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

backend/apps/profiles/views.py

@@ -0,0 +1,72 @@
+"""Profile read endpoints (the search endpoints live in ``apps.search``)."""
+
+from __future__ import annotations
+
+from django.db.models import QuerySet
+from drf_spectacular.utils import extend_schema
+from rest_framework import generics
+from rest_framework.permissions import IsAuthenticated
+
+from apps.profiles.models import Profile, Skill
+from apps.profiles.serializers import (
+    ProfileDetailSerializer,
+    ProfileListSerializer,
+    SkillSerializer,
+)
+
+
+@extend_schema(tags=["profiles"])
+class ProfileListView(generics.ListAPIView):
+    """
+    Plain, unranked listing.
+
+    Useful for browsing and for verifying the dataset; ranked keyword search is
+    served by ``/api/v1/search/``.
+    """
+
+    serializer_class = ProfileListSerializer
+    permission_classes = [IsAuthenticated]
+
+    def get_queryset(self) -> QuerySet[Profile]:
+        return (
+            Profile.objects.select_related("current_company")
+            .prefetch_related("profile_skills__skill")
+            .order_by("full_name", "id")
+        )
+
+
+@extend_schema(tags=["profiles"])
+class ProfileDetailView(generics.RetrieveAPIView):
+    """Full profile including work history, education and (masked) contacts."""
+
+    serializer_class = ProfileDetailSerializer
+    permission_classes = [IsAuthenticated]
+
+    def get_queryset(self) -> QuerySet[Profile]:
+        return Profile.objects.select_related("current_company").prefetch_related(
+            "profile_skills__skill",
+            "experiences__company",
+            "educations__school",
+        )
+
+
+@extend_schema(tags=["profiles"])
+class SkillListView(generics.ListAPIView):
+    """
+    Skill dictionary ordered by popularity.
+
+    The frontend uses it to power the skill filter's type-ahead without hitting
+    Elasticsearch for every keystroke.
+    """
+
+    serializer_class = SkillSerializer
+    permission_classes = [IsAuthenticated]
+    pagination_class = None
+
+    def get_queryset(self) -> QuerySet[Skill]:
+        queryset = Skill.objects.filter(profile_count__gt=0)
+        term = self.request.query_params.get("q", "").strip().lower()
+        if term:
+            queryset = queryset.filter(name__icontains=term[:64])
+        limit = min(int(self.request.query_params.get("limit", 50) or 50), 200)
+        return queryset.order_by("-profile_count", "name")[:limit]