feder-cr/Jobs_Applier_AI_Agent_AIHawk · error · TypeError

Error in salary_expectations data: {e}

Error message

Error in salary_expectations data: {e}

What it means

TypeError from the salary_expectations processing: data['salary_expectations'] is not a dict (so ** unpacking raises 'not a mapping'), or the dict contains a key SalaryExpectations.__init__ does not accept ('unexpected keyword argument'). The {e} interpolation preserves the original TypeError message distinguishing the two.

Source

Thrown at src/resume_schemas/job_application_profile.py:164

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

        logger.debug("JobApplicationProfile initialization completed successfully.")

    def __str__(self):
        logger.debug("Generating string representation of JobApplicationProfile")

        def format_dataclass(obj):
            return "\n".join(f"{field.name}: {getattr(obj, field.name)}" for field in obj.__dataclass_fields__.values())

        formatted_str = (f"Self Identification:\n{format_dataclass(self.self_identification)}\n\n"
                         f"Legal Authorization:\n{format_dataclass(self.legal_authorization)}\n\n"
                         f"Work Preferences:\n{format_dataclass(self.work_preferences)}\n\n"

View on GitHub (pinned to 79155b52fa)

Solutions

  1. Ensure the section is a dict with exactly the keys SalaryExpectations accepts.
  2. Convert scalar forms into the expected dict shape or use {} as default.
  3. Re-validate resume files against the current schema after library upgrades.

Example fix

# before
self.salary_expectations = SalaryExpectations(**data['salary_expectations'])  # value: 80000

# after
se = data.get('salary_expectations') or {}
if not isinstance(se, dict):
    se = {'amount': se, 'currency': 'USD'}
self.salary_expectations = SalaryExpectations(**se)
Defensive patterns

Strategy: type-guard

Validate before calling

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

Type guard

def is_salary_expectations_dict(data: dict) -> bool:
    return isinstance(data.get('salary_expectations'), dict)

Try / catch

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

Prevention

When it happens

Trigger: salary_expectations: 80000 (a bare number) in YAML; a list of ranges; extra keys like 'negotiable: true' not present in the constructor signature.

Common situations: Hand-written resume YAML using scalar salary values; older data files against a newer schema; extra keys injected by upstream tooling.

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/365550f0d74c70ef. Report an issue: GitHub.