feder-cr/Jobs_Applier_AI_Agent_AIHawk · error · TypeError

Error in work_preferences data: {e}

Error message

Error in work_preferences data: {e}

What it means

TypeError from the work_preferences processing block: data['work_preferences'] is not unpackable as **kwargs (string, list, None → 'argument ... is not a mapping'), or WorkPreferences.__init__ rejects a key in the dict ('unexpected keyword argument'). The original TypeError text is carried in {e}, which distinguishes the two cases.

Source

Thrown at src/resume_schemas/job_application_profile.py:128

            raise TypeError(f"Error in legal_authorization data: {e}") from e
        except AttributeError as e:
            logger.error(f"Attribute error in legal_authorization processing: {e}")
            raise AttributeError("Attribute error in legal_authorization processing.") from e
        except Exception as e:
            logger.error(f"An unexpected error occurred while processing legal_authorization: {e}")
            raise RuntimeError("An unexpected error occurred while processing legal_authorization.") from e

        # Process work_preferences
        try:
            logger.debug("Processing work_preferences")
            self.work_preferences = WorkPreferences(**data['work_preferences'])
            logger.debug(f"Work_preferences processed: {self.work_preferences}")
        except KeyError as e:
            logger.error(f"Required field {e} is missing in work_preferences data.")
            raise KeyError(f"Required field {e} is missing in work_preferences data.") from e
        except TypeError as e:
            logger.error(f"Error in work_preferences data: {e}")
            raise TypeError(f"Error in work_preferences data: {e}") from e
        except AttributeError as e:
            logger.error(f"Attribute error in work_preferences processing: {e}")
            raise AttributeError("Attribute error in work_preferences processing.") from e
        except Exception as e:
            logger.error(f"An unexpected error occurred while processing work_preferences: {e}")
            raise RuntimeError("An unexpected error occurred while processing work_preferences.") from e

        # Process availability
        try:
            logger.debug("Processing availability")
            self.availability = Availability(**data['availability'])
            logger.debug(f"Availability processed: {self.availability}")
        except KeyError as e:
            logger.error(f"Required field {e} is missing in availability data.")
            raise KeyError(f"Required field {e} is missing in availability data.") from e
        except TypeError as e:
            logger.error(f"Error in availability data: {e}")
            raise TypeError(f"Error in availability data: {e}") from e

View on GitHub (pinned to 79155b52fa)

Solutions

  1. Verify data['work_preferences'] is a dict; coerce scalars/lists or replace with {}.
  2. Filter the dict to the exact keyword arguments WorkPreferences accepts.
  3. Regenerate or migrate resume files against the current schema after library updates.

Example fix

# before
self.work_preferences = WorkPreferences(**data['work_preferences'])  # value is a list

# after
wp = data.get('work_preferences') or {}
if not isinstance(wp, dict):
    wp = {}
self.work_preferences = WorkPreferences(**wp)
Defensive patterns

Strategy: type-guard

Validate before calling

wp = data.get('work_preferences')
if not isinstance(wp, dict):
    data['work_preferences'] = {}

Type guard

def is_work_preferences_dict(data: dict) -> bool:
    return isinstance(data.get('work_preferences'), dict)

Try / catch

try:
    profile = JobApplicationProfile(**data)
except TypeError as e:
    if 'work_preferences' in str(e) and 'mapping' in str(e):
        data['work_preferences'] = {}
        profile = JobApplicationProfile(**data)

Prevention

When it happens

Trigger: work_preferences: true / work_preferences: [] in YAML; extra keys such as 'timezone' that WorkPreferences doesn't define; calling the constructor with positional args.

Common situations: Hand-written or LLM-generated YAML with wrong shape for the preferences section; library upgrades that renamed/removed WorkPreferences fields while old data files persist.

Understand the failure class

Background: Schema validation failed / invalid input schema: payload rejected because its shape doesn't match the expected schema — this error's family across 28 libraries.

Related errors

AI-assisted analysis of feder-cr/Jobs_Applier_AI_Agent_AIHawk@79155b52fa (2026-08-28). Data as JSON: /api/errors/6d8aec789bdcc2eb. Report an issue: GitHub.