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result_conversions.py
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result_conversions.py
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from typing import Union, List
from vortexasdk.api.serdes import FromDictMixin
from vortexasdk.logger import get_logger
import pandas as pd
logger = get_logger(__name__)
def create_list(list_of_dicts, output_class: FromDictMixin) -> List:
"""Convert each list element into an instance of the output class."""
logger.debug(f"Converting list of dictionaries to list of {output_class}")
return [output_class.from_dict(d) for d in list_of_dicts]
def format_datatypes(df: pd.DataFrame) -> pd.DataFrame:
"""Format the relevant columns with sensible datatypes"""
timestamp_cols = [col for col in df.columns if "timestamp" in col]
for col in timestamp_cols:
df[col] = pd.to_datetime(df[col])
return df
def create_dataframe(
columns: Union[None, List[str]],
default_columns: List[str],
data: List[dict],
logger_description: str,
) -> pd.DataFrame:
"""
:param columns: Columns to be used in the dataframe
:param default_columns: Default columns to be used if columns is None
:param data: records that will be present in the dataframe
:param logger_description: name of the type of record created. Used for logging.
:return: pd.DataFrame of records with specified columns
"""
logger.debug(f"Creating DataFrame of {logger_description}")
if columns is None:
df = pd.DataFrame(data=data, columns=default_columns)
elif columns == "all":
df = pd.DataFrame(data=data)
else:
df = pd.DataFrame(data=data, columns=columns)
return format_datatypes(df)