KiraTV---Aplicacion-para-Windows/docs/architecture/stalker-mock-server.md

Stalker Mock Server Architecture

This document describes the design decisions, data flow, and extension points of the stalker-mock-server development tool.

Related Docs

• Stalker Portal Architecture
• Stalker EPG Architecture

Purpose

The mock server enables:

1. Local development without access to a real Stalker portal
2. Playwright E2E testing with predictable, deterministic data
3. Scenario-based testing via predefined MAC addresses that map to specific data shapes

Key Design Decisions

Seeded Determinism (Not Per-Request Random)

Per-request random data would break navigation: if category IDs change between calls, content fetched under a category ID won't match the category list. Instead:

• Data is generated once per MAC address on first request, then cached in memory.
• @faker-js/faker is seeded with a numeric value derived from the MAC address before generation.
• Same MAC → identical data on every server restart.
• Restart the server to reshuffle all data.

MAC Address as Identity

Stalker portals use MAC address as the primary credential. The mock server follows the same model:

• Each unique MAC gets its own isolated dataset.
• Predefined MACs map to specific ScenarioConfig shapes (see src/app/scenarios.ts).
• Unknown MACs use the sum of their byte values as a seed, producing unique but deterministic data.

In-Memory Only

No files or databases are written. All state (generated content + favorites) lives in process memory and resets on server restart. This is intentional — tests should not share state across runs.

Data Generation Pipeline

faker.seed(macToNumber(mac))
│
├── generateCategories('itv', N)  → itvCategories[]
│     └── generateChannels()      → channels Map<categoryId, channel[]>
│           └── generateEpg()     → epg Map<channelId, program[]>
│
├── generateCategories('vod', N)  → vodCategories[]
│     └── generateVodItems()      → vod Map<categoryId, item[]>
│           ├── normal VOD items
│           ├── is_series=1 items (fraction, Ministra flow)
│           └── embedded series[] items (fraction)
│
└── generateCategories('series', N) → seriesCategories[]
      └── generateSeriesItems()    → series Map<categoryId, item[]>
            └── generateSeasons()  → seasons Map<seriesItemId, season[]>

Response Shapes

All responses follow the Stalker portal.php envelope:

{ "js": <action-specific payload> }

get_categories

{
  "js": [
    { "id": "2001", "title": "Action", "alias": "action" },
    ...
  ]
}

get_ordered_list (content)

{
  "js": {
    "data": [
      {
        "id": "20001",
        "name": "...",
        "cmd": "ffrt4://vod/20001/index.m3u8",
        "screenshot_uri": "https://picsum.photos/seed/vod-20001/300/200",
        "cover": "https://picsum.photos/seed/vod-cover-20001/300/450",
        "description": "...",
        "actors": "...",
        "director": "...",
        "year": "2019",
        "rating_imdb": "7.3",
        "category_id": "2001",
        "is_series": 0,
        "has_files": 1
      }
    ],
    "total_items": 40,
    "max_page_items": 14,
    "cur_page": 1,
    "total_pages": 3
  }
}

get_ordered_list (seasons — when movie_id is present)

{
  "js": [
    {
      "id": "30001-s1",
      "name": "Season 1",
      "cmd": "ffrt4://series/30001/season/1",
      "series": ["30001-s1-e1", "30001-s1-e2", ...],
      "screenshot_uri": "https://picsum.photos/seed/30001-s1/300/200",
      "director": "...",
      "actors": "...",
      "year": "2021",
      "rating_imdb": "8.1"
    }
  ]
}

create_link

{
  "js": {
    "cmd": "https://test-streams.mux.dev/x36xhzz/x36xhzz.m3u8",
    "streamer_id": "1",
    "load": "",
    "error": ""
  }
}

The stream URL is selected from a pool of 4 real public HLS test streams. The choice is deterministic based on the cmd field's character sum, so the same item always returns the same stream.

get_short_epg

{
  "js": {
    "data": [
      {
        "id": "1",
        "name": "Channel Name: Program Title",
        "start": "2026-02-21T10:00:00.000Z",
        "stop": "2026-02-21T12:00:00.000Z",
        "start_timestamp": 1740128400,
        "stop_timestamp": 1740135600,
        "descr": "...",
        "category": "News"
      }
    ]
  }
}

get_short_epg returns the current program and upcoming items from the generated schedule, limited by the requested size.

get_epg_info

{
  "js": {
    "data": {
      "10000": [
        {
          "id": "1",
          "name": "Channel Name: Program Title",
          "start": "2026-02-21T10:00:00.000Z",
          "stop": "2026-02-21T12:00:00.000Z",
          "start_timestamp": 1740128400,
          "stop_timestamp": 1740135600,
          "descr": "...",
          "category": "News"
        }
      ]
    }
  }
}

get_epg_info returns bulk EPG keyed by channel id and filters the generated 7-day schedule from the current UTC day start through now + period.

EPG programs are generated as 2-hour slots across 7 days for each channel, starting at the current UTC day boundary.

Scenarios

Scenarios are defined in src/app/scenarios.ts. Each scenario is a ScenarioConfig:

interface ScenarioConfig {
  name: string;
  description: string;
  seed: number;
  categoryCount: { itv: number; vod: number; series: number };
  itemsPerCategory: number;
  seasonsPerSeries: number;
  episodesPerSeason: number;
  isSeriesFraction: number;      // 0–1: fraction of VOD with is_series=1
  embeddedSeriesFraction: number; // 0–1: fraction of VOD with embedded series[]
}

Adding a New Scenario

1. Add an entry to the SCENARIOS map in src/app/scenarios.ts.
2. Use any unique MAC address as the key (lowercase, colon-separated).
3. Document it in README.md and this file.

Favorites

Favorites are stored in a Map<mac, Set<itemId>> in src/app/data-store.ts. They persist for the lifetime of the server process and are shared across all requests for the same MAC.

Call POST /reset to clear all favorites (and regenerated data) between test runs.

Playwright Integration

apps/web-e2e/playwright.config.ts registers the mock server as a second webServer entry:

webServer: [
  {
    command: 'pnpm nx run web:serve',
    url: 'http://localhost:4200',
    reuseExistingServer: !process.env['CI'],
  },
  {
    command: 'pnpm nx run stalker-mock-server:serve',
    url: 'http://localhost:3210/health',
    reuseExistingServer: !process.env['CI'],
  },
]

Playwright waits for both servers to be healthy before starting tests. If either is already running (e.g. in local dev), it reuses the existing instance.

Test Isolation

Each stalker e2e test calls POST http://localhost:3210/reset in beforeEach to clear in-memory state. This ensures tests don't bleed favorites or other mutable state into each other.

The generated content (categories, items) is not cleared on reset — it's deterministic and doesn't need to be. Only in-memory favorites are cleared.

Recommended Test Structure

import { test, expect } from '@playwright/test';

const MOCK_URL = 'http://localhost:3210/portal.php';
const MOCK_MAC = '00:1A:79:00:00:01'; // default scenario

test.beforeEach(async ({ request }) => {
  await request.post('http://localhost:3210/reset');
});

test('browse VOD categories', async ({ page }) => {
  // Add portal via UI or programmatically via IndexedDB
  // Navigate to portal
  // Assert category list matches expected count (8 for default scenario)
});

Extension Points

• New content types: Add a new generator function in data-generator.ts and a new handler in handlers/.
• New scenarios: Add to SCENARIOS in scenarios.ts.
• Stateful session tokens: handshake.handler.ts generates a token from the MAC — extend this to track token expiry for testing re-auth flows.
• Error simulation: Add a special MAC or query param to trigger error responses (e.g. 401, 500) for testing error handling in the Stalker store.
• Slow responses: Add a MOCK_DELAY_MS env var and apply it in middleware for testing loading states.