[BugFix] Chunk FMP Price Performance URL For Large Lists

openbb_platform/core/openbb_core/provider/standard_models/etf_holdings.py

@@ -2,7 +2,7 @@
 
 from typing import Optional
 
-from pydantic import Field
+from pydantic import Field, field_validator
 
 from openbb_core.provider.abstract.data import Data
 from openbb_core.provider.abstract.query_params import QueryParams
@@ -17,6 +17,12 @@ class EtfHoldingsQueryParams(QueryParams):
 
     symbol: str = Field(description=QUERY_DESCRIPTIONS.get("symbol", "") + " (ETF)")
 
+    @field_validator("symbol")
+    @classmethod
+    def to_upper(cls, v: str) -> str:
+        """Convert field to uppercase."""
+        return v.upper()
+
 
 class EtfHoldingsData(Data):
     """ETF Holdings Data."""

openbb_platform/extensions/etf/openbb_etf/etf_router.py

@@ -1,5 +1,6 @@
 """ETF Router."""
 
+from openbb_core.app.deprecation import OpenBBDeprecationWarning
 from openbb_core.app.model.command_context import CommandContext
 from openbb_core.app.model.example import APIEx
 from openbb_core.app.model.obbject import OBBject
@@ -172,6 +173,13 @@ async def holdings_date(
 
 @router.command(
     model="EtfHoldingsPerformance",
+    deprecated=True,
+    deprecation=OpenBBDeprecationWarning(
+        message="This endpoint is deprecated; pass a list of holdings symbols directly to"
+        + " `/equity/price/performance` instead.",
+        since=(4, 1),
+        expected_removal=(4, 2),
+    ),
     examples=[APIEx(parameters={"symbol": "XLK", "provider": "fmp"})],
 )
 async def holdings_performance(

openbb_platform/openbb/assets/reference.json

@@ -5350,6 +5350,20 @@
                         "default": null,
                         "optional": true
                     },
+                    {
+                        "name": "smart_score_1m",
+                        "type": "float",
+                        "description": "A weighted average smart score over the last month.",
+                        "default": null,
+                        "optional": true
+                    },
+                    {
+                        "name": "success_rate_1m",
+                        "type": "float",
+                        "description": "The percentage (normalized) of gain/loss ratings that resulted in a gain over the last month",
+                        "default": null,
+                        "optional": true
+                    },
                     {
                         "name": "gain_count_3m",
                         "type": "int",
@@ -5378,6 +5392,20 @@
                         "default": null,
                         "optional": true
                     },
+                    {
+                        "name": "smart_score_3m",
+                        "type": "float",
+                        "description": "A weighted average smart score over the last 3 months.",
+                        "default": null,
+                        "optional": true
+                    },
+                    {
+                        "name": "success_rate_3m",
+                        "type": "float",
+                        "description": "The percentage (normalized) of gain/loss ratings that resulted in a gain over the last 3 months",
+                        "default": null,
+                        "optional": true
+                    },
                     {
                         "name": "gain_count_6m",
                         "type": "int",
@@ -5434,6 +5462,20 @@
                         "default": null,
                         "optional": true
                     },
+                    {
+                        "name": "smart_score_9m",
+                        "type": "float",
+                        "description": "A weighted average smart score over the last 9 months.",
+                        "default": null,
+                        "optional": true
+                    },
+                    {
+                        "name": "success_rate_9m",
+                        "type": "float",
+                        "description": "The percentage (normalized) of gain/loss ratings that resulted in a gain over the last 9 months",
+                        "default": null,
+                        "optional": true
+                    },
                     {
                         "name": "gain_count_1y",
                         "type": "int",
@@ -5462,6 +5504,20 @@
                         "default": null,
                         "optional": true
                     },
+                    {
+                        "name": "smart_score_1y",
+                        "type": "float",
+                        "description": "A weighted average smart score over the last 1 year.",
+                        "default": null,
+                        "optional": true
+                    },
+                    {
+                        "name": "success_rate_1y",
+                        "type": "float",
+                        "description": "The percentage (normalized) of gain/loss ratings that resulted in a gain over the last 1 year",
+                        "default": null,
+                        "optional": true
+                    },
                     {
                         "name": "gain_count_2y",
                         "type": "int",
@@ -5490,6 +5546,20 @@
                         "default": null,
                         "optional": true
                     },
+                    {
+                        "name": "smart_score_2y",
+                        "type": "float",
+                        "description": "A weighted average smart score over the last 3 years.",
+                        "default": null,
+                        "optional": true
+                    },
+                    {
+                        "name": "success_rate_2y",
+                        "type": "float",
+                        "description": "The percentage (normalized) of gain/loss ratings that resulted in a gain over the last 2 years",
+                        "default": null,
+                        "optional": true
+                    },
                     {
                         "name": "gain_count_3y",
                         "type": "int",
@@ -5517,6 +5587,20 @@
                         "description": "The standard deviation in percent (normalized) price difference in the analyst's ratings over the last 3 years",
                         "default": null,
                         "optional": true
+                    },
+                    {
+                        "name": "smart_score_3y",
+                        "type": "float",
+                        "description": "A weighted average smart score over the last 3 years.",
+                        "default": null,
+                        "optional": true
+                    },
+                    {
+                        "name": "success_rate_3y",
+                        "type": "float",
+                        "description": "The percentage (normalized) of gain/loss ratings that resulted in a gain over the last 3 years",
+                        "default": null,
+                        "optional": true
                     }
                 ]
             },
@@ -23216,8 +23300,8 @@
         },
         "/etf/holdings_performance": {
             "deprecated": {
-                "flag": null,
-                "message": null
+                "flag": true,
+                "message": "This endpoint is deprecated; pass a list of holdings symbols directly to `/equity/price/performance` instead. Deprecated in OpenBB Platform V4.1 to be removed in V4.2."
             },
             "description": "Get the recent price performance of each ticker held in the ETF.",
             "examples": "\nExamples\n--------\n\n```python\nfrom openbb import obb\nobb.etf.holdings_performance(symbol='XLK', provider='fmp')\n```\n\n",

openbb_platform/openbb/package/equity_estimates.py

@@ -126,6 +126,10 @@ def analyst_search(
             The average percent (normalized) price difference per rating over the last month (provider: benzinga)
         std_dev_1m : Optional[float]
             The standard deviation in percent (normalized) price difference in the analyst's ratings over the last month (provider: benzinga)
+        smart_score_1m : Optional[float]
+            A weighted average smart score over the last month. (provider: benzinga)
+        success_rate_1m : Optional[float]
+            The percentage (normalized) of gain/loss ratings that resulted in a gain over the last month (provider: benzinga)
         gain_count_3m : Optional[int]
             The number of ratings that have gained value over the last 3 months (provider: benzinga)
         loss_count_3m : Optional[int]
@@ -134,6 +138,10 @@ def analyst_search(
             The average percent (normalized) price difference per rating over the last 3 months (provider: benzinga)
         std_dev_3m : Optional[float]
             The standard deviation in percent (normalized) price difference in the analyst's ratings over the last 3 months (provider: benzinga)
+        smart_score_3m : Optional[float]
+            A weighted average smart score over the last 3 months. (provider: benzinga)
+        success_rate_3m : Optional[float]
+            The percentage (normalized) of gain/loss ratings that resulted in a gain over the last 3 months (provider: benzinga)
         gain_count_6m : Optional[int]
             The number of ratings that have gained value over the last 6 months (provider: benzinga)
         loss_count_6m : Optional[int]
@@ -150,6 +158,10 @@ def analyst_search(
             The average percent (normalized) price difference per rating over the last 9 months (provider: benzinga)
         std_dev_9m : Optional[float]
             The standard deviation in percent (normalized) price difference in the analyst's ratings over the last 9 months (provider: benzinga)
+        smart_score_9m : Optional[float]
+            A weighted average smart score over the last 9 months. (provider: benzinga)
+        success_rate_9m : Optional[float]
+            The percentage (normalized) of gain/loss ratings that resulted in a gain over the last 9 months (provider: benzinga)
         gain_count_1y : Optional[int]
             The number of ratings that have gained value over the last 1 year (provider: benzinga)
         loss_count_1y : Optional[int]
@@ -158,6 +170,10 @@ def analyst_search(
             The average percent (normalized) price difference per rating over the last 1 year (provider: benzinga)
         std_dev_1y : Optional[float]
             The standard deviation in percent (normalized) price difference in the analyst's ratings over the last 1 year (provider: benzinga)
+        smart_score_1y : Optional[float]
+            A weighted average smart score over the last 1 year. (provider: benzinga)
+        success_rate_1y : Optional[float]
+            The percentage (normalized) of gain/loss ratings that resulted in a gain over the last 1 year (provider: benzinga)
         gain_count_2y : Optional[int]
             The number of ratings that have gained value over the last 2 years (provider: benzinga)
         loss_count_2y : Optional[int]
@@ -166,6 +182,10 @@ def analyst_search(
             The average percent (normalized) price difference per rating over the last 2 years (provider: benzinga)
         std_dev_2y : Optional[float]
             The standard deviation in percent (normalized) price difference in the analyst's ratings over the last 2 years (provider: benzinga)
+        smart_score_2y : Optional[float]
+            A weighted average smart score over the last 3 years. (provider: benzinga)
+        success_rate_2y : Optional[float]
+            The percentage (normalized) of gain/loss ratings that resulted in a gain over the last 2 years (provider: benzinga)
         gain_count_3y : Optional[int]
             The number of ratings that have gained value over the last 3 years (provider: benzinga)
         loss_count_3y : Optional[int]
@@ -174,6 +194,10 @@ def analyst_search(
             The average percent (normalized) price difference per rating over the last 3 years (provider: benzinga)
         std_dev_3y : Optional[float]
             The standard deviation in percent (normalized) price difference in the analyst's ratings over the last 3 years (provider: benzinga)
+        smart_score_3y : Optional[float]
+            A weighted average smart score over the last 3 years. (provider: benzinga)
+        success_rate_3y : Optional[float]
+            The percentage (normalized) of gain/loss ratings that resulted in a gain over the last 3 years (provider: benzinga)
 
         Examples
         --------

openbb_platform/openbb/package/etf.py

@@ -2,13 +2,15 @@
 
 import datetime
 from typing import List, Literal, Optional, Union
+from warnings import simplefilter, warn
 
+from openbb_core.app.deprecation import OpenBBDeprecationWarning
 from openbb_core.app.model.custom_parameter import OpenBBCustomParameter
 from openbb_core.app.model.obbject import OBBject
 from openbb_core.app.static.container import Container
 from openbb_core.app.static.utils.decorators import exception_handler, validate
 from openbb_core.app.static.utils.filters import filter_inputs
-from typing_extensions import Annotated
+from typing_extensions import Annotated, deprecated
 
 
 class ROUTER_etf(Container):
@@ -698,6 +700,10 @@ def holdings_date(
 
     @exception_handler
     @validate
+    @deprecated(
+        "This endpoint is deprecated; pass a list of holdings symbols directly to `/equity/price/performance` instead. Deprecated in OpenBB Platform V4.1 to be removed in V4.2.",
+        category=OpenBBDeprecationWarning,
+    )
     def holdings_performance(
         self,
         symbol: Annotated[
@@ -782,6 +788,13 @@ def holdings_performance(
         >>> obb.etf.holdings_performance(symbol='XLK', provider='fmp')
         """  # noqa: E501
 
+        simplefilter("always", DeprecationWarning)
+        warn(
+            "This endpoint is deprecated; pass a list of holdings symbols directly to `/equity/price/performance` instead. Deprecated in OpenBB Platform V4.1 to be removed in V4.2.",
+            category=DeprecationWarning,
+            stacklevel=2,
+        )
+
         return self._run(
             "/etf/holdings_performance",
             **filter_inputs(

openbb_platform/providers/fmp/openbb_fmp/models/etf_holdings.py

@@ -137,7 +137,7 @@ def normalize_percent(cls, v):
     def replace_empty(cls, v):
         """Replace empty strings and 0s with None."""
         if isinstance(v, str):
-            return v if v not in ("", "0") else None
+            return v if v not in ("", "0", "-") else None
         if isinstance(v, (float, int)):
             return v if v and v not in (0.0, 0) else None
         return v if v else None

openbb_platform/providers/fmp/openbb_fmp/models/etf_holdings_performance.py

@@ -54,7 +54,7 @@ async def aextract_data(
         # Split into chunks of 500
         chunks = [holdings_list[i : i + 500] for i in range(0, len(holdings_list), 500)]
         # Get price performance for the holdings
-        holdings_performance: list = []
+        holdings_performance: List[Dict] = []
         for holding_chunk in chunks:
             holdings_str = (
                 ",".join(holding_chunk) if len(holding_chunk) > 1 else holding_chunk[0]

openbb_platform/providers/fmp/openbb_fmp/models/price_performance.py

@@ -9,7 +9,7 @@
     RecentPerformanceData,
     RecentPerformanceQueryParams,
 )
-from openbb_fmp.utils.helpers import create_url, get_data_many
+from openbb_fmp.utils.helpers import create_url, get_data_urls
 from pydantic import Field, model_validator
 
 
@@ -71,14 +71,23 @@ async def aextract_data(
     ) -> List[Dict]:
         """Return the raw data from the FMP endpoint."""
         api_key = credentials.get("fmp_api_key") if credentials else ""
-
-        url = create_url(
-            version=3,
-            endpoint=f"stock-price-change/{query.symbol}",
-            api_key=api_key,
-            exclude=["symbol"],
-        )
-        return await get_data_many(url, **kwargs)
+        symbols = query.symbol.upper().split(",")
+        symbols = list(dict.fromkeys(symbols))
+        chunk_size = 200
+        chunks = [
+            symbols[i : i + chunk_size] for i in range(0, len(symbols), chunk_size)
+        ]
+        urls = [
+            create_url(
+                version=3,
+                endpoint=f"stock-price-change/{','.join(chunk)}",
+                api_key=api_key,
+                exclude=["symbol"],
+            )
+            for chunk in chunks
+        ]
+        data = await get_data_urls(urls, **kwargs)
+        return data
 
     @staticmethod
     def transform_data(
@@ -88,7 +97,8 @@ def transform_data(
     ) -> List[FMPPricePerformanceData]:
         """Return the transformed data."""
 
-        symbols = query.symbol.split(",")
+        symbols = query.symbol.upper().split(",")
+        symbols = list(dict.fromkeys(symbols))
         if len(data) != len(symbols):
             data_symbols = [d["symbol"] for d in data]
             missing_symbols = [