Update functionality with FinanceDatabase v2, depreciate stocks/sia, fix exe --example and fix stocks/fa/dcf

openbb_terminal/economy/economy_controller.py

@@ -839,6 +839,7 @@ def call_index(self, other_args: List[str]):
             "-q",
             "--query",
             type=str,
+            nargs="+",
             dest="query",
             help="Search for indices with given keyword",
         )
@@ -862,7 +863,8 @@ def call_index(self, other_args: List[str]):
         if ns_parser:
             indices = list_from_str(ns_parser.indices)
             if ns_parser.query and ns_parser.limit:
-                yfinance_view.search_indices(ns_parser.query, ns_parser.limit)
+                query = " ".join(ns_parser.query)
+                yfinance_view.search_indices(query, ns_parser.limit)
                 return self.queue
 
             if ns_parser.show_indices:

openbb_terminal/economy/yfinance_model.py

@@ -738,11 +738,16 @@ def get_search_indices(keyword: list, limit: int = 10) -> pd.DataFrame:
         keyword.replace(",", " ") if isinstance(keyword, str) else " ".join(keyword)  # type: ignore
     )
 
-    indices = fd.select_indices()
-
-    queried_indices = pd.DataFrame.from_dict(
-        fd.search_products(indices, keyword_adjusted, "short_name"), orient="index"
+    indices = fd.Indices()
+
+    queried_indices = indices.search(name=keyword_adjusted, exclude_exchanges=True)
+    queried_indices = pd.concat(
+        [
+            queried_indices,
+            indices.search(index=keyword_adjusted),
+        ]
     )
+    queried_indices = queried_indices.drop_duplicates()
 
     queried_indices = queried_indices.iloc[:limit]
 

openbb_terminal/etf/financedatabase_model.py

@@ -5,6 +5,8 @@
 from typing import Dict, List
 
 import financedatabase as fd
+import numpy as np
+import pandas as pd
 
 from openbb_terminal.decorators import log_start_end
 
@@ -25,8 +27,13 @@ def get_etfs_by_name(name: str) -> Dict:
     data : Dict[str, Any]
         Dictionary with ETFs that match a certain name
     """
-    data = fd.select_etfs()
-    data = fd.search_products(data, query=name, search="long_name")
+    etfs = fd.ETFs()
+
+    data = etfs.search(name=name, exclude_exchanges=True)
+    data = pd.concat([data, etfs.search(index=name, exclude_exchanges=True)])
+
+    # Ensures that data that's missing values is at the bottom of the DataFrame
+    data = data.iloc[np.argsort(-data.isnull().mul(-1).sum(axis=1))]
 
     return data
 
@@ -46,8 +53,12 @@ def get_etfs_by_description(description: str) -> Dict:
     data: Dict[str, Any]
         Dictionary with ETFs that match a certain description
     """
-    data = fd.select_etfs()
-    data = fd.search_products(data, query=description, search="summary")
+    etfs = fd.ETFs()
+
+    data = etfs.search(summary=description, exclude_exchanges=True)
+
+    # Ensures that data that's missing values is at the bottom of the DataFrame
+    data = data.iloc[np.argsort(-data.isnull().mul(-1).sum(axis=1))]
 
     return data
 
@@ -67,7 +78,12 @@ def get_etfs_by_category(category: str) -> Dict:
     data: Dict[str, Any]
         Dictionary with ETFs that match a certain description
     """
-    data = fd.select_etfs(category=category)
+    etfs = fd.ETFs()
+
+    data = etfs.select(category=category, exclude_exchanges=True)
+
+    # Ensures that data that's missing values is at the bottom of the DataFrame
+    data = data.iloc[np.argsort(-data.isnull().mul(-1).sum(axis=1))]
 
     return data
 
@@ -81,5 +97,6 @@ def get_etfs_categories() -> List[str]:
     List[str]
         ETF categories
     """
+    etfs = fd.ETFs()
 
-    return fd.show_options("etfs")
+    return etfs.options("category")

openbb_terminal/etf/financedatabase_view.py

@@ -5,8 +5,6 @@
 import os
 from typing import Optional
 
-import pandas as pd
-
 from openbb_terminal.decorators import log_start_end
 from openbb_terminal.etf import financedatabase_model
 from openbb_terminal.helper_funcs import export_data, print_rich_table
@@ -22,7 +20,7 @@ def display_etf_by_name(
     export: str = "",
     sheet_name: Optional[str] = None,
 ):
-    """Display a selection of ETFs based on name filtered by total assets. [Source: Finance Database]
+    """Display a selection of ETFs based on name. [Source: Finance Database]
 
     Parameters
     ----------
@@ -36,30 +34,25 @@ def display_etf_by_name(
         Type of format to export data
     """
     data = financedatabase_model.get_etfs_by_name(name)
-    if not data:
-        console.print("No data was found with that name\n")
-        return
 
-    table_data = pd.DataFrame(data).T[
-        ["long_name", "family", "category", "total_assets"]
-    ]
+    if data.empty:
+        console.print("No data was found with that name.")
+        return
 
-    # Sort by total assets but it is then dropped due to not being completely up to date
-    table_data_sorted = table_data.sort_values(by="total_assets", ascending=False)
-    table_data_sorted = table_data_sorted.drop("total_assets", axis=1)
+    table_data = data[["name", "family", "category_group", "category"]]
 
     print_rich_table(
-        table_data_sorted.iloc[:limit],
+        table_data.iloc[:limit],
         show_index=True,
-        headers=["Name", "Family", "Category"],
-        title="ETFs by Total Assets",
+        headers=["Name", "Family", "Category Group", "Category"],
+        title="ETFs",
     )
 
     export_data(
         export,
         os.path.dirname(os.path.abspath(__file__)),
         "ln_fd",
-        table_data_sorted,
+        table_data,
         sheet_name,
     )
 
@@ -71,8 +64,7 @@ def display_etf_by_description(
     export: str = "",
     sheet_name: Optional[str] = None,
 ):
-    """Display a selection of ETFs based on description filtered by total assets.
-    [Source: Finance Database]
+    """Display a selection of ETFs based on description. [Source: Finance Database]
 
     Parameters
     ----------
@@ -86,29 +78,25 @@ def display_etf_by_description(
         Type of format to export data
     """
     data = financedatabase_model.get_etfs_by_description(description)
-    if not data:
-        console.print("No data was found with that description\n")
+
+    if data.empty:
+        console.print("No data was found with that description.")
         return
 
-    table_data = pd.DataFrame(data).T[
-        ["long_name", "family", "category", "total_assets"]
-    ]
-    # Sort by total assets but it is then dropped due to not being completely up to date
-    table_data_sorted = table_data.sort_values(by="total_assets", ascending=False)
-    table_data_sorted = table_data_sorted.drop("total_assets", axis=1)
+    table_data = data[["name", "family", "category_group", "category"]]
 
     print_rich_table(
-        table_data_sorted.iloc[:limit],
+        table_data.iloc[:limit],
         show_index=True,
-        headers=["Name", "Family", "Category"],
-        title="ETFs by Total Assets",
+        headers=["Name", "Family", "Category Group", "Category"],
+        title="ETFs",
     )
 
     export_data(
         export,
         os.path.dirname(os.path.abspath(__file__)),
         "ld",
-        data,
+        table_data,
         sheet_name,
     )
 
@@ -120,8 +108,7 @@ def display_etf_by_category(
     export: str = "",
     sheet_name: Optional[str] = None,
 ):
-    """Display a selection of ETFs based on a category filtered by total assets.
-    [Source: Finance Database]
+    """Display a selection of ETFs based on a category. [Source: Finance Database]
 
     Parameters
     ----------
@@ -135,28 +122,24 @@ def display_etf_by_category(
         Type of format to export data
     """
     data = financedatabase_model.get_etfs_by_category(category)
-    if not data:
-        console.print("No data was found on that category\n")
+
+    if data.empty:
+        console.print("No data was found on that category.")
         return
 
-    table_data = pd.DataFrame(data).T[
-        ["long_name", "family", "category", "total_assets"]
-    ]
-    # Sort by total assets but it is then dropped due to not being completely up to date
-    table_data_sorted = table_data.sort_values(by="total_assets", ascending=False)
-    table_data_sorted = table_data_sorted.drop("total_assets", axis=1)
+    table_data = data[["name", "family", "category_group", "category"]]
 
     print_rich_table(
-        table_data_sorted.iloc[:limit],
+        table_data.iloc[:limit],
         show_index=True,
-        headers=["Name", "Family", "Category"],
-        title="ETFs by Category and Total Assets",
+        headers=["Name", "Family", "Category Group", "Category"],
+        title="ETFs by Category",
     )
 
     export_data(
         export,
         os.path.join(os.path.dirname(os.path.abspath(__file__)), "screener"),
         "sbc",
-        data,
+        table_data,
         sheet_name,
     )

openbb_terminal/etf/screener/screener_controller.py

@@ -31,7 +31,7 @@ class ScreenerController(BaseController):
     ]
 
     PRESET_CHOICES = screener_model.get_preset_choices()
-    ETF_CATEGORY_LIST = financedatabase_model.get_etfs_categories()
+    ETF_CATEGORY_LIST = financedatabase_model.get_etfs_categories().tolist()
 
     sortby_screen_choices = [
         "Assets",

openbb_terminal/miscellaneous/i18n/en.yml

@@ -123,7 +123,6 @@ en:
   stocks/th: trading hours,                check open markets
   stocks/options: options menu,                 chains, open interest, greeks, parity
   stocks/disc: discover trending stocks,     map, sectors, high short interest
-  stocks/sia: sector and industry analysis, companies per sector, quick ratio per industry and country
   stocks/dps: dark pool and short data,     darkpool, short interest, ftd
   stocks/scr: screener stocks,              overview/performance, using preset filters
   stocks/ins: insider trading,              latest penny stock buys, top officer purchases
@@ -784,6 +783,7 @@ en:
   economy/qa/raw: print raw data
   economy/qa/decompose: decomposition in cyclic-trend, season, and residuals of prices
   economy/qa/cusum: detects abrupt changes using cumulative sum algorithm of prices
+  fixedincome: Fixed Income
   fixedincome/_reference_rates_: Reference rates
   fixedincome/estr: euro short-term rate (estr)
   fixedincome/sofr: secured overnight financing rate (sofr)
@@ -808,7 +808,7 @@ en:
   fixedincome/spot: display spot rates ranging from 1 year to a 100 years
   fixedincome/hqm: display the High Quality Market (HQM) corporate yield curve
   fixedincome/_spreads_: Spreads
-  fixedincome/icespread: display spread between ICE BofA Corporate Indices and spot treasury curve 
+  fixedincome/icespread: display spread between ICE BofA Corporate Indices and spot treasury curve
   fixedincome/tmc: 10-year treasury constant maturity minus selected treasury constant maturity
   fixedincome/ffrmc: selected treasury constant maturity minus federal funds rate
   fixedincome/tbffr: selected treasury bill minus federal funds rate

openbb_terminal/miscellaneous/routines/routine_example.openbb

@@ -7,11 +7,11 @@ load AAPL
 # Show a candle chart with a 20 day Moving Average
 candle --ma 20
 
-# Switch over to the Due Diligence menu
-dd
+# Switch over to the Fundamental Analysis menu
+fa
 
-# Show analyst ratings
-analyst
+# Show Management
+mgmt
 
 # Show price targets charts
 pt