3 Repos
Structured data definitions for resume sections that support template mapping.
Distinct from Data Model Templating: Distinct from general data model templating: focuses on resume-specific schema inheritance and field mapping.
Explore 3 awesome GitHub repositories matching data & databases · Resume Data Models. Refine with filters or upvote what's useful.
RenderCV is a command-line utility designed to transform structured YAML data into professionally typeset documents. By separating content from presentation, it allows users to maintain version-controlled resumes that are automatically rendered into high-quality PDF, HTML, and Markdown formats. The system leverages a specialized typesetting engine to ensure precise layout control and professional-grade typography. The project distinguishes itself through a schema-driven approach that enforces strict data validation, ensuring that input files are error-free before processing. Users can customi
Defines structured data models for resume sections to enable consistent template mapping.
HackMyResume is a command-line tool that generates polished résumés and CVs in multiple formats from a single JSON or YAML data source. It validates résumé documents against the FRESH or JSON Resume schema, converts between these two formats, and produces output in HTML, Markdown, LaTeX, MS Word, PDF, plain text, JSON, XML, and YAML. The tool supports custom themes through a plugin architecture, allowing users to apply visual styling via Handlebars templates and register custom helpers for extended template logic. It can merge multiple résumé JSON files into one, overriding generic data with
Translates resume data between the FRESH and JSON Resume schema formats.
Open-resume is an ATS-friendly resume builder and browser-based document editor designed for creating professional resumes with a focus on applicant tracking system readability. It functions as a resume template engine that allows users to construct structured documents while keeping all personal data stored locally in the browser to ensure privacy and data ownership. The project features a PDF resume parser that extracts professional information from existing files to automatically populate new templates. It also includes ATS compatibility testing to verify how effectively automated tracking
Converts existing PDF resumes into structured data to populate new templates without manual typing.