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| import pandas as pd | |
| import sqlite3 | |
| import uuid | |
| from core.parsing.schema import Resume | |
| def resume_to_sqlite(resume: Resume, db_path: str = "resumes.db"): | |
| r = resume.model_dump() | |
| resume_id = str(uuid.uuid4())[:8] | |
| # 1. Prepare Data | |
| base_data = { | |
| "resume_id": resume_id, | |
| "name": r.get("full_name"), | |
| # **{f"contact_{k}": v for k, v in (r.get("contact") or {}).items()}, | |
| "summary": r.get("summary"), | |
| } | |
| # Helper to create DF with resume_id | |
| def create_df(key): | |
| data = r.get(key) or [] | |
| # Special handling for project technologies list | |
| if key == "projects": | |
| for p in data: | |
| if isinstance(p.get("technologies"), list): | |
| p["technologies"] = ", ".join(p["technologies"]) | |
| if key == "contact": | |
| df = pd.DataFrame([data]) | |
| else: | |
| df = pd.DataFrame(data) | |
| if not df.empty: | |
| df.insert(0, 'resume_id', resume_id) | |
| return df | |
| # 2. Write to SQLite | |
| with sqlite3.connect(db_path) as conn: | |
| # Save base info | |
| pd.DataFrame([base_data]).to_sql("resume_base", conn, if_exists="append", index=False) | |
| # pd.DataFrame([r.get("contact" or [])]).to_sql('contact', conn, if_exists='append', index=False) | |
| # Save nested lists | |
| tables = ["contact", "skills", "certifications", "education", "experience", "projects"] | |
| for table in tables: | |
| df = create_df(table) | |
| if not df.empty: | |
| df.to_sql(table, conn, if_exists="append", index=False) | |
| return resume_id | |