mobiniqow
a464e550c9
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
37 lines
1.0 KiB
Python
37 lines
1.0 KiB
Python
"""Backend factory - resolves ``SEARCH["BACKEND"]`` to a concrete strategy."""
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from __future__ import annotations
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from functools import cache
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from django.conf import settings
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from django.core.exceptions import ImproperlyConfigured
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from apps.search.backends.base import SearchBackend
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__all__ = ["SearchBackend", "get_search_backend"]
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@cache
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def get_search_backend(name: str | None = None) -> SearchBackend:
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"""
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Return the configured backend.
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Cached because both implementations hold a connection pool that should be
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created once per process, not once per request.
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"""
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backend = (name or settings.SEARCH["BACKEND"]).lower()
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if backend == "elasticsearch":
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from apps.search.backends.elastic import ElasticsearchBackend
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return ElasticsearchBackend()
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if backend == "postgres":
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from apps.search.backends.postgres import PostgresBackend
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return PostgresBackend()
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raise ImproperlyConfigured(
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f"Unknown SEARCH['BACKEND'] {backend!r}; expected 'elasticsearch' or 'postgres'."
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)
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