Files
mobiniqow a464e550c9 feat: LinkedIn profile search engine (Django + React + Elasticsearch + ELK)
Full-stack implementation of the Cyberyan full-stack trial task.

Backend (Django 5 / DRF)
- Normalised PostgreSQL model (Profile, Company, School, Skill, Experience,
  Education) as the source of truth, with GIN + trigram indexes.
- Self-healing CSV reader: the supplied export carries an injected watermark
  column, missing columns, rows split by broken quoting and a duplicated
  header. A signature-scored Needleman-Wunsch alignment reconstructs 284 clean
  records out of 336 physical rows; only 10 rows parse correctly without it.
- Pluggable search layer (Strategy): Elasticsearch by default, PostgreSQL
  full-text search as a fallback selected by a single environment variable.
- Keyword search with per-field boosts, fuzziness and phrase boosting, six
  faceted filters (OR within a filter, AND across filters), an experience
  range, four sort orders, highlighting and facet aggregations.
- JWT auth with rotation + blacklist, three roles, PII masking, scoped rate
  limits, a single error envelope, OpenAPI schema and health probes.

Frontend (React 18 / TypeScript / Vite)
- Debounced search with type-ahead, faceted filter panel, result cards,
  profile drawer, URL-synced search state, automatic token refresh.
- Highlight snippets rendered without dangerouslySetInnerHTML.

Infrastructure
- Hardened multi-stage images (non-root, read-only rootfs, healthchecks).
- docker-compose for the full stack plus dev and production overlays.
- ELK: structured JSON logs shipped asynchronously to Logstash, routed per
  event type, with a composable index template and a Kibana setup script.

Quality
- 61 backend tests (85% coverage), ruff/black/bandit/mypy, ESLint + tsc,
  GitHub Actions running lint, tests and both image builds.
- Persian documentation: README plus architecture, search, API, data,
  security and operations guides.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01GnFo6fNaHCTAkJbfcdkqtG
2026-09-03 08:13:50 +00:00

53 lines
2.2 KiB
Python

"""``python manage.py search_index`` - manage the Elasticsearch index."""
from __future__ import annotations
import json
import time
from typing import Any
from django.core.management.base import BaseCommand, CommandError
from apps.search.indexing import alias_name, get_client, rebuild_index
class Command(BaseCommand):
help = "Create, rebuild, inspect or drop the Elasticsearch profile index."
def add_arguments(self, parser) -> None: # noqa: ANN001
group = parser.add_mutually_exclusive_group(required=True)
group.add_argument("--rebuild", action="store_true", help="Rebuild and swap the alias.")
group.add_argument("--status", action="store_true", help="Show index/alias status.")
group.add_argument("--drop", action="store_true", help="Delete the index and its alias.")
def handle(self, *args: Any, **options: Any) -> None:
client = get_client()
if not client.ping():
raise CommandError("Elasticsearch is not reachable. Check ELASTICSEARCH_HOSTS.")
if options["rebuild"]:
started = time.perf_counter()
result = rebuild_index(client)
result["elapsed_seconds"] = round(time.perf_counter() - started, 2)
self.stdout.write(json.dumps(result, indent=2))
self.stdout.write(self.style.SUCCESS("Index rebuilt."))
return
alias = alias_name()
if options["status"]:
exists = client.indices.exists_alias(name=alias)
payload: dict[str, Any] = {"alias": alias, "exists": bool(exists)}
if exists:
indices = list(client.indices.get_alias(name=alias).keys())
payload["indices"] = indices
payload["documents"] = client.count(index=alias)["count"]
self.stdout.write(json.dumps(payload, indent=2))
return
if options["drop"]:
if client.indices.exists_alias(name=alias):
for name in client.indices.get_alias(name=alias):
client.indices.delete(index=name, ignore_unavailable=True)
client.indices.delete(index=alias, ignore_unavailable=True)
self.stdout.write(self.style.WARNING(f"Dropped index/alias {alias}."))