OpenBB/openbb_terminal/etf/fmp_view.py

"""FinancialModelingPrep view"""
__docformat__ = "numpy"

import logging
import os
from typing import Optional

import pandas as pd

from openbb_terminal import OpenBBFigure, theme
from openbb_terminal.decorators import check_api_key, log_start_end
from openbb_terminal.etf import fmp_model
from openbb_terminal.helper_funcs import export_data, print_rich_table
from openbb_terminal.rich_config import console

logger = logging.getLogger(__name__)


@log_start_end(log=logger)
def display_etf_weightings(
    name: str,
    raw: bool = False,
    export: str = "",
    sheet_name: Optional[str] = None,
    external_axes: bool = False,
):
    """Display sector weightings allocation of ETF. [Source: FinancialModelingPrep]

    Parameters
    ----------
    name: str
        ETF name
    raw: bool
        Display sector weighting allocation
    min_pct_to_display: float
        Minimum percentage to display sector
    sheet_name: str
        Optionally specify the name of the sheet the data is exported to.
    export: str
        Type of format to export data
    external_axes : bool, optional
        Whether to return the figure object or not, by default False
    """
    sectors = fmp_model.get_etf_sector_weightings(name)
    if not sectors:
        return console.print("No data was found for that ETF\n")

    title = f"Sector holdings of {name}"

    sector_weights_formatted = {}
    for sector_weight in sectors:
        sector_weights_formatted[sector_weight["sector"]] = (
            float(sector_weight["weightPercentage"].strip("%")) / 100
        )
    sector_weights_formatted = dict(sorted(sector_weights_formatted.items()))

    legend, values = zip(*sector_weights_formatted.items())
    colors = theme.get_colors()

    fig = OpenBBFigure.create_subplots(
        1,
        3,
        specs=[[{"type": "domain"}, {"type": "pie", "colspan": 2}, None]],
        row_heights=[1],
        column_widths=[0.1, 0.8, 0.1],
    )

    fig.add_pie(
        labels=legend,
        values=values,
        textinfo="label+percent",
        hoverinfo="label+percent",
        automargin=True,
        rotation=45,
        row=1,
        col=2,
    )
    fig.update_traces(
        textposition="outside",
        textfont_size=15,
        marker=dict(
            colors=colors,
            line=dict(color="#F5EFF3", width=0.8),
        ),
    )

    fig.update_layout(
        margin=dict(t=40, b=20),
        title=dict(
            text=title,
            y=0.98,
            x=0.5,
            xanchor="center",
            yanchor="top",
        ),
        colorway=colors,
        showlegend=False,
    )

    export_data(
        export,
        os.path.dirname(os.path.abspath(__file__)),
        "weights",
        pd.DataFrame([sector_weights_formatted]).T,
        sheet_name,
        fig,
    )

    if raw:
        sectors_df = pd.DataFrame(sectors).sort_values(by="sector")
        return print_rich_table(
            sectors_df,
            headers=["Sector", "Weight"],
            show_index=False,
            title=f"\n{title}",
            export=bool(export),
        )

    return fig.show(external=external_axes)


@log_start_end(log=logger)
@check_api_key(["API_KEY_FINANCIALMODELINGPREP"])
def view_etf_holdings_performance(
    ticker: str,
    start_date: str,
    end_date: str,
    limit: int = 10,
    raw: bool = False,
    export: str = "",
    sheet_name: Optional[str] = None,
):
    """Display ETF's holdings' performance over specified time. [Source: FinancialModelingPrep]
    Parameters
    ----------
    ticker: str
        ETF ticker.
    start_date: str
        Date from which data is fetched in format YYYY-MM-DD.
    end: str
        Date from which data is fetched in format YYYY-MM-DD.
    limit: int
        Limit number of holdings to view. Sorted by holding percentage (desc).
    raw: bool
        Display holding performance
    sheet_name: str
        Optionally specify the name of the sheet the data is exported to.
    export: str
        Type of format to export data.
    """
    data = fmp_model.get_holdings_pct_change(ticker, start_date, end_date, limit)[::-1]

    if raw:
        print_rich_table(
            data,
            show_index=False,
            headers=["Ticker", "Name", "Percent Change"],
            title="ETF Holdings' Performance",
            limit=limit,
            export=bool(export),
        )

    fig = OpenBBFigure()

    if not raw or fig.is_image_export(export):
        fig.add_bar(
            hovertext=[f"{x:.2f}" + "%" for x in data["Percent Change"]],
            x=data["Percent Change"],
            y=data["Name"],
            name="Stock",
            orientation="h",
            marker_color=[
                "darkgreen" if x > 0 else "darkred" for x in data["Percent Change"]
            ],
        )

        fig.update_layout(
            title=f"Percent Change in Price for Each Holding from {start_date} to {end_date} for {ticker}",
            xaxis=dict(title="Percent Change"),
            yaxis=dict(title="Asset Name"),
        )

    if export:
        export_data(
            export_type=export,
            dir_path=os.path.dirname(os.path.abspath(__file__)),
            func_name=f"{ticker}_holdings_perf",
            df=data,
            sheet_name=sheet_name,
            figure=fig,
        )
        return

    fig.show(external=raw or bool(export))

    return