Improving economy.cpi for the FRED data

openbb_platform/platform/provider/openbb_provider/standard_models/cpi.py

@@ -2,6 +2,7 @@
 from datetime import date as dateType
 from typing import List, Literal, Optional
 
+from dateutil import parser
 from pydantic import Field, field_validator
 
 from openbb_provider.abstract.data import Data
@@ -91,15 +92,10 @@ class CPIQueryParams(QueryParams):
 class CPIData(Data):
     """CPI data."""
 
-    date: Optional[dateType] = Field(
-        default=None, description=DATA_DESCRIPTIONS.get("date")
-    )
-    value: Optional[float] = Field(default=None, description="CPI value on the date.")
+    date: dateType = Field(description=DATA_DESCRIPTIONS.get("date"))
 
-    @field_validator("value", mode="before")
+    @field_validator("date", mode="before")
     @classmethod
-    def value_validate(cls, v: str):  # pylint: disable=E0213
-        """Validate value."""
-        if v == ".":
-            return 0.0
-        return float(v)
+    def date_validate(cls, v):
+        """Validate date."""
+        return parser.isoparse(v)

openbb_platform/platform/provider/openbb_provider/utils/descriptions.py

@@ -11,8 +11,12 @@
     "date": "A specific date to get data for.",
     "limit": "The number of data entries to return.",
     "countries": "The country or countries to get data.",
-    "units": "The data units.",
-    "frequency": "The data time frequency.",
+    "units": """The unit of measurement for the CPI data.
+    Options:
+    - `growth_previous`: growth from the previous period
+    - `growth_same`: growth from the same period in the previous year
+    - `index_2015`: index with base year 2015.""",
+    "frequency": "The frequency of the data points; options include `monthly`, `quarter`, and `annual`",
 }
 
 DATA_DESCRIPTIONS = {

openbb_platform/providers/fred/openbb_fred/models/cpi.py

@@ -17,19 +17,17 @@ class FREDCPIData(CPIData):
     """CPI data."""
 
 
-class FREDCPIFetcher(Fetcher[FREDCPIQueryParams, List[Dict[str, List[FREDCPIData]]]]):
+class FREDCPIFetcher(Fetcher[FREDCPIQueryParams, List[FREDCPIData]]):
     """FRED CPI Fetcher."""
 
-    data_type = FREDCPIData
-
     @staticmethod
     def transform_query(params: Dict[str, Any]) -> FREDCPIQueryParams:
         return FREDCPIQueryParams(**params)
 
     @staticmethod
     def extract_data(
         query: FREDCPIQueryParams, credentials: Optional[Dict[str, str]], **kwargs: Any
-    ) -> dict:
+    ) -> Dict:
         api_key = credentials.get("fred_api_key") if credentials else ""
 
         all_options = all_cpi_options(query.harmonized)
@@ -41,23 +39,31 @@ def extract_data(
         series_dict = {}
         fred = Fred(api_key)
         for item in step_3:
-            loc = f"{item['country']}-{item['frequency']}-{item['units']}"
+            loc = f"{item['country']}"
             temp = fred.get_series(
                 item["series_id"], query.start_date, query.end_date, **kwargs
             )
-            series_dict[loc] = temp
+            temp = [{"date": item["date"], "value": item["value"]} for item in temp]
+            series_dict[loc] = [item for item in temp if item["value"] != "."]
 
         return series_dict
 
     @staticmethod
     def transform_data(
-        query: FREDCPIQueryParams, data: dict, **kwargs: Any
-    ) -> List[Dict[str, List[FREDCPIData]]]:
-        for key, value in data.items():
-            data[key] = [
-                FREDCPIData(date=x["date"], value=x["value"])
-                for x in value
-                if x["value"] != "."
-            ]
-
-        return [data]
+        query: FREDCPIQueryParams, data: Dict, **kwargs: Any
+    ) -> List[FREDCPIData]:
+        transformed_data = {}
+
+        # Iterate over the series_dict
+        for country, data_list in data.items():
+            for item in data_list:
+                # If the date is not in the dictionary, add it
+                if item["date"] not in transformed_data:
+                    transformed_data[item["date"]] = {"date": item["date"]}
+                # Update the dictionary with the country's value data
+                transformed_data[item["date"]].update({country: item["value"]})
+
+        # Convert the dictionary to a list of dictionaries
+        transformed_data = list(transformed_data.values())
+
+        return [FREDCPIData.model_validate(item) for item in transformed_data]