| import psycopg2 |
| import psycopg2.extras |
| import json |
| import os |
| from dotenv import load_dotenv |
| from huggingface_hub import hf_hub_download |
| from pathlib import Path |
| from huggingface_hub import snapshot_download |
| from zoneinfo import ZoneInfo |
|
|
| load_dotenv() |
| POSTGRES_USER = os.environ.get("POSTGRES_USER") |
| POSTGRES_PASS = os.environ.get("POSTGRES_PASS") |
| HF_TOKEN = os.environ.get("HF_TOKEN") |
|
|
| def insert_data(website): |
|
|
| files_succeeded = 0 |
| files_failed = 0 |
| total_inserted = 0 |
| total_duplicates = 0 |
|
|
| repo_dir = snapshot_download( |
| repo_id="Amin1600/Web_Scraper_Data", |
| repo_type="dataset", |
| allow_patterns=f"job_data/raw/{website}/*", |
| token=HF_TOKEN, |
| tqdm_class=None |
| ) |
|
|
| target_folder = Path(repo_dir) / "job_data" / "raw" / website |
|
|
| conn = psycopg2.connect( |
| host="localhost", |
| port="5433", |
| database="jobs", |
| user=POSTGRES_USER, |
| password=POSTGRES_PASS |
| ) |
| cur = conn.cursor() |
|
|
| for job_file in target_folder.rglob('*.jsonl'): |
|
|
| cur.execute( |
| "SELECT 1 FROM file_metadata WHERE file_name = %s", |
| (job_file.name,) |
| ) |
| if cur.fetchone(): |
| print(f"Skipping {job_file.name} (already loaded)") |
| continue |
|
|
| |
| rows = [] |
| with open(job_file, "r", encoding="utf-8") as f: |
| for line_num, line in enumerate(f, start=1): |
| try: |
| job = json.loads(line) |
| except json.JSONDecodeError as e: |
| print(f"⚠️ Skipping malformed line {line_num} in {job_file.name}: {e}") |
| continue |
|
|
| rows.append(( |
| job.get("source"), |
| job.get("search_term"), |
| job.get("job_id"), |
| job.get("url"), |
| job.get("collection_timestamp"), |
| job.get("job_title"), |
| job.get("company"), |
| job.get("location"), |
| job.get("employment_type"), |
| job.get("salary_min"), |
| job.get("salary_max"), |
| job.get("department"), |
| job.get("posting_date"), |
| job.get("job_description"), |
| job.get("requirements"), |
| json.dumps(job.get("skills", [])), |
| job.get("raw_html") |
| )) |
|
|
| if not rows: |
| print(f"No valid rows in {job_file.name}, skipping.") |
| continue |
|
|
| try: |
| inserted = psycopg2.extras.execute_values( |
| cur, |
| """ |
| INSERT INTO stg_jobs ( |
| source, search_term, job_id, url, collection_timestamp, |
| job_title, company, location, employment_type, salary_min, |
| salary_max, department, posting_date, job_description, |
| requirements, skills, raw_html |
| ) |
| VALUES %s |
| ON CONFLICT (source, job_id) |
| DO NOTHING |
| RETURNING job_id; |
| """, |
| rows, |
| template="(%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s::jsonb,%s)", |
| page_size=100, |
| fetch=True |
| ) |
|
|
| num_inserted = len(inserted) |
| num_duplicates = len(rows) - num_inserted |
|
|
| cur.execute( |
| "INSERT INTO file_metadata (file_name) VALUES (%s)", |
| (job_file.name,) |
| ) |
| conn.commit() |
|
|
| total_inserted += num_inserted |
| total_duplicates += num_duplicates |
| files_succeeded += 1 |
|
|
| print(f"✅ {job_file.name}: {num_inserted} inserted, {num_duplicates} duplicates skipped") |
|
|
| except Exception as e: |
| conn.rollback() |
| files_failed += 1 |
| print(f"❌ {job_file.name} failed, transaction rolled back: {e}") |
| continue |
|
|
| print("\n--- INSERTION REPORT ---") |
| print(f"Files loaded: {files_succeeded}") |
| print(f"Files failed: {files_failed}") |
| print(f"Total rows inserted: {total_inserted}") |
| print(f"Total duplicates skipped: {total_duplicates}") |
|
|
| cur.close() |
| conn.close() |
|
|
|
|
| if __name__ == "__main__": |
|
|
| scraped_websites = ["linkedin", "jobstreet"] |
| for website in scraped_websites: |
| insert_data(website) |
