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* BIGGGG LINTING * fixing lints * fixing lints * black * very ruff * no export * fix hedge_view again * lints * platform lints * lints * black * black it @hjoaquim * fix some more linting --------- Co-authored-by: hjoaquim <h.joaquim@campus.fct.unl.pt>
167 lines
4.3 KiB
Python
167 lines
4.3 KiB
Python
"""TA Overlap View"""
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__docformat__ = "numpy"
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import logging
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import os
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from datetime import datetime
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from typing import List, Optional, Union
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import pandas as pd
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from openbb_terminal import OpenBBFigure
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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.helper_funcs import export_data
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from openbb_terminal.rich_config import console
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logger = logging.getLogger(__name__)
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# pylint: disable=too-many-arguments
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@log_start_end(log=logger)
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def view_ma(
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data: pd.Series,
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window: Optional[List[int]] = None,
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offset: int = 0,
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ma_type: str = "EMA",
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symbol: str = "",
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export: str = "",
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sheet_name: Optional[str] = None,
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external_axes: bool = False,
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) -> Union[OpenBBFigure, None]:
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"""Plots MA technical indicator
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Parameters
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----------
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data: pd.Series
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Series of prices
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window: List[int]
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Length of EMA window
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offset: int
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Offset variable
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ma_type: str
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Type of moving average. Either "EMA" "ZLMA" or "SMA"
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symbol: str
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Ticker
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sheet_name: str
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Optionally specify the name of the sheet the data is exported to.
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export: str
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Format to export data
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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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Examples
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--------
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>>> from openbb_terminal.sdk import openbb
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>>> df = openbb.stocks.load("AAPL")
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>>> openbb.ta.ma_chart(data=df["Adj Close"], symbol="AAPL", ma_type="EMA", window=[20, 50, 100])
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>>> from openbb_terminal.sdk import openbb
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>>> spuk_index = openbb.economy.index(indices = ["^SPUK"])
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>>> openbb.ta.ma_chart(data = spuk_index["^SPUK"], symbol = "S&P UK Index", ma_type = "EMA", window = [20, 50, 100])
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"""
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# Define a dataframe for adding EMA series to it
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price_df = pd.DataFrame(data)
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price_df.index.name = "date"
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if not window:
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window = [50]
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ta = PlotlyTA()
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fig = ta.plot(
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data,
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{f"{ma_type.lower()}": dict(length=window, offset=offset)},
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f"{symbol.upper()} {ma_type.upper()}",
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False,
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volume=False,
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)
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export_data(
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export,
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os.path.dirname(os.path.abspath(__file__)).replace("common", "stocks"),
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f"{ma_type.lower()}{'_'.join([str(win) for win in window])}", # type: ignore
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ta.df_ta,
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sheet_name,
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fig,
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)
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return fig.show(external=external_axes)
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@log_start_end(log=logger)
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def view_vwap(
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data: pd.DataFrame,
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symbol: str = "",
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start_date: Optional[datetime] = None,
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end_date: Optional[datetime] = None,
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offset: int = 0,
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interval: str = "",
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export: str = "",
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sheet_name: Optional[str] = None,
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external_axes: bool = False,
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) -> Union[OpenBBFigure, None]:
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"""Plots VWMA technical indicator
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Parameters
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----------
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data : pd.DataFrame
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Dataframe of OHLC prices
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symbol : str
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Ticker
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offset : int
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Offset variable
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start_date: Optional[str]
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Initial date, format YYYY-MM-DD
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end_date: Optional[str]
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Final date, format YYYY-MM-DD
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interval : str
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Interval of data
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export : str
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Format to export data
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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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data.index = data.index.tz_localize(None)
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if start_date is None:
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start = data.index[0].date()
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console.print(f"No start date specified. Start date: {start}")
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else:
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start = datetime.date(start_date)
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if end_date is None:
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end = data.index[-1].date()
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console.print(f"No end date specified. End date: {end}")
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else:
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end = datetime.date(end_date)
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day_df = data[(start <= data.index.date) & (data.index.date <= end)]
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if len(day_df) == 0:
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return console.print(
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f"[red]No data found between {start.strftime('%Y-%m-%d')} and {end.strftime('%Y-%m-%d')}[/red]"
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)
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ta = PlotlyTA()
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fig = ta.plot(
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day_df,
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dict(vwap=dict(offset=offset)),
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f"{symbol.upper()} {interval} VWAP",
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volume=False,
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)
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export_data(
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export,
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os.path.dirname(os.path.abspath(__file__)).replace("common", "stocks"),
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"VWAP",
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ta.df_ta,
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sheet_name,
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fig,
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)
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return fig.show(external=external_axes)
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