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626428e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 | 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
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