Structlog example showing how to serialize polars and pandas dataframes and pydantic models

struct.py

from typing import Any
import json
import structlog
import pandas as pd # pip install pandas
import polars as pl # pip install polars
from pydantic import BaseModel

class PydanticModel(BaseModel):
    a: int
    b: str

df = pl.DataFrame({"a": [1, 2, 3], "b": ["a", "b", "c"]})
df2 = pd.DataFrame({"a": [1, 2, 3], "b": ["a", "b", "c"]})
pydantic_model = PydanticModel(a=1, b="a")

def default(obj: pl.DataFrame | pd.DataFrame | BaseModel) -> dict[str, Any]:
    "Return a JSON serializable version of a DataFrame or Pydantic model."
    if isinstance(obj, pl.DataFrame):
        return json.loads(obj.write_json())
    elif isinstance(obj, pd.DataFrame):
        return json.loads(obj.to_json())
    elif isinstance(obj, BaseModel):
        return obj.model_dump(mode="json")
    raise TypeError(
        f"Object of type {obj.__class__.__name__} is not JSON serializable. "
        "Add entries to the `default` function to support this type."
    )


# BAD
# JSON is just a jsonified version of __repr__
processors = [structlog.processors.JSONRenderer()]
structlog.configure(processors)

log = structlog.stdlib.get_logger()

log.info("polars", df=df)
log.info("pandas", df=df2)
log.info("pydantic", df=pydantic_model)
# {"df": "shape: (3, 2)\n\u250c\u2500\u2500\u2500\u2500\u2500\u252c\u2500\u2500\u2500\u2500\u2500\u2510\n\u2502 a   \u2506 b   \u2502\n\u2502 --- \u2506 --- \u2502\n\u2502 i64 \u2506 str \u2502\n\u255e\u2550\u2550\u2550\u2550\u2550\u256a\u2550\u2550\u2550\u2550\u2550\u2561\n\u2502 1   \u2506 a   \u2502\n\u2502 2   \u2506 b   \u2502\n\u2502 3   \u2506 c   \u2502\n\u2514\u2500\u2500\u2500\u2500\u2500\u2534\u2500\u2500\u2500\u2500\u2500\u2518", "event": "polars"}
# {"df": "   a  b\n0  1  a\n1  2  b\n2  3  c", "event": "pandas"}
# {"df": "PydanticModel(a=1, b='a')", "event": "pydantic"}

# GOOD
# JSON is created from properly serializable objects
processors = [structlog.processors.JSONRenderer(default=default)]
structlog.configure(processors)

log.info("polars", df=df)
log.info("pandas", df=df2)
log.info("pydantic", df=pydantic_model)
# {"df": {"columns": [{"name": "a", "datatype": "Int64", "bit_settings": "", "values": [1, 2, 3]}, {"name": "b", "datatype": "Utf8", "bit_settings": "", "values": ["a", "b", "c"]}]}, "event": "polars"}
# {"df": {"a": {"0": 1, "1": 2, "2": 3}, "b": {"0": "a", "1": "b", "2": "c"}}, "event": "pandas"}
# {"df": {"a": 1, "b": "a"}, "event": "pydantic"}