diff options
Diffstat (limited to 'openbb_platform/core/openbb_core/app/model/metadata.py')
| -rw-r--r-- | openbb_platform/core/openbb_core/app/model/metadata.py | 30 |
1 files changed, 19 insertions, 11 deletions
diff --git a/openbb_platform/core/openbb_core/app/model/metadata.py b/openbb_platform/core/openbb_core/app/model/metadata.py index e5ea6a0f5bf..eca37b061f9 100644 --- a/openbb_platform/core/openbb_core/app/model/metadata.py +++ b/openbb_platform/core/openbb_core/app/model/metadata.py @@ -1,6 +1,8 @@ +"""Metadata model.""" + from datetime import datetime from inspect import isclass -from typing import Any, Dict +from typing import Any, Dict, Optional, Sequence, Union import numpy as np import pandas as pd @@ -10,6 +12,8 @@ from openbb_core.provider.abstract.data import Data class Metadata(BaseModel): + """Metadata of a command execution.""" + arguments: Dict[str, Any] = Field( default_factory=dict, description="Arguments of the command.", @@ -21,6 +25,7 @@ class Metadata(BaseModel): timestamp: datetime = Field(description="Execution starting timestamp.") def __repr__(self) -> str: + """Return string representation.""" return f"{self.__class__.__name__}\n\n" + "\n".join( f"{k}: {v}" for k, v in self.model_dump().items() ) @@ -29,6 +34,7 @@ class Metadata(BaseModel): @classmethod def scale_arguments(cls, v): """Scale arguments. + This function is meant to limit the size of the input arguments of a command. If the type is one of the following: `Data`, `List[Data]`, `DataFrame`, `List[DataFrame]`, `Series`, `List[Series]` or `ndarray`, the value of the argument is swapped by a dictionary @@ -36,7 +42,7 @@ class Metadata(BaseModel): value is kept or trimmed to 80 characters. """ for arg, arg_val in v.items(): - new_arg_val = None + new_arg_val: Optional[Union[str, dict[str, Sequence[Any]]]] = None # Data if isclass(type(arg_val)) and issubclass(type(arg_val), Data): @@ -47,30 +53,32 @@ class Metadata(BaseModel): # List[Data] if isinstance(arg_val, list) and issubclass(type(arg_val[0]), Data): - columns = [list(d.model_dump().keys()) for d in arg_val] - columns = (item for sublist in columns for item in sublist) # flatten + _columns = [list(d.model_dump().keys()) for d in arg_val] + ld_columns = ( + item for sublist in _columns for item in sublist + ) # flatten new_arg_val = { "type": f"List[{type(arg_val[0]).__name__}]", - "columns": list(set(columns)), + "columns": list(set(ld_columns)), } # DataFrame elif isinstance(arg_val, pd.DataFrame): - columns = ( + df_columns = ( list(arg_val.index.names) + arg_val.columns.tolist() if any(index is not None for index in list(arg_val.index.names)) else arg_val.columns.tolist() ) new_arg_val = { "type": f"{type(arg_val).__name__}", - "columns": columns, + "columns": df_columns, } # List[DataFrame] elif isinstance(arg_val, list) and issubclass( type(arg_val[0]), pd.DataFrame ): - columns = [ + ldf_columns = [ ( list(df.index.names) + df.columns.tolist() if any(index is not None for index in list(df.index.names)) @@ -80,7 +88,7 @@ class Metadata(BaseModel): ] new_arg_val = { "type": f"List[{type(arg_val[0]).__name__}]", - "columns": columns, + "columns": ldf_columns, } # Series @@ -92,7 +100,7 @@ class Metadata(BaseModel): # List[Series] elif isinstance(arg_val, list) and isinstance(arg_val[0], pd.Series): - columns = [ + ls_columns = [ ( list(series.index.names) + [series.name] if any(index is not None for index in list(series.index.names)) @@ -102,7 +110,7 @@ class Metadata(BaseModel): ] new_arg_val = { "type": f"List[{type(arg_val[0]).__name__}]", - "columns": columns, + "columns": ls_columns, } # ndarray |