbol,
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resolution=resolution,
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interval=clean_interval,
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start_date=start_date,
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end_date=end_date,
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)
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df.index.name = "date"
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df.name = f"{from_symbol}/{to_symbol}"
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return df
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if source == "YahooFinance":
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df = yf.download(
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f"{from_symbol}{to_symbol}=X",
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start=datetime.strptime(start_date, "%Y-%m-%d"),
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end=datetime.strptime(end_date, "%Y-%m-%d"),
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interval=clean_interval,
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progress=verbose,
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)
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df.index = pd.to_datetime(df.index).tz_localize(None)
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df.index.name = "date"
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df.name = f"{from_symbol}/{to_symbol}"
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return df
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if source == "Polygon":
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# Interval for polygon gets broken into multiplier and timeframe
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temp = re.split(r"(\d+)", interval)
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multiplier = int(temp[1])
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timeframe = temp[2]
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if timeframe == "min":
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timeframe = "minute"
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df = polygon_model.get_historical(
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f"{from_symbol}{to_symbol}",
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multiplier=multiplier,
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timespan=timeframe,
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start_date=start_date,
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end_date=end_date,
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)
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df.index.name = "date"
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df.name = f"{from_symbol}/{to_symbol}"
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return df
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console.print(f"Source {source} not supported")
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return pd.DataFrame()
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@log_start_end(log=logger)
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def get_yf_currency_list() -> List:
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"""Load YF list of forex pair a local file."""
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path = os.path.join(os.path.dirname(__file__), "data/yahoofinance_forex.json")
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return sorted(list(set(pd.read_json(path)["from_symbol"])))
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YF_CURRENCY_LIST = get_yf_currency_list()
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@log_start_end(log=logger)
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def check_valid_yf_forex_currency(fx_symbol: str) -> str:
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"""Check if given symbol is supported on Yahoo Finance.
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Parameters
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----------
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fx_symbol : str
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Symbol to check
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Returns
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-------
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str
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Currency symbol
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Raises
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------
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argparse.ArgumentTypeError
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Symbol not valid on YahooFinance
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"""
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if fx_symbol.upper() in get_yf_currency_list():
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return fx_symbol.upper()
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raise argparse.ArgumentTypeError(
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f"{fx_symbol.upper()} not found in YahooFinance supported currency codes. "
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)
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@log_start_end(log=logger)
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def display_candle(
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data: pd.DataFrame,
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to_symbol: str = "",
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from_symbol: str = "",
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ma: Optional[Iterable[int]] = None,
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external_axes: bool = False,
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add_trend: bool = False,
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yscale: str = "linear",
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):
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"""Show candle plot for fx data.
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Parameters
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----------
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data : pd.DataFrame
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Loaded fx historical data
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to_symbol : str
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To forex symbol
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from_symbol : str
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From forex symbol
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ma : Optional[Iterable[int]]
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Moving averages
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external_axes : bool, optional
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Whether to return the figure object or not, by default False
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"""
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# We check if there's Volume data to avoid errors and empty subplots
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if not (has_volume := False) and "Volume" in data.columns:
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has_volume = bool(data["Volume"].sum() > 0)
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if add_trend and (data.index[1] - data.index[0]).total_seconds() >= 86400:
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if "date_id" not in data.columns:
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data = stocks_helper.process_candle(data)
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data = stocks_helper.find_trendline(data, "OC_High", "high")
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data = stocks_helper.find_trendline(data, "OC_Low", "low")
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indicators = {}
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if ma:
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indicators = dict(rma=dict(length=ma))
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data.name = f"{from_symbol}/{to_symbol}"
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fig = PlotlyTA.plot(data, indicators, volume=has_volume)
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if add_trend:
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fig.add_trend(data, secondary_y=False)
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fig.update_yaxes(type=yscale, row=1, col=1, nticks=20, secondary_y=False)
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return fig.show(external=external_axes)
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@log_start_end(log=logger)
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def parse_forex_symbol(input_symbol):
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"""Parse potential forex symbols."""
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for potential_split in ["-", "/"]:
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if potential_split in input_symbol:
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symbol = input_symbol.replace(potential_split, "")
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return symbol
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if len(input_symbol) != 6:
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raise argparse.ArgumentTypeError("Input symbol should be 6 characters.\n ")
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return input_symbol.upper()
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