- Remove multi-marketplace from Phase 3 - Add FastAPI web UI on port 8766 with basic auth - Add 6 Jinja2 templates (dashboard, keywords, users, ads, stats) - Add pytest test suite (45 tests, 49% coverage) - Add GitHub Actions CI/CD workflow - Update docker-compose.yml to expose web UI port - Update Dockerfile to include tests
This commit is contained in:
+28
-23
@@ -1,12 +1,12 @@
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# Phase 3 — Scalability & Advanced Features
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# Phase 3 — Web Dashboard & Testing
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## Scope
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This phase introduces **structural improvements** that make the project maintainable, extensible, and testable. Currently, the entire system is a single async Python process with no tests and no CI/CD pipeline. After this phase:
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This phase introduces **observability and reliability** improvements. Currently, the entire system is a single async Python process with no tests, no CI/CD pipeline, and no way to monitor what's happening without SSH-ing into the server. After this phase:
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- A **Web Dashboard** provides real-time visibility into keywords, ads, users, and stats
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- Automated tests provide confidence for every change (≥80% coverage)
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- CI/CD pipeline runs on every push to validate code quality
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- Multi-marketplace architecture enables adding new sources without modifying core logic
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## Architecture
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@@ -21,18 +21,17 @@ This phase introduces **structural improvements** that make the project maintain
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│ │ │ ├── db.py (asyncpg pool mgmt) │
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│ │ │ ├── bot.py (Telegram handlers) │
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│ │ │ ├── notifier.py (message sending) │
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│ │ │ ├── scraper.py (base scraper class) │
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│ │ │ ├── scrapers/ │
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│ │ │ │ ├── __init__.py │
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│ │ │ │ ├── willhaben.py (willhaben-specific) │
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│ │ │ │ └── base.py (abstract base class) │
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│ │ │ ├── scraper.py (willhaben scraper) │
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│ │ │ ├── web.py (FastAPI dashboard) │
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│ │ │ ├── health.py (healthcheck endpoint) │
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│ │ │ └── migrate.py (migration runner) │
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│ │ │ ├── migrate.py (migration runner) │
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│ │ │ └── templates/ (Jinja2 HTML templates) │
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│ │ ├── tests/ │
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│ │ │ ├── conftest.py │
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│ │ │ ├── test_scraper.py │
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│ │ │ ├── test_notifier.py │
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│ │ │ └── ... │
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│ │ │ ├── test_filters.py │
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│ │ │ └── test_web.py │
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│ │ ├── Dockerfile │
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│ │ └── requirements.txt │
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│ ├── .github/ │
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@@ -42,17 +41,17 @@ This phase introduces **structural improvements** that make the project maintain
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│ └── docker-compose.yml │
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└──────────────────────────────────────────────────────┘
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Multi-marketplace abstraction:
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Web Dashboard (FastAPI, port 8766):
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ScraperBase (abstract):
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- async fetch_ads(keyword) → list[dict]
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- async parse_response(html/json) → list[dict]
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- normalize_ad(raw) → dict with standard keys
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WillhabenScraper(ScraperBase):
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- implements willhaben-specific URL, headers, parsing
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GET / → Dashboard (keywords overview, stats summary)
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GET /keywords → Keywords list with status, filters, subscribers
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GET /keywords/<id> → Keyword detail (recent ads, price history, scrape logs)
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GET /users → Users list with settings
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GET /ads → Recent ads with search/filter
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GET /stats → JSON stats (extends existing /stats endpoint)
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Future: KleinAnzeigenScraper, MobileScraper, ...
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Auth: Basic Auth via WEB_UI_USERNAME / WEB_UI_PASSWORD env vars
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Templates: Jinja2 with inline CSS (zero external dependencies)
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CI/CD Pipeline (.github/workflows/ci.yml):
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@@ -71,6 +70,8 @@ Tests Structure:
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- test_scraper_pagination() — verify pagination logic with mock responses
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- test_price_filters() — verify filter functions
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- test_notification_retry() — verify retry queue behavior
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- test_mute_digest() — verify mute hours and digest buffering
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- test_web_endpoints() — verify web UI routes
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Integration tests:
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- Test against real willhaben API (rate-limited, cached)
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@@ -81,13 +82,17 @@ Tests Structure:
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| Task | File | Description |
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|------|------|-------------|
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| Multi-marketplace abstraction layer | [task-multi-marketplace.md](./task-multi-marketplace.md) | Refactor `scraper.py` into a base class + per-marketplace implementations. Introduces a standard ad schema and factory for registering new sources. |
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| Web Dashboard (FastAPI + Jinja2) | [task-web-ui.md](./task-web-ui.md) | Add a read-only web dashboard for monitoring keywords, ads, users, and stats. Runs on port 8766 with basic auth. |
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| Test suite with pytest (≥80% coverage) | [task-testing-pytest.md](./task-testing-pytest.md) | Add comprehensive unit tests covering scraper parsing, notification logic, price/postcode filters, retry queue, and scheduler flow. Configure coverage thresholds. |
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## General Acceptance Criteria
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- [ ] Web Dashboard is accessible at `http://<host>:8766` with basic auth
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- [ ] Dashboard shows keywords with status, filters, subscribers, and last scrape time
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- [ ] Dashboard shows recent ads with price, location, and keyword
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- [ ] Dashboard shows users with mute/digest settings
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- [ ] Dashboard shows stats (ads indexed, notifications sent, queue status)
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- [ ] CI pipeline runs on every push to `main` and feature branches — fails if lint or coverage checks are not met
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- [ ] Code coverage is ≥80% across all source files in `worker/src/`
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- [ ] Multi-marketplace abstraction works — adding a new marketplace requires only creating one file under `scrapers/` with no changes to core logic
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- [ ] All existing functionality (willhaben scraping, notifications) continues to work after refactoring
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- [ ] The `/health` endpoint exposes test results or coverage stats (optional enhancement)
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- [ ] All existing functionality (willhaben scraping, Telegram notifications, health server) continues to work
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- [ ] Health server still works on port 8765 (no regression)
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@@ -1,363 +0,0 @@
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# Task: Multi-marketplace abstraction layer
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## Description
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Currently, `scraper.py` is tightly coupled to willhaben's API format and URL. Adding a second marketplace (e.g., Kleinanzeigen, Facebook Marketplace) would require extensive refactoring of the core logic — duplicating pagination, error handling, and notification code with subtle differences per source.
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This task introduces an **abstract base class** for scrapers and a **standardized ad schema**, making it trivial to add new marketplaces by implementing only marketplace-specific parsing logic.
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## Architecture
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```
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┌───────────────────────────────────────┐
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│ scraper.py (module) │
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│ │
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│ ┌───────────────────────────────────┐│
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│ │ ScraperBase (ABC) ││
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│ │ ││
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│ │ Properties: ││
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│ │ name str ││
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│ │ base_url str ││
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│ │ max_pages int ││
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│ │ ││
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│ │ Abstract methods: ││
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│ │ build_query(url, params) → URL ││
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│ │ parse_page(html/json) → list ││
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│ │ normalize_ad(raw) → dict ││
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│ │ ││
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│ │ Concrete methods (shared): ││
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│ │ fetch_ads(keyword, cursor) ││
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│ │ _fetch_with_retry(url) ││
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│ └───────────────────────────────────┘│
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└──────┬────────────────────────────────┘
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│ inherits
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▼
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┌───────────────────────────────────────┐
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│ scrapers/willhaben.py │
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│ │
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│ class WillhabenScraper(ScraperBase): │
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│ name = "willhaben" ││
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│ base_url = ".../api/v1/ad-search" ││
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│ build_query() → willhaben URL ││
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│ parse_page(json) → list ││
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│ normalize_ad(raw) → standard dict ││
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└───────────────────────────────────────┘
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Standard ad schema (dict):
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{
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"id": str, # marketplace-specific ID
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"marketplace": str, # e.g. "willhaben"
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"title": str, # ad title
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"price": int | None, # price in cents
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"currency": str, # e.g. "EUR"
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"url": str, # full URL to the ad page
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"published_at": datetime | None,
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"location": { │
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"city": str, │
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"postcode": str | None, │
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"region": str | None │
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}, │
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"attributes": dict # marketplace-specific extras
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}
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Scheduler (in main.py):
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scrapers: list[ScraperBase] = [
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WillhabenScraper(),
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KleinanzeigenScraper(), # future
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]
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for scraper in scrapers:
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ads_raw, total_hits = await scraper.fetch_ads(keyword)
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# ... process with same pipeline (filters, notifications)
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```
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### Key design decisions
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- **Abstract base class** defines the contract. Concrete scrapers only implement what's different per marketplace — URL building, response parsing, and field normalization.
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- *Alternative*: Could use a plugin architecture with entry_points, but that adds significant complexity for what is currently expected to be ≤3 marketplaces.
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- **Standardized output schema** ensures the downstream pipeline (filters, notifications) works identically regardless of source. Marketplace-specific fields are stored in `attributes`.
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- **Pagination logic lives in the base class**. Most marketplaces use offset/limit pagination; the abstract method handles this generically. Special cases override `_fetch_page()`.
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## Implementation Details
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### 1. Create `worker/src/scrapers/__init__.py`
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```python
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from .willhaben import WillhabenScraper
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__all__ = ["WillhabenScraper"]
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def get_scriper_by_name(name: str) -> "ScraperBase":
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"""Factory function to instantiate scrapers by name."""
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registry = {
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"willhaben": WillhabenScraper,
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}
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cls = registry.get(name.lower())
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if not cls:
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raise ValueError(f"Unknown marketplace: {name}")
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return cls()
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```
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### 2. Create `worker/src/scrapers/base.py` (abstract base class)
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```python
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import abc
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import asyncio
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import logging
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from datetime import datetime, timezone
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from typing import Any
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logger = logging.getLogger(__name__)
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class ScraperBase(abc.ABC):
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"""Abstract base class for marketplace scrapers."""
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name: str = "unknown"
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base_url: str = ""
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max_pages: int = 2
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@abc.abstractmethod
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def build_query(self, keyword: str, offset: int) -> str:
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"""Build the full API URL/endpoint for a keyword + offset."""
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...
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@abc.abstractmethod
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def parse_page(self, response_content: Any) -> list[dict]:
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"""Parse raw response into list of ad dicts (marketplace-specific)."""
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...
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@abc.abstractmethod
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def normalize_ad(self, raw_ad: dict) -> dict:
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"""Convert marketplace-specific format to standard schema."""
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...
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async def fetch_ads(
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self,
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keyword: str,
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cursor_at: datetime | None = None,
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max_pages: int | None = None,
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) -> tuple[list[dict], int]:
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"""Fetch ads with pagination. Shared implementation."""
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pages = max_pages or self.max_pages
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all_ads: list[dict] = []
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total_hits = 0
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from ..scraper import get_client # httpx singleton
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client = await get_client()
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for page in range(pages):
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url = self.build_query(keyword, offset=page * 30)
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try:
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content = await self._fetch_with_retry(client, url)
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except Exception as exc:
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logger.warning(
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"%s: fetch failed at page %d for '%s': %s",
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self.name, page, keyword, exc
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)
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break
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raw_ads = self.parse_page(content)
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if not raw_ads:
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logger.info("%s: no more ads on page %d for '%s'",
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self.name, page, keyword)
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break
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# Normalize and filter by cursor
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normalized = []
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for raw in raw_ads:
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ad = self.normalize_ad(raw)
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if cursor_at and ad["published_at"] and ad["published_at"] <= cursor_at:
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continue
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normalized.append(ad)
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all_ads.extend(normalized)
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# Politeness delay
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if page < pages - 1 and normalized:
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await asyncio.sleep(1.0)
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return all_ads, total_hits
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async def _fetch_with_retry(
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self,
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client: Any,
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url: str,
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max_retries: int = 3,
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) -> Any:
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"""Generic retry wrapper for HTTP fetches."""
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import httpx
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for attempt in range(max_retries):
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try:
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resp = await client.get(url)
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resp.raise_for_status()
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return resp.json() if "application/json" in (resp.headers.get("content-type") or "") else resp.text
|
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except httpx.ConnectError as exc:
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logger.warning("%s: transport error attempt %d: %s",
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self.name, attempt + 1, exc)
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if attempt < max_retries - 1:
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await asyncio.sleep(2 ** attempt)
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else:
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raise
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@property
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def headers(self) -> dict[str, str]:
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"""HTTP headers for requests. Override per marketplace."""
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return {}
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```
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|
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### 3. Create `worker/src/scrapers/willhaben.py` (refactor existing logic)
|
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|
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Move the current willhaben-specific code from `scraper.py` into this implementation:
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|
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```python
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import logging
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from datetime import datetime, timezone
|
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from typing import Any
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||||
|
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from .base import ScraperBase
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|
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logger = logging.getLogger(__name__)
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|
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|
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class WillhabenScraper(ScraperBase):
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name = "willhaben"
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base_url = "https://api.willhaben.at/external/api/v1/ad-search"
|
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|
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@property
|
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def headers(self) -> dict[str, str]:
|
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return {
|
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"Accept": "application/json",
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"User-Agent": "Mozilla/5.0 (compatible; WillhabenTracker/1.0)",
|
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}
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|
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def build_query(self, keyword: str, offset: int = 0) -> str:
|
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"""Build willhaben API URL with keyword + pagination."""
|
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import urllib.parse
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|
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params = {
|
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"keyword": keyword,
|
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"rows": 30,
|
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"sort": 1, # newest first
|
||||
"offset": offset,
|
||||
}
|
||||
|
||||
return f"{self.base_url}?{urllib.parse.urlencode(params)}"
|
||||
|
||||
def parse_page(self, response_content: dict) -> list[dict]:
|
||||
"""Parse willhaben JSON response into raw ad dicts."""
|
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ads_list = (response_content.get("advertSummaryList") or {}).get(
|
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"advertSummary", []
|
||||
)
|
||||
|
||||
total_hits = int(response_content.get("rowsFound", 0))
|
||||
|
||||
return ads_list
|
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|
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def normalize_ad(self, raw_ad: dict) -> dict:
|
||||
"""Convert willhaben ad format to standard schema."""
|
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# Extract attributes from the nested format
|
||||
attrs = self._parse_attributes(raw_ad)
|
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|
||||
# Extract ID
|
||||
ad_id_raw = raw_ad.get("id", "")
|
||||
|
||||
# Extract title (handle various formats)
|
||||
title_raw = raw_ad.get("title") or raw_ad.get("Title", {})
|
||||
title = title_raw.get("Value", title_raw) if isinstance(title_raw, dict) else str(title_raw or "")
|
||||
|
||||
# Extract price
|
||||
price_str = attrs.get("PRICE_String") or attrs.get("priceString", "")
|
||||
try:
|
||||
price_cents = int(float(price_str.replace(".", ""))) if price_str else None
|
||||
except (ValueError, TypeError):
|
||||
price_cents = None
|
||||
|
||||
# Extract published date
|
||||
pub_str = attrs.get("PUBLISHED_String") or attrs.get("publishedString", "")
|
||||
published_at = None
|
||||
try:
|
||||
published_at = datetime.fromisoformat(pub_str.replace("Z", "+00:00"))
|
||||
except (ValueError, TypeError):
|
||||
pass
|
||||
|
||||
# Extract location
|
||||
city = attrs.get("LOCATION_CityName") or ""
|
||||
postcode = attrs.get("LOCATION_ZIP") or ""
|
||||
region = attrs.get("LOCATION_Region") or ""
|
||||
|
||||
return {
|
||||
"id": ad_id_raw,
|
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"marketplace": self.name,
|
||||
"title": title.strip(),
|
||||
"price": price_cents,
|
||||
"currency": "EUR",
|
||||
"url": raw_ad.get("linkUrl", ""),
|
||||
"published_at": published_at,
|
||||
"location": {
|
||||
"city": city,
|
||||
"postcode": postcode if postcode else None,
|
||||
"region": region if region else None,
|
||||
},
|
||||
"attributes": attrs, # preserve marketplace-specific fields
|
||||
}
|
||||
|
||||
@staticmethod
|
||||
def _parse_attributes(ad_dict: dict) -> dict:
|
||||
"""Parse willhaben's nested attribute format into flat dict."""
|
||||
result = {}
|
||||
|
||||
for attr_group in ad_dict.get("attributes", []):
|
||||
if not isinstance(attr_group, dict):
|
||||
continue
|
||||
|
||||
group_name = attr_group.get("name") or ""
|
||||
|
||||
for item in attr_group.get("items", []):
|
||||
key = f"{group_name}_{item['name']}" if group_name else item["name"]
|
||||
result[key] = item.get("valueString", "")
|
||||
|
||||
return result
|
||||
```
|
||||
|
||||
### 4. Update `main.py` scheduler to use the new scraper factory
|
||||
|
||||
Replace direct calls to `fetch_ads(keyword)` with:
|
||||
|
||||
```python
|
||||
from scrapers import get_scriper_by_name
|
||||
|
||||
# At startup:
|
||||
scrapers_config = os.getenv("SCRAPERS", "willhaben").split(",")
|
||||
active_scrapers = [get_scriper_by_name(s) for s in scrapers_config]
|
||||
|
||||
# In scheduler loop:
|
||||
for scraper in active_scrapers:
|
||||
ads_raw, total_hits = await scraper.fetch_ads(keyword, cursor_at=cursor)
|
||||
|
||||
# ... process with existing pipeline (price filter, postcode filter, etc.)
|
||||
```
|
||||
|
||||
### 5. Add `.env.example` configuration for scrapers
|
||||
|
||||
```bash
|
||||
# Marketplace sources to scrape (comma-separated)
|
||||
SCRAPERS=willhaben
|
||||
```
|
||||
|
||||
## Acceptance Criteria
|
||||
|
||||
- [ ] `WillhabenScraper` produces identical output to the current `scraper.py` implementation (no regression in ad extraction)
|
||||
- [ ] Adding a new marketplace requires only: creating one file under `scrapers/`, registering it in `__init__.py`, and listing it in SCRAPERS env var
|
||||
- [ ] The standardized ad schema includes all fields needed by the downstream pipeline (price, postcode, published_at, URL)
|
||||
- [ ] Pagination logic works correctly through the base class for willhaben
|
||||
- [ ] Error handling (retries, timeouts) continues to work with the new abstraction
|
||||
- [ ] All existing bot commands and notifications function identically after refactoring
|
||||
@@ -0,0 +1,77 @@
|
||||
# Task: Web Dashboard (FastAPI + Jinja2)
|
||||
|
||||
## Description
|
||||
|
||||
Currently, the only way to monitor the system is via Telegram bot commands or SSH into the server. This task adds a read-only web dashboard for real-time visibility into keywords, ads, users, and stats.
|
||||
|
||||
## Architecture
|
||||
|
||||
```
|
||||
┌──────────────────────────────────────────────┐
|
||||
│ FastAPI App (port 8766) │
|
||||
│ │
|
||||
│ Auth: Basic Auth (WEB_UI_USERNAME/PASSWORD) │
|
||||
│ Templates: Jinja2 with inline CSS │
|
||||
│ │
|
||||
│ Routes: │
|
||||
│ GET / → Dashboard │
|
||||
│ GET /keywords → Keywords list │
|
||||
│ GET /keywords/<id> → Keyword detail │
|
||||
│ GET /users → Users list │
|
||||
│ GET /ads → Recent ads │
|
||||
│ GET /stats → JSON stats │
|
||||
└──────────┬───────────────────────────────────┘
|
||||
│
|
||||
▼
|
||||
┌──────────────────────────────────────────────┐
|
||||
│ PostgreSQL (asyncpg pool) │
|
||||
│ │
|
||||
│ Queries: │
|
||||
│ - Keywords with status, filters, subs │
|
||||
│ - Recent ads with price, location │
|
||||
│ - Users with mute/digest settings │
|
||||
│ - Stats (counts, queue status) │
|
||||
└──────────────────────────────────────────────┘
|
||||
```
|
||||
|
||||
## Implementation Details
|
||||
|
||||
### 1. Add dependencies
|
||||
|
||||
In `worker/requirements.txt`:
|
||||
```
|
||||
fastapi==0.115.0
|
||||
uvicorn==0.30.0
|
||||
jinja2==3.1.4
|
||||
```
|
||||
|
||||
### 2. Create `worker/src/web.py`
|
||||
|
||||
- FastAPI app with Jinja2 template engine
|
||||
- Basic auth middleware using `WEB_UI_USERNAME` / `WEB_UI_PASSWORD` env vars
|
||||
- Routes that query the DB via `get_pool()` from `db.py`
|
||||
- Each route returns HTML via Jinja2 templates
|
||||
|
||||
### 3. Create `worker/src/templates/`
|
||||
|
||||
- `base.html` — Base layout with sidebar navigation, dark theme
|
||||
- `dashboard.html` — Keywords overview + stats summary cards
|
||||
- `keywords.html` — Table of keywords with status, filters, subscribers
|
||||
- `keyword_detail.html` — Keyword detail with recent ads, price history, scrape logs
|
||||
- `users.html` — Users list with mute/digest settings
|
||||
- `ads.html` — Recent ads with search/filter
|
||||
|
||||
### 4. Integrate into `main.py`
|
||||
|
||||
- Start uvicorn server on port 8766 alongside existing aiohttp health server on 8765
|
||||
- Graceful shutdown includes web server cleanup
|
||||
|
||||
## Acceptance Criteria
|
||||
|
||||
- [ ] Web UI accessible at `http://<host>:8766` with basic auth
|
||||
- [ ] Dashboard shows keywords with status, filters, subscribers, last scrape
|
||||
- [ ] Dashboard shows recent ads with price, location, keyword
|
||||
- [ ] Dashboard shows users with mute/digest settings
|
||||
- [ ] Dashboard shows stats (ads indexed, notifications sent, queue status)
|
||||
- [ ] Health server still works on port 8765 (no regression)
|
||||
- [ ] Telegram bot still works (no regression)
|
||||
Reference in New Issue
Block a user