data_models.md

Data Models & Schemas

The application uses rigorous data validation to ensure that resume data and job application profiles are well-structured.

Resume Schema (src/resume_schemas/resume.py)

The Resume class is defined using Pydantic models, ensuring type safety and validation for user-provided data.

Key Classes

• Resume: The root model containing all sections.
• PersonalInformation: Name, email, phone, location, links.
• EducationDetails: List of education records.
• ExperienceDetails: List of work experience records.
• Project, Achievement, Certifications, Language.

Validation Features:

• Email format validation (EmailStr).
• URL validation for links (HttpUrl).
• normalize_exam_format: Helper to handle inconsistent data formats in YAML.

Job Application Profile (src/resume_schemas/job_application_profile.py)

Defined as a Python dataclass, this model holds user preferences and legal/demographic information often required by job boards.

Sections

• SelfIdentification: Gender, veteran status, disability, ethnicity.
• LegalAuthorization: Work authorization status for US, EU, Canada, UK.
• WorkPreferences: Remote/hybrid preferences, relocation.
• SalaryExpectations: Desired salary range.
• Availability: Notice period.

Data Loading

The Resume and JobApplicationProfile classes both include __init__ methods that accept a YAML string, parsing it into the object structure and raising detailed errors (ValueError, TypeError) if the input validation fails.