Build a Resume Parser & Job Matcher API with FastAPI and NLP

In today’s competitive talent market, recruiters often sift through hundreds of resumes for a single role. Manually comparing each resume against a job description is tedious and inconsistent. In this article, we’ll build a Resume Parser & Job Matcher a REST API that: Extracts text from PDF, DOCX, or TXT resumes. Compares the resume against one or more job descriptions. Returns a match score (0–100) based on cosine similarity and skill overlap. We’ll use FastAPI for the web framework, spaCy for text preprocessing, scikit‑learn for TF‑IDF vectorisation, and pdfplumber / python-docx for file parsing. ** What You’ll Learn** How to parse text from different resume formats. How to clean and tokenise text using spaCy. How to compute similarity between documents with TF‑IDF. How to combine multiple heuristics (keyword overlap) into a final score. How to expose everything as a modern, self‑documenting API. Prerequisites Python 3.9+ installed Basic familiarity with Python and virtual enviro