Set up controller and view flow

openbb_terminal/etf/etf_controller.py

@@ -643,8 +643,8 @@ class ETFController(BaseController):
 
     @log_start_end(log=logger)
     def call_holding_perf(self, other_args: List[str]):
-        print(self.etf_holdings)
         """Process holdings performance command"""
+
         parser = argparse.ArgumentParser(
             add_help=False,
             formatter_class=argparse.ArgumentDefaultsHelpFormatter,
@@ -675,11 +675,13 @@ class ETFController(BaseController):
             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_BOTH_RAW_DATA_AND_FIGURES, raw= True)
+        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(
@@ -687,6 +689,9 @@ class ETFController(BaseController):
                     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_view.py

@@ -6,8 +6,6 @@ import os
 from typing import Optional
 
 import pandas as pd
-import seaborn as sns
-import matplotlib.pyplot as plt
 
 from openbb_terminal import OpenBBFigure, theme
 from openbb_terminal.decorators import check_api_key, log_start_end
@@ -127,17 +125,26 @@ def display_etf_weightings(
 @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 descending percent change.
+        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)[0:limit]
 
-    colors = ['g' if x > 0 else 'r' for x in data['Percent Change']]
-
-    sns.barplot(
-        x= 'Percent Change',
-        y= 'Name',
-        data=data,
-        palette=colors,
-    )
     if raw:
         print_rich_table(
             data,
@@ -148,13 +155,34 @@ def view_etf_holdings_performance(ticker: str, start_date: str, end_date: str, l
             export=bool(export),
         )
 
-    if export:
-        export_data(
-            export,
-            os.path.dirname(os.path.abspath(__file__)),
-            "holdings_perf",
-            data,
-            sheet_name,
+    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']],
         )
 
-    return plt.show()
+        fig.update_layout(
+            title=f"Percent Change from {start_date} to {end_date}",
+            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
+
+    return fig.show(external= raw or export)