import json

import pandas as pd

import pyarrow.parquet as pq

import pyarrow as pa

def deserialize_dataset(data, data_type="json"):

"""

Deserializes dataset input based on the specified data type.

Args:

data (str): The input data as a string.

data_type (str): The type of data (e.g., "json", "parquet").

Returns:

pandas.DataFrame or pyarrow.Table or None: The deserialized dataset

as a pandas DataFrame or

pyarrow Table, or None if

deserialization fails.

"""

try:

if data_type == "json":

# Deserialize JSON data to pandas DataFrame

df = pd.read_json(data)

return df

elif data_type == "parquet":

# Deserialize Parquet data to pyarrow Table

table = pq.read_table(data)

return table

else:

print(f"Error: Unsupported data type: {data_type}")

return None # Return None for unsupported types

except json.JSONDecodeError as e:

print(f"Error decoding JSON: {e}")

return None

except Exception as e:

print(f"Error deserializing dataset: {e}")

return None

if __name__ == '__main__':

# Example Usage (for testing)

# JSON Example

json_data = '{"name": ["Alice", "Bob"], "age": [30, 25]}'

df = deserialize_dataset(json_data, "json")

if df is not None:

print("JSON Deserialized DataFrame:")

print(df)

# Parquet Example

parquet_data = "data=your_parquet_file.parquet" #replace with path to your parquet file

table = deserialize_dataset(parquet_data, "parquet")

if table is not None:

print("\nParquet Deserialized Table:")

print(table)

print(table.schema)

#Example of error handling

invalid_json = '{"name": "Alice", "age": 30' #missing closing bracket

df = deserialize_dataset(invalid_json, "json")

if df is None:

print("\nJSON deserialization failed as expected.")