Files
sientia-dataops-laborious_t…/laborious/utils/dataframe_utils.py
vitor-aignosi d2b365a34d SIENTIAPDE-1273
Refactor data handling in various modules to ensure DataFrame consistency

- Replaced direct DataFrame instantiation with `ensure_dataframe` utility in Gates, MLFlow, OPC, and ModelMetrics classes to standardize data handling.
- Updated return types in several asynchronous methods to return DataFrames instead of dictionaries for improved usability.
- Adjusted data export processes in workflows to convert DataFrames to dictionaries with `to_dict(orient='records')` for compatibility with downstream systems.
2025-11-14 16:55:00 -03:00

32 lines
825 B
Python

"""
DataFrame utility functions for handling serialized DataFrames.
This module provides helper functions to work with DataFrames that may
come from Temporal serialization (already as DataFrame) or from legacy
code (as dict).
"""
from typing import Any
from pandas import DataFrame
def ensure_dataframe(data: Any) -> DataFrame:
"""
Ensure that data is a DataFrame, converting from dict if necessary.
This function handles both cases:
- Data already deserialized as DataFrame (from Temporal codec)
- Data as dict (legacy format or non-DataFrame serialization)
Args:
data: Data that should be a DataFrame (can be DataFrame or dict)
Returns:
DataFrame: The data as a pandas DataFrame
"""
if isinstance(data, DataFrame):
return data
return DataFrame(data)