Resume to JSON — Explore a Real Parsed Output (50+ Fields) [ResumeParser.pro](https://resumeparser.pro) - [Parsing API](https://resumeparser.pro/resume-parsing-api) - [Match Score API](https://resumeparser.pro/resume-job-match-score-api) - [Sample JSON](https://resumeparser.pro/resume-to-json) - [Guides](https://resumeparser.pro/guides) - [Glossary](https://resumeparser.pro/glossary) - [Get API key](https://sharpapi.com/en/resume-parsing-api?utm_source=resumeparser.pro&utm_medium=referral&utm_campaign=resume-to-json&utm_content=nav) 1. [Home](https://resumeparser.pro) 2. What a Resume Looks Like as JSON What a Resume Looks Like as JSON ================================ Below is a genuine parsing output and a genuine match-score payload — click through the trees. This is the contract your code would integrate against, shown in full, before you sign up for anything. Converting a resume to JSON means extracting its content into named, typed fields a program can query: candidate\_name, positions\[\].skills, education\_qualifications\[\].degree\_type. The two payloads below come from the SharpAPI parsing and match-score endpoints, unedited in structure. parse\_resume → result resume\_job\_match\_score → result POST → 202 Accepted ``` { "data": { "type": "api_job_result", "id": "87eda824-6b9e-4557-b5e0-fa23b2207d58", "attributes": { "status": "success", "type": "hr_parse_resume", "result": { "candidate_name": "Linda Harris", "candidate_email": "linda.h@dayjob.co.uk", "candidate_phone": "02476 000 0000, 0887 222 9999", "candidate_address": "34 Made Up Road, Coventry, CV66 7RF", "candidate_language": "English", "candidate_spoken_languages": [ "German" ], "candidate_honors_and_awards": [], "candidate_courses_and_certifications": [ "ISEB certification" ], "positions": [ { "position_name": "Test Engineer", "company_name": "IT & Telecoms Company", "country": "United Kingdom", "start_date": "2008-06-01", "end_date": null, "skills": [ "Acceptance testing", "Technical investigation", "Exploratory testing", "Agile", "Test environments", "Test management tools", "UAT knowledge", "Writing test reports", "Performance testing", "Integration testing", "Manual testing methods" ], "job_details": "Responsible for the whole test process from planning, through test plan development, execution & result reporting. Duties included organising, conducting and supporting test activities, performance testing, integration testing, responding to equipment failures, participating in audits and reviews, executing test cases, and reporting issues to the Test Manager." } ], "education_qualifications": [ { "school_name": "Nuneaton University", "school_type": "University or equivalent", "degree_type": "Bachelor’s Degree or equivalent", "faculty_department": "", "specialization_subjects": "Information Technology (Software Engineering)", "country": "United Kingdom", "start_date": "2005-01-01", "end_date": "2008-01-01", "learning_mode": "In-person learning", "education_details": "" }, { "school_name": "Coventry North School", "school_type": "High School/Secondary School or equivalent", "degree_type": "High School/Secondary School Diploma or equivalent", "faculty_department": "", "specialization_subjects": "", "country": "United Kingdom", "start_date": "2000-01-01", "end_date": "2005-01-01", "learning_mode": "In-person learning", "education_details": "A levels: Maths (A), English (B), Technology (B), Science (C)" } ] } } } } ``` ``` { "data": { "type": "api_job_result", "id": "8a432abd-73a4-4c9d-8dbf-1730ed8bfa90", "attributes": { "status": "success", "type": "hr_resume_job_match_score", "result": { "match_scores": { "overall_match": 72, "skills_match": 80, "experience_match": 90, "education_match": 0, "certifications_match": 0, "job_title_relevance": 70, "industry_experience_match": 85, "project_experience_match": 75, "technical_stack_match": 80, "methodologies_match": 60, "soft_skills_match": 80, "language_proficiency_match": 100, "location_preference_match": 20, "remote_work_flexibility": 90, "certifications_training_relevance": 0, "years_experience_weighting": 95, "recent_role_relevance": 60, "management_experience_match": 100, "cultural_fit_potential": 70, "stability_score": 85 }, "explanations": { "skills_match": "Strong PHP and MySQL coverage; Laravel is not mentioned explicitly in the resume.", "experience_match": "Over 22 years of programming experience — well beyond the seniority the role requires.", "education_match": "No education section found in the resume, so this dimension could not be assessed.", "certifications_match": "No PHP- or MySQL-related certifications listed.", "language_proficiency_match": "Fluent English, which the job posting requires." } } } } } ``` ``` { "status_url": "https://sharpapi.com/api/v1/hr/parse_resume/job/status/09cf83f8-3e3e-4948-add9-63cdecc1f9fe", "job_id": "09cf83f8-3e3e-4948-add9-63cdecc1f9fe" } ``` How to read the parse payload ----------------------------- Everything lives under data.attributes.result. Scalars first — name, email, phone, address, languages — then the two arrays that carry most of the value: positions (one entry per role, each with its own dated skill list) and education\_qualifications (with normalized degree\_type vocabularies, so a UK bachelor's and its EU equivalent compare cleanly). The schema is deterministic: parse a thousand resumes and every one returns these fields. Empty rather than missing, string dates in YYYY-MM-DD, arrays always arrays. The complete field inventory is in [what fields does a resume parser extract](https://resumeparser.pro/what-fields-does-a-resume-parser-extract). How to read the match payload ----------------------------- match\_scores holds all 20 dimensions as integers 0–100; explanations holds written reasons for the headline dimensions. Zeros are honest: this candidate's resume has no education section, so education\_match is 0 with an explanation saying exactly that — not a hallucinated average. Details on the weighting live on the [Match Score API page](https://resumeparser.pro/resume-job-match-score-api). Get this JSON for your own files -------------------------------- One POST with your file, one poll of the status URL. Tutorials with working code: [Python](https://resumeparser.pro/guides/parse-resume-python), [PHP & Laravel](https://resumeparser.pro/guides/parse-resume-php-laravel), [Node.js](https://resumeparser.pro/guides/parse-resume-nodejs). Run it on a real resume ----------------------- The trial's 100,000 words parse a full test batch of your own documents — same schema you just explored, no credit card. [Start parsing free](https://sharpapi.com/en/resume-parsing-api?utm_source=resumeparser.pro&utm_medium=referral&utm_campaign=resume-to-json&utm_content=footer-cta) [Endpoint docs](https://sharpapi.com/documentation?utm_source=resumeparser.pro&utm_medium=referral&utm_campaign=resume-to-json&utm_content=footer-cta-docs) 14-day trial · 100,000 words included · No credit card · 30-day money-back guarantee Questions, answered ------------------- What does a resume look like as JSON?A single object with the candidate profile at the top level and arrays for positions, education, skills, certifications and languages. Explore the full example on this page — it is a real parsing output, not a mock-up. Is the JSON schema the same for every resume?Yes — deterministic by design. A two-column designer CV and a plain-text developer resume both return the same field structure; fields the document lacks come back empty rather than missing, so your code never branches on layout. How do I convert my own resumes to JSON?One multipart POST to the SharpAPI parse\_resume endpoint with your file and API key. The response gives you a status URL; poll it or take a webhook and read the parsed JSON. Working code for Python, PHP and Node.js is in the guides section. Can I get a match score as JSON too?Yes — the second tab of the explorer on this page shows the exact payload: 20 scored dimensions plus written explanations, from the resume\_job\_match\_score endpoint. Further reading --------------- - [What Fields Does a Resume Parser Extract? All 50+ Listed](https://resumeparser.pro/what-fields-does-a-resume-parser-extract) The complete field list a production resume parser returns: contact data, work history, education, skills, certifications, licenses and 40+ more — with types. - [Resume Parsing API — PDF, DOCX & Photo CVs to JSON (80+ Langs)](https://resumeparser.pro/resume-parsing-api) AI resume parsing API: send a PDF, DOCX, RTF, TXT or photo CV, get back 50+ structured JSON fields. 80+ languages, OCR included, async REST, from $50/mo. - [Parse a Resume in Python: PDF to JSON in Under 30 Lines](https://resumeparser.pro/guides/parse-resume-python) A working Python tutorial: send a PDF resume to a parsing API, poll the async job and read 50+ structured fields — requests-only, no ML setup. ResumeParser.pro — a free resource on resume parsing and candidate matching, written and maintained by the team behind [SharpAPI](https://sharpapi.com/?utm_source=resumeparser.pro&utm_medium=referral&utm_campaign=resume-to-json&utm_content=footer). The APIs documented here: [Resume Parsing API](https://sharpapi.com/en/resume-parsing-api?utm_source=resumeparser.pro&utm_medium=referral&utm_campaign=resume-to-json&utm_content=footer) and [Resume Job Match Score API](https://sharpapi.com/en/resume-job-match-score-api?utm_source=resumeparser.pro&utm_medium=referral&utm_campaign=resume-to-json&utm_content=footer). SDKs on [GitHub](https://github.com/sharpapi). On this site: [What is resume parsing](https://resumeparser.pro/what-is-resume-parsing)·[How parsing works](https://resumeparser.pro/how-does-resume-parsing-work)·[Extracted fields](https://resumeparser.pro/what-fields-does-a-resume-parser-extract)·[Resume to JSON](https://resumeparser.pro/resume-to-json)·[Best parser APIs](https://resumeparser.pro/guides/best-resume-parser-apis)·[All guides](https://resumeparser.pro/guides)·[Glossary](https://resumeparser.pro/glossary)·[About](https://resumeparser.pro/about) No cookies, no tracking pixels, no popups. © 2026 [A2Z Web](https://a2zweb.co). A Markdown version of this page is available at https://resumeparser.pro/resume-to-json.md, optimized for AI and LLM tools.