Null-Safe Data Access

Write code so nullable/missing data can’t cause runtime errors.

Apply these rules: 1) Declare nullability in types

• If a parameter or field defaults to None, type it as Optional[...].

2) Use safe dict/JSON access

• If a key may be absent, prefer dict.get("key") instead of dict["key"].

3) Guard empty sequences before indexing

• Before using choices[0], rows[0], etc., check the sequence is non-empty (and the expected object shape exists).

4) Use is not None instead of truthiness for config inclusion

• When deciding whether to include a config value, use if value is not None: so meaningful falsy values aren’t accidentally dropped.

Example:

from typing import Optional

def parse_intent(payload: dict) -> Optional[str]:
    # key may be missing -> use get
    return payload.get("rewrited_question")

def handle_response(r):
    # choices may be missing/empty -> guard before indexing
    choices = r.get("choices") if isinstance(r, dict) else getattr(r, "choices", None)
    if not choices:
        return None
    first = choices[0]
    return getattr(first.delta, "content", None)

def build_config(cfg_obj):
    config_dict = {}
    for key in cfg_obj.model_dump().keys():
        value = getattr(cfg_obj, key)
        if value is not None:  # not: if value:
            config_dict[key] = value
    return config_dict

Outcome: fewer KeyError, IndexError, and silent config-misbehavior, while making null/empty cases explicit and testable.