Feature/add etf holding performance

openbb_terminal/etf/etf_controller.py

@@ -50,6 +50,7 @@ class ETFController(BaseController):
         "load",
         "overview",
         "holdings",
+        "holding_perf",
         "news",
         "candle",
         "weights",
@@ -106,6 +107,7 @@ def print_help(self):
         mt.add_raw("\n")
         mt.add_cmd("overview", self.etf_name)
         mt.add_cmd("holdings", self.etf_name)
+        mt.add_cmd("holding_perf", self.etf_name)
         mt.add_cmd("weights", self.etf_name)
         mt.add_cmd("news", self.etf_name)
         mt.add_cmd("candle", self.etf_name)
@@ -638,3 +640,60 @@ def call_compare(self, other_args):
                 if ns_parser.sheet_name
                 else None,
             )
+
+    @log_start_end(log=logger)
+    def call_holding_perf(self, other_args: List[str]):
+        """Process holdings performance command"""
+
+        parser = argparse.ArgumentParser(
+            add_help=False,
+            formatter_class=argparse.ArgumentDefaultsHelpFormatter,
+            prog="holding_perf",
+            description="Look at ETF company holdings' performance",
+        )
+        parser.add_argument(
+            "-s",
+            "--start-date",
+            type=valid_date,
+            default=(datetime.now().date() - timedelta(days=366)),
+            dest="start",
+            help="The starting date (format YYYY-MM-DD) to get each holding's price",
+        )
+        parser.add_argument(
+            "-e",
+            "--end-date",
+            type=valid_date,
+            default=datetime.now().date(),
+            dest="end",
+            help="The ending date (format YYYY-MM-DD) to get each holding's price",
+        )
+        parser.add_argument(
+            "-l",
+            "--limit",
+            type=check_positive,
+            dest="limit",
+            help="Number of holdings to get",
+            default=20,
+        )
+        if other_args and "-" not in other_args[0][0]:
+            other_args.insert(0, "-l")
+
+        ns_parser = self.parse_known_args_and_warn(
+            parser,
+            other_args,
+            export_allowed=EXPORT_BOTH_RAW_DATA_AND_FIGURES,
+            raw=True,
+        )
+        if ns_parser:
+            if self.etf_name:
+                fmp_view.view_etf_holdings_performance(
+                    ticker=self.etf_name,
+                    start_date=ns_parser.start,
+                    end_date=ns_parser.end,
+                    limit=ns_parser.limit,
+                    export=ns_parser.export,
+                    sheet_name=ns_parser.sheet_name,
+                    raw=ns_parser.raw,
+                )
+            else:
+                console.print("Please load a ticker using <load name>. \n")

openbb_terminal/etf/fmp_model.py

@@ -3,13 +3,16 @@
 
 import json
 import logging
-from typing import Dict
+from typing import Any, Dict, List
 from urllib.error import HTTPError
 from urllib.request import urlopen
 
+import pandas as pd
+
 from openbb_terminal.core.session.current_user import get_current_user
-from openbb_terminal.decorators import log_start_end
-from openbb_terminal.rich_config import console
+from openbb_terminal.decorators import check_api_key, log_start_end
+from openbb_terminal.helper_funcs import request
+from openbb_terminal.rich_config import console, optional_rich_track
 
 logger = logging.getLogger(__name__)
 
@@ -47,3 +50,158 @@ def get_etf_sector_weightings(name: str) -> Dict:
         raise ValueError(data["Error Message"])
 
     return data
+
+
+@log_start_end(log=logger)
+@check_api_key(["API_KEY_FINANCIALMODELINGPREP"])
+def get_stock_price_change(
+    tickers: List[str], start_date: str, end_date: str
+) -> Dict[str, float]:
+    """Get stock's price percent change over specified time period.
+
+    Parameters
+    ----------
+    tickers : List[str]
+        Ticker(s) to get information for.
+    start: 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
+
+    Returns
+    -------
+    Dict[str, float]
+        Percent change of closing price over time period, or dictionary of ticker, change pairs.
+    """
+    tickers_tracker = optional_rich_track(
+        tickers, False, "Gathering stock prices", len(tickers)
+    )
+    current_user = get_current_user()
+    data_aggregate = dict()
+
+    for tick in tickers_tracker:
+        tickers_req = str(tick) + ","
+        for _ in range(4):
+            try:
+                _tick = next(tickers_tracker)
+                tickers_req += _tick + ","
+            except StopIteration:
+                break
+
+        url = f"""https://financialmodelingprep.com/api/v3/historical-price-full/{tickers_req}?\
+from={start_date}&to={end_date}&serietype=line\
+&apikey={current_user.credentials.API_KEY_FINANCIALMODELINGPREP}"""
+
+        response = request(url)
+        if response.status_code != 200 or "Error Message" in response.json():
+            message = f"Error, Status Code: {response.status_code}."
+            message = (
+                message
+                if "Error Message" not in response.json()
+                else message + "\n" + response.json()["Error Message"] + ".\n"
+            )
+            console.print(message)
+            return dict()
+
+        data = response.json()
+        stock_list = data
+        if "historicalStockList" in data:
+            stock_list = data["historicalStockList"]
+
+        for stock in stock_list:
+            close_end = stock["historical"][0]["close"]
+            close_start = stock["historical"][-1]["close"]
+            pct_change = 100 * (close_end - close_start) / close_start
+            data_aggregate[stock["symbol"]] = pct_change
+
+    return data_aggregate
+
+
+@log_start_end(log=logger)
+@check_api_key(["API_KEY_FINANCIALMODELINGPREP"])
+def get_etf_holdings(ticker: str, limit: int = 10) -> List[Dict[str, Any]]:
+    """This endpoint returns all stocks held by a specific ETF.
+
+    Parameters
+    ----------
+    ticker : str
+        ETF ticker.
+    limit: int
+        Limit amount of stocks to return. FMP returns data
+        by descending weighting.
+
+    Returns
+    -------
+    List[Dict[str,any]]
+        Info for stock holdings in the ETF.
+    """
+
+    current_user = get_current_user()
+    url = f"""https://financialmodelingprep.com/api/v3/etf-holder/{ticker}\
+?apikey={current_user.credentials.API_KEY_FINANCIALMODELINGPREP}"""
+    response = request(url)
+    if response.status_code != 200 or "Error Message" in response.json():
+        message = f"Error, Status Code: {response.status_code}."
+        message = (
+            message
+            if "Error Message" not in response.json()
+            else message + "\n" + response.json()["Error Message"] + ".\n"
+        )
+        console.print(message)
+        return []
+
+    return response.json()[0:limit]
+
+
+@log_start_end(log=logger)
+@check_api_key(["API_KEY_FINANCIALMODELINGPREP"])
+def get_holdings_pct_change(
+    ticker: str,
+    start_date: str,
+    end_date: str,
+    limit: int = 10,
+) -> pd.DataFrame:
+    """Calculate percent change for each holding in ETF.
+
+    Parameters
+    ----------
+    ticker : str
+        ETF ticker.
+    limit: int
+        Limit amount of stocks to return. FMP returns data
+        by descending weighting.
+
+    Returns
+    -------
+    pd.DataFrame
+        Calculated percentage change for each stock in the ETF, in descending order.
+    """
+
+    df = pd.DataFrame(columns=["Ticker", "Name", "Percent Change"], data=[])
+    holdings = get_etf_holdings(ticker, limit)
+    tickers = []
+    for stock in holdings:
+        tickers.append(stock.get("asset", " "))
+
+    pct_changes = get_stock_price_change(tickers, start_date, end_date)
+
+    for stock in holdings:
+        pct_change = pct_changes.get(stock["asset"], 0)
+        if pct_change == 0:
+            console.print(
+                f"""Percent change not found for: {stock["asset"]}: {stock["name"]}"""
+            )
+        new_df = pd.DataFrame(
+            {
+                "Ticker": stock["asset"],
+                "Name": stock["name"],
+                "Percent Change": pct_changes.get(stock["asset"], 0),
+            },
+            index=[0],
+        )
+
+        df = pd.concat([df, new_df], ignore_index=True)
+
+    sorted_df = df.sort_values(by="Percent Change", ascending=False, inplace=False)
+
+    return sorted_df

openbb_terminal/etf/fmp_view.py

@@ -8,12 +8,9 @@
 import pandas as pd
 
 from openbb_terminal import OpenBBFigure, theme
-from openbb_terminal.decorators import log_start_end
+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.helper_funcs import export_data, print_rich_table
 from openbb_terminal.rich_config import console
 
 logger = logging.getLogger(__name__)
@@ -120,3 +117,80 @@ def display_etf_weightings(
         )
 
     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

openbb_terminal/miscellaneous/i18n/en.yml

@@ -702,6 +702,7 @@ en:
   etf/scr: screener ETFs                 overview/performance, using preset filters
   etf/overview: get overview
   etf/holdings: top company holdings
+  etf/holding_perf: Performance of holdings in ETF.
   etf/weights: sector weights allocation
   etf/candle: view a candle chart for ETF
   etf/news: latest news of the company

openbb_terminal/miscellaneous/integration_tests_scripts/etf/test_etf.openbb

@@ -2,6 +2,7 @@ etf
 load spy
 overview
 holdings
+holdings_perf --limit 3
 weights
 weights --raw
 candle