feder-cr/Jobs_Applier_AI_Agent_AIHawk · error · TypeError

Error in availability data: {e}

Error message

Error in availability data: {e}

What it means

TypeError raised while processing availability in JobApplicationProfile.__init__: either data['availability'] is not a dict so **-unpacking fails, or Availability.__init__ got an unexpected keyword argument present in the availability mapping. The original TypeError text in {e} tells you which case it is.

Source

Thrown at src/resume_schemas/job_application_profile.py:146

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

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

View on GitHub (pinned to 79155b52fa)

Solutions

  1. Ensure data['availability'] is a dict; if the source is a scalar, wrap it appropriately or default to {}.
  2. Prune keys not accepted by Availability.__init__ before unpacking.
  3. Validate resume files against the current schema after upgrading the library.

Example fix

# before
self.availability = Availability(**data['availability'])  # 'availability: immediate' in YAML

# after
av = data.get('availability') or {}
if not isinstance(av, dict):
    av = {'notice_period': str(av)}
self.availability = Availability(**av)
Defensive patterns

Strategy: type-guard

Validate before calling

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

Type guard

def is_availability_dict(data: dict) -> bool:
    return isinstance(data.get('availability'), dict)

Try / catch

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

Prevention

When it happens

Trigger: availability given as a string ('immediate') or list in YAML; extra unknown keys inside the availability dict; wrong arity when calling Availability programmatically.

Common situations: Human-authored YAML collapsing availability to a scalar; schema drift after Availability gained/lost fields; tool-generated JSON with extra metadata keys inside sections.

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/d71f30f3a577b6fb. Report an issue: GitHub.