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# Architecture — Detailed Reference
Comprehensive architectural overview of the OSS AI Data Analyst platform.
For a concise summary, see [../ARCHITECTURE.md](../ARCHITECTURE.md).
## Top-Level Module Map
```
oss-ai-data-analyst/
├── src/ Core engine (config, sync, parquet, profiling)
├── connectors/ Pluggable data connectors (keboola, jira)
├── auth/ Pluggable auth providers (google, password, desktop)
├── services/ Standalone background services
├── webapp/ Flask web portal (dashboard, catalog, API)
├── server/ Server deployment (setup, deploy, nginx, systemd)
├── scripts/ Analyst-side utility scripts (sync, DuckDB, dev server)
├── config/ Instance configuration (loader, templates)
├── examples/ Example notification scripts
├── tests/ Test suite
├── dev_docs/ Internal development documentation
└── docs/ User-facing documentation
```
## Block Diagram
```
┌─────────────────────────────────────────────────────────────────────────────┐
│ EXTERNAL DATA SOURCES │
│ ┌──────────┐ ┌──────────┐ ┌──────────┐ ┌──────────┐ │
│ │ Keboola │ │ Jira │ │ CSV │ │ BigQuery │ │
│ │ Storage │ │ Cloud │ │ (plan) │ │ (plan) │ │
│ └────┬─────┘ └────┬─────┘ └──────────┘ └──────────┘ │
└────────┼──────────────┼────────────────────────────────────────────────────┘
│ │
▼ ▼
┌─────────────────────────────────────────────────────────────────────────────┐
│ CONNECTORS (connectors/) auto-discovery via importlib │
│ │
│ ┌──────────────────────────┐ ┌─────────────────────────────────────┐ │
│ │ connectors/keboola/ │ │ connectors/jira/ │ │
│ │ │ │ │ │
│ │ adapter.py │ │ webhook.py Flask blueprint │ │
│ │ KeboolaDataSource (ABC) │ │ service.py Jira REST API client │ │
│ │ full/incr/partitioned │ │ transform.py JSON -> 6 Parquet tbl│ │
│ │ │ │ incremental_transform.py realtime │ │
│ │ client.py │ │ file_lock.py POSIX advisory locks │ │
│ │ Keboola Storage API │ │ │ │
│ │ type mapping + cache │ │ scripts/ backfill, SLA poll, │ │
│ │ │ │ consistency check │ │
│ │ tests/ │ │ systemd/ jira-sla-poll, │ │
│ └──────────────────────────┘ │ jira-consistency │ │
│ │ tests/ │ │
│ Registry: src/data_sync.py └─────────────────────────────────────┘ │
│ create_data_source(type) -> │
│ importlib("connectors.{type}.adapter") │
└─────────────────────────────────────────────────────────────────────────────┘
▼ Parquet files
┌─────────────────────────────────────────────────────────────────────────────┐
│ CORE ENGINE (src/) │
│ │
│ ┌─────────────────────┐ ┌──────────────────┐ ┌──────────────────────┐ │
│ │ data_sync.py │ │ config.py │ │ profiler.py │ │
│ │ DataSource ABC │ │ data_description │ │ Parquet -> stats │ │
│ │ SyncState (JSON) │ │ .md parser │ │ alerts, sampling │ │
│ │ DataSyncManager │ │ TableConfig │ │ -> profiles.json │ │
│ │ create_data_source()│ │ WhereFilter │ └──────────────────────┘ │
│ └─────────────────────┘ │ ForeignKey │ │
│ │ get_config() │ ┌──────────────────────┐ │
│ └──────────────────┘ │ parquet_manager.py │ │
│ │ CSV->Parquet, merge │ │
│ │ upsert, schema │ │
│ └──────────────────────┘ │
└─────────────────────────────────────────────────────────────────────────────┘
│ /data/src_data/parquet/
┌─────────────────────────────────────────────────────────────────────────────┐
│ AUTH PROVIDERS (auth/) auto-discovery via scan │
│ │
│ ┌────────────────┐ ┌────────────────┐ ┌──────────────────────┐ │
│ │ auth/google/ │ │ auth/password/ │ │ auth/desktop/ │ │
│ │ │ │ │ │ │ │
│ │ Google OAuth │ │ Email+password │ │ JWT for desktop app │ │
│ │ SSO (Authlib) │ │ Argon2 hash │ │ visible=False │ │
│ │ domain restrict │ │ SendGrid email │ │ (API-only, not login) │ │
│ │ order=10 │ │ order=20 │ │ order=100 │ │
│ └────────────────┘ └────────────────┘ └──────────────────────┘ │
│ │
│ ABC: AuthProvider (get_name, get_blueprint, get_login_button, is_avail.) │
│ Discovery: discover_providers() -> scans auth/*/provider.py │
│ Contract: all providers set session["user"] = {email, name, picture} │
└─────────────────────────────────────────────────────────────────────────────┘
│ Blueprints registered in Flask app
┌─────────────────────────────────────────────────────────────────────────────┐
│ WEB PORTAL (webapp/) │
│ │
│ ┌───────────────────┐ ┌──────────────────────────────────────────────┐ │
│ │ app.py (Flask) │ │ Pages │ │
│ │ - discover auth │ │ /dashboard - account, stats, setup │ │
│ │ providers │ │ /catalog - data catalog + profiles │ │
│ │ - register │ │ /corporate-memory - knowledge + voting │ │
│ │ blueprints │ │ /activity-center - intelligence overview │ │
│ │ - inject_config() │ └──────────────────────────────────────────────┘ │
│ │ - routes │ │
│ └───────────────────┘ ┌──────────────────────────────────────────────┐ │
│ │ API Endpoints │ │
│ ┌───────────────────┐ │ /webhooks/jira (HMAC, -> jira connector)│ │
│ │ webapp services │ │ /api/telegram/* (link/unlink/status) │ │
│ │ user_service │ │ /api/desktop/* (JWT, scripts, run) │ │
│ │ account_service │ │ /api/sync-settings (GET/POST) │ │
│ │ sync_settings_svc │ │ /api/corporate-memory/* (CRUD, votes) │ │
│ │ telegram_service │ │ /api/catalog/profile/<table> │ │
│ │ email_service │ │ /health (service health) │ │
│ │ health_service │ └──────────────────────────────────────────────┘ │
│ │ corporate_memory │ │
│ └───────────────────┘ Config chain: instance.yaml -> loader -> Config -> │
│ inject_config() -> {{ config.X }} in Jinja │
└─────────────────────────────────────────────────────────────────────────────┘
┌─────────────────────────────────────────────────────────────────────────────┐
│ BACKGROUND SERVICES (services/) each = __main__.py + systemd │
│ │
│ ┌────────────────────────┐ ┌─────────────────────────────────────────┐ │
│ │ services/telegram_bot/ │ │ services/ws_gateway/ │ │
│ │ │ │ │ │
│ │ bot.py polling + │ │ gateway.py WebSocket TCP:8765 │ │
│ │ HTTP socket │ │ + HTTP dispatch socket │ │
│ │ runner.py script exec │ │ auth.py JWT validation │ │
│ │ sender.py msg dispatch │ │ config.py gateway config │ │
│ │ dispatch.py -> WS gw │ │ │ │
│ │ storage.py JSON state │ │ Heartbeat: ping/pong, 3 miss = drop │ │
│ │ status.py /status cmd │ │ Per-user connection limit (5) │ │
│ │ │ │ │ │
│ │ Always running (systemd)│ │ Always running (systemd) │ │
│ └────────────────────────┘ └─────────────────────────────────────────┘ │
│ │
│ ┌────────────────────────┐ ┌─────────────────────────────────────────┐ │
│ │ services/ │ │ services/ │ │
│ │ corporate_memory/ │ │ session_collector/ │ │
│ │ │ │ │ │
│ │ collector.py │ │ collector.py │ │
│ │ Scans CLAUDE.local.md │ │ Copies .jsonl from user homes │ │
│ │ -> Claude Haiku -> JSON│ │ to /data/user_sessions/ │ │
│ │ MD5 change detection │ │ Idempotent, atomic writes │ │
│ │ prompts.py │ │ │ │
│ │ LLM prompts for │ │ Timer: every 6 hours │ │
│ │ knowledge extraction │ │ │ │
│ │ │ │ │ │
│ │ Timer: every 30 min │ │ │ │
│ └────────────────────────┘ └─────────────────────────────────────────┘ │
└─────────────────────────────────────────────────────────────────────────────┘
│ Unix sockets + /data/ filesystem
┌─────────────────────────────────────────────────────────────────────────────┐
│ SERVER INFRASTRUCTURE (server/) │
│ │
│ ┌──────────────────┐ ┌────────────────────┐ ┌───────────────────────┐ │
│ │ Deployment │ │ User Management │ │ Web Server │ │
│ │ setup.sh │ │ bin/add-analyst │ │ webapp-nginx.conf │ │
│ │ deploy.sh (CI/CD) │ │ bin/list-analysts │ │ webapp.service │ │
│ │ webapp-setup.sh │ │ bin/notify-runner │ │ SSL (Let's Encrypt) │ │
│ │ sudoers rules │ │ bin/notify-scripts │ │ Gunicorn + Unix sock │ │
│ └──────────────────┘ └────────────────────┘ └───────────────────────┘ │
│ │
│ Groups: dataread (analysts) | data-private (privileged) | data-ops (admin) │
│ │
│ /data/ │
│ ├── src_data/parquet/ shared data (readonly for analysts) │
│ ├── src_data/metadata/ sync_state.json, profiles.json │
│ ├── src_data/raw/jira/ webhook JSON, attachments │
│ ├── docs/ , scripts/ documentation, helper scripts │
│ ├── notifications/ telegram_users, desktop_users, codes │
│ ├── corporate-memory/ knowledge.json, votes.json │
│ └── user_sessions/ centralized Claude Code transcripts │
└─────────────────────────────────────────────────────────────────────────────┘
│ rsync (SSH) - scripts/sync_data.sh (bi-directional)
┌─────────────────────────────────────────────────────────────────────────────┐
│ ANALYST WORKSTATION (local) │
│ │
│ server/ (read-only, rsynced from broker) │
│ ├── parquet/, docs/, scripts/, metadata/ │
│ │
│ user/ (writable workspace, backed up to server) │
│ ├── duckdb/analytics.duckdb SQL views over parquet │
│ ├── notifications/*.py custom notification scripts │
│ ├── sessions/ Claude Code transcripts │
│ └── artifacts/ analysis outputs │
│ │
│ .claude/rules/ corporate memory knowledge rules │
│ │
│ Claude Code <- local analysis over DuckDB + Parquet
└─────────────────────────────────────────────────────────────────────────────┘
```
## Auto-Discovery Patterns
The platform uses three symmetrical auto-discovery mechanisms. Adding a new
connector, auth method, or service requires no changes to existing code.
### 1. Connector Discovery (`src/data_sync.py`)
```
config/instance.yaml -> data_source.type: "keboola"
-> importlib.import_module("connectors.keboola.adapter")
-> KeboolaDataSource (implements DataSource ABC)
```
- Factory: `create_data_source(type)` in `src/data_sync.py`
- Connectors live in `connectors/{name}/adapter.py`
- Must export a `DataSource` subclass or a `create_data_source()` factory function
- Keboola is hard-coded for ImportError handling; all others use dynamic import
### 2. Auth Provider Discovery (`auth/__init__.py`)
```
startup -> scan auth/*/provider.py
-> import `provider` instance
-> filter by is_available() (checks env vars)
-> register blueprint + login button in Flask
```
- ABC: `AuthProvider` with methods `get_name()`, `get_blueprint()`, `get_login_button()`, `is_available()`, `init_app()`
- Session contract: all providers set `session["user"] = {email, name, picture}`
- Login page renders buttons dynamically, sorted by `order` field
### 3. Service Pattern (`services/*/__main__.py`)
```
python -m services.<name> # entry point
services/<name>/systemd/ # unit files
deploy.sh auto-discovers # systemd/* in each service dir
```
- Each service is self-contained: code, systemd units, and config in one directory
- `deploy.sh` scans `services/*/systemd/*.service` and `connectors/*/systemd/*.service`
- Long-running services (telegram_bot, ws_gateway) use async dual-server model
- Periodic services (corporate_memory, session_collector) are systemd timer oneshots
## Data Flows
### Pull Sync (Keboola)
```
Keboola Storage API
-> connectors/keboola/client.py (export CSV with filters)
-> src/parquet_manager.py (convert to typed Parquet)
-> /data/src_data/parquet/ (stored on broker)
-> rsync to analyst (scripts/sync_data.sh)
-> DuckDB views (scripts/setup_views.sh)
```
Sync strategies: `full_refresh`, `incremental`, `partitioned`, `chunked_initial_load`.
### Push Sync (Jira)
```
Jira Cloud webhook (issue created/updated/deleted)
-> connectors/jira/webhook.py (HMAC-SHA256 verification)
-> connectors/jira/service.py (fetch full issue + attachments)
-> /data/src_data/raw/jira/issues/ (atomic JSON write)
-> connectors/jira/incremental_transform.py (update monthly Parquet)
-> /data/src_data/parquet/jira/ (6 tables: issues, comments,
attachments, changelog,
issuelinks, remote_links)
```
Background jobs supplement the webhook pipeline:
- `jira-sla-poll` (every 5 min): refreshes SLA fields for open tickets
- `jira-consistency` (every 6h): detects and backfills missing issues
### Notification Pipeline
```
~/user/notifications/*.py analyst's custom scripts
-> server/bin/notify-runner (cron, executes with timeout)
-> cooldown check (~/.notifications/state/)
├-> services/telegram_bot/ (Unix socket /run/notify-bot/bot.sock)
│ -> Telegram chat message (text or photo)
└-> services/ws_gateway/ (Unix socket /run/ws-gateway/ws.sock)
-> WebSocket push to desktop app
```
Script output format:
```json
{
"notify": true,
"title": "Revenue dropped 25%",
"message": "Details...",
"cooldown": "6h",
"image_path": "/tmp/chart.png"
}
```
### Knowledge Loop (Corporate Memory)
```
Analyst writes CLAUDE.local.md (insights, patterns, tips)
-> scripts/sync_data.sh (uploads to server)
-> services/corporate_memory/ (timer, every 30 min)
-> MD5 change detection
-> Claude Haiku extracts knowledge items
-> /data/corporate-memory/knowledge.json
-> webapp /corporate-memory (voting UI: upvote/downvote)
-> scripts/sync_data.sh (downloads to analyst)
-> .claude/rules/ (rules for Claude Code)
-> Claude Code uses rules in next session
```
## Module Reference
### Core Engine (`src/`)
| File | Lines | Responsibility |
|------|-------|----------------|
| `data_sync.py` | ~1400 | `DataSource` ABC, `SyncState`, `DataSyncManager`, connector factory |
| `config.py` | ~600 | Parse `data_description.md` YAML blocks, `TableConfig`, `WhereFilter`, `ForeignKey` |
| `parquet_manager.py` | ~750 | CSV-to-Parquet conversion, merge, upsert, schema enforcement |
| `profiler.py` | ~1200 | Data profiling: stats, alerts, type classification -> `profiles.json` |
### Connectors (`connectors/`)
| Module | Files | Sync Model | Description |
|--------|-------|------------|-------------|
| `keboola/` | adapter.py, client.py, tests/ | Pull (DataSource ABC) | Keboola Storage API, type mapping, metadata caching (24h TTL) |
| `jira/` | webhook.py, service.py, transform.py, incremental_transform.py, file_lock.py, scripts/, systemd/, tests/ | Push (webhook) | Real-time webhook pipeline, SLA polling, consistency monitoring, 6 output Parquet tables |
### Auth Providers (`auth/`)
| Provider | Available when | Login UI | Order | Description |
|----------|---------------|----------|-------|-------------|
| `google/` | `GOOGLE_CLIENT_ID` set | Yes | 10 | Google OAuth SSO with domain restriction |
| `password/` | `SENDGRID_API_KEY` set | Yes | 20 | Email + password for external users (Argon2, rate limiting) |
| `desktop/` | `DESKTOP_JWT_SECRET` set | No (API-only) | 100 | JWT tokens for native desktop app |
### Background Services (`services/`)
| Service | Type | Schedule | Description |
|---------|------|----------|-------------|
| `telegram_bot/` | Long-running | Always on | Telegram polling + HTTP dispatch socket, script execution, /status /test commands |
| `ws_gateway/` | Long-running | Always on | WebSocket TCP:8765 + HTTP dispatch socket, JWT auth, heartbeat |
| `corporate_memory/` | Timer oneshot | Every 30 min | AI knowledge extraction from CLAUDE.local.md via Claude Haiku |
| `session_collector/` | Timer oneshot | Every 6 hours | Copy session .jsonl from user homes to central storage |
### Web Portal (`webapp/`)
| File | Responsibility |
|------|----------------|
| `app.py` | Flask factory, blueprint registration, route definitions, context processors |
| `config.py` | Load `instance.yaml`, expose `Config` to templates |
| `auth.py` | Core auth infrastructure: `login_required`, `validate_email_domain`, `/login`, `/logout` |
| `user_service.py` | Username derivation, SSH key validation, system account creation |
| `account_service.py` | Dashboard account widget data, cron info, sync status |
| `sync_settings_service.py` | Per-user dataset sync preferences |
| `telegram_service.py` | Telegram account linking/unlinking |
| `desktop_auth.py` | JWT generation/validation, desktop app link state |
| `password_auth.py` | Password auth implementation (Argon2, rate limiting, token workflow) |
| `email_service.py` | SendGrid integration for setup/reset emails |
| `corporate_memory_service.py` | Knowledge CRUD, voting, user rules regeneration |
| `health_service.py` | System health checks (services, timers, disk, load, webhooks) |
| `notification_images.py` | Serve chart PNGs generated by notification runner |
| `utils/metric_parser.py` | Parse business metric YAML definitions for catalog UI |
### Server Infrastructure (`server/`)
| File | Responsibility |
|------|----------------|
| `setup.sh` | Initial server bootstrap (groups, users, directories, venv) |
| `deploy.sh` | CI/CD deployment (git pull, deps, scripts, services, ACLs) |
| `webapp-setup.sh` | Nginx + SSL + Gunicorn setup |
| `webapp-nginx.conf` | Nginx reverse proxy config (HTTPS, WebSocket upgrade) |
| `webapp.service` | Systemd unit for Gunicorn |
| `sudoers-deploy` | Sudo rules for deploy user (least-privilege) |
| `sudoers-webapp` | Sudo rules for www-data |
| `bin/add-analyst` | Create analyst user with workspace structure |
| `bin/list-analysts` | List registered analysts |
| `bin/notify-runner` | Execute user notification scripts, dispatch to bot + gateway |
| `bin/notify-scripts` | List/run notification scripts for a user |
### Analyst Scripts (`scripts/`)
| File | Responsibility |
|------|----------------|
| `sync_data.sh` | Bi-directional rsync: download data, upload workspace, refresh DuckDB |
| `setup_views.sh` | Create/replace DuckDB views over all Parquet files |
| `duckdb_manager.py` | DuckDB setup utility |
| `dev_run.py` | Development server with auth bypass |
| `collect_session.py` | Session transcript collector (used by service) |
| `generate_user_sync_configs.py` | Generate per-user sync config files |
## Analyst Workspace Layout
Created by `server/bin/add-analyst` for each registered user:
```
/home/{username}/
├── server/ read-only symlinks to shared data
│ ├── parquet/ -> /data/src_data/parquet
│ ├── docs/ -> /data/docs
│ ├── scripts/ -> /data/scripts
│ ├── metadata/ -> /data/src_data/metadata
│ └── jira_attachments/ -> /data/src_data/raw/jira/attachments
├── user/ writable workspace (backed up to server)
│ ├── duckdb/ local DuckDB database
│ ├── notifications/ custom notification scripts (*.py)
│ ├── artifacts/ analysis outputs
│ ├── scripts/ user helper scripts
│ ├── parquet/ user Parquet files
│ └── sessions/ Claude Code session transcripts
├── .notifications/ notification runner state
│ ├── state/ cooldown tracking (JSON per script)
│ └── logs/ runner logs
└── .claude/
└── rules/ corporate memory knowledge rules (auto-synced)
```
## Security Model
### System Groups
| Group | Access |
|-------|--------|
| `data-ops` | Full admin access to all server resources |
| `dataread` | Read access to public Parquet data |
| `data-private` | Read access to sensitive/restricted data |
### Authentication Layers
| Layer | Mechanism | Scope |
|-------|-----------|-------|
| Web portal | Google OAuth / email+password | Browser sessions |
| Desktop app | JWT Bearer tokens | API endpoints (`/api/desktop/*`) |
| Jira webhook | HMAC-SHA256 signature | Webhook endpoint |
| SSH access | Key-based auth only | Data sync (rsync) |
| Inter-service | Unix socket permissions | Bot, gateway, webapp |
### Permission Boundaries
- Analysts cannot access other users' home directories
- Webapp (www-data) uses sudoers-whitelisted commands for user operations
- Deploy user has explicit sudo rules for service management
- Staging directory (`/tmp/data_analyst_staging`) uses setgid for group ownership
- All JSON state files written atomically: `tempfile.mkstemp()` + `os.fchmod()` + `os.replace()`
## Configuration Chain
```
config/instance.yaml (instance-specific, not committed)
| loaded by config/loader.py
| ${ENV_VAR} references resolved from .env / environment
v
webapp/config.py (Flask Config class)
| _load_instance_config() at module level
| _get(config, *keys) for safe nested access
v
inject_config() context processor (exposes Config to templates)
v
{{ config.INSTANCE_NAME }} in Jinja2 (all templates have access)
```
Validation: `config/loader.py` checks required fields at startup (`instance.name`,
`auth.allowed_domain`, `server.host`, `server.hostname`, `auth.webapp_secret_key`).
Missing required fields cause immediate startup failure with a clear error message.
## Server Filesystem Layout
```
/opt/data-analyst/
├── repo/ git repository (deployed via CI/CD)
├── .venv/ Python virtual environment
├── logs/ application logs
└── .env secrets (mode 0640)
/data/
├── src_data/
│ ├── parquet/ shared Parquet files (readonly for analysts)
│ ├── metadata/ sync_state.json, profiles.json, table_metadata.json
│ └── raw/jira/ webhook JSON files, attachments
├── docs/ documentation and schema
├── scripts/ helper scripts synced to analysts
├── notifications/ telegram_users.json, desktop_users.json, pending_codes.json
├── corporate-memory/ knowledge.json, votes.json, user_hashes.json
└── user_sessions/ centralized Claude Code session transcripts
/run/
├── notify-bot/bot.sock Telegram bot HTTP socket
├── ws-gateway/ws.sock WebSocket gateway HTTP socket
└── webapp/webapp.sock Gunicorn WSGI socket
```
## CI/CD
### Deploy Guard (`.github/workflows/deploy-guard.yml`)
Runs on every pull request:
1. `pytest tests/test_deploy_guard.py` - validates deploy.sh/sudoers/systemd consistency
2. `pytest tests/test_sync_data.py -m "not live"` - validates sync script reliability
3. `visudo -cf server/sudoers-*` - validates sudoers syntax in Docker
### Deployment (`.github/workflows/deploy.yml.example`)
Runs on push to main (or manual trigger):
1. SSH into server
2. Execute `server/deploy.sh` (git pull, deps, scripts, services, ACLs)

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# VM Test Plan - Self-Service Data Onboarding
End-to-end test of the full platform on a clean VM with a new GitHub repository.
## Prerequisites
- Clean Ubuntu 22.04+ VM (or Debian 12) with root access
- GitHub account with ability to create repositories
- Domain name pointing to the VM (or use IP + skip SSL)
- Keboola project with Storage API token (for discovery/sync testing)
- Google OAuth credentials (for login testing)
---
## Step 0: Create GitHub Repository & Push
**On your local machine:**
```bash
cd /Users/padak/github/oss-ai-data-analyst
# Create repo on GitHub (pick org/name)
gh repo create YOUR_ORG/ai-data-analyst --private --source=. --push
# Verify
gh repo view YOUR_ORG/ai-data-analyst
```
**Expected:** Repo created, code pushed, visible on GitHub.
---
## Step 1: VM Initial Setup
**On the VM as root:**
```bash
# Clone the repo
REPO_URL="git@github.com:YOUR_ORG/ai-data-analyst.git"
APP_DIR="/opt/data-analyst"
mkdir -p $APP_DIR
ssh-keygen -t ed25519 -f /root/.ssh/deploy_key -N ""
# Add deploy key to GitHub repo (Settings -> Deploy keys)
sudo -u deploy git clone $REPO_URL $APP_DIR/repo
# Run setup
cd $APP_DIR/repo
REPO_URL=$REPO_URL bash server/setup.sh
```
### Checklist
| # | Check | Command |
|---|-------|---------|
| 1.1 | Groups created | `getent group data-ops dataread data-private` |
| 1.2 | Deploy user exists | `id deploy` |
| 1.3 | Directory structure | `ls -la /opt/data-analyst/` |
| 1.4 | Python venv works | `/opt/data-analyst/.venv/bin/python -c "import flask; print('OK')"` |
| 1.5 | Management scripts | `which add-analyst list-analysts` |
---
## Step 2: Webapp Setup
```bash
export SERVER_HOSTNAME="data.yourdomain.com" # or skip SSL with IP
bash server/webapp-setup.sh
```
Then edit `/opt/data-analyst/.env`:
```bash
# Required
WEBAPP_SECRET_KEY="$(python3 -c 'import secrets; print(secrets.token_hex(32))')"
GOOGLE_CLIENT_ID="your-google-client-id"
GOOGLE_CLIENT_SECRET="your-google-client-secret"
SERVER_HOST="YOUR_VM_IP"
SERVER_HOSTNAME="data.yourdomain.com"
# For Keboola discovery/sync
KEBOOLA_STORAGE_TOKEN="your-token"
KEBOOLA_STACK_URL="https://connection.keboola.com"
KEBOOLA_PROJECT_ID="your-project-id"
DATA_SOURCE="keboola"
DATA_DIR="/data/src_data"
```
### Checklist
| # | Check | Command |
|---|-------|---------|
| 2.1 | Nginx running | `systemctl status nginx` |
| 2.2 | Webapp running | `systemctl status webapp` |
| 2.3 | SSL cert (if domain) | `curl -I https://data.yourdomain.com/health` |
| 2.4 | Health endpoint | `curl http://localhost:5000/health` (or via nginx) |
| 2.5 | Login page loads | Browser: `https://data.yourdomain.com/login` |
---
## Step 3: Instance Configuration
```bash
cd /opt/data-analyst/repo
cp config/instance.yaml.example config/instance.yaml
```
Edit `config/instance.yaml` with:
- `instance.name` / `instance.subtitle`
- `server.hostname` / `server.host`
- `auth.allowed_domain` (your Google domain)
- `data_source.type: "keboola"` + keboola settings
- `catalog.categories` (at least one, e.g., `crm: {label: "CRM", icon: "crm"}`)
### Checklist
| # | Check | Command |
|---|-------|---------|
| 3.1 | Config loads | `cd /opt/data-analyst/repo && .venv/bin/python -c "from config.loader import load_instance_config; print(load_instance_config())"` |
| 3.2 | Webapp picks it up | Restart webapp, check login page shows instance name |
---
## Step 4: Create Admin Account & Login
1. Login via Google OAuth in browser
2. Register account with SSH key
3. Verify the user is admin:
```bash
id YOUR_USERNAME # should be in data-ops or sudo group
# If not admin, manually add:
usermod -aG data-ops YOUR_USERNAME
```
### Checklist
| # | Check | Command |
|---|-------|---------|
| 4.1 | Google OAuth works | Login via browser |
| 4.2 | Account created | `list-analysts` shows your username |
| 4.3 | Dashboard loads | Browser: /dashboard shows data stats |
| 4.4 | Admin access | Browser: /admin/tables loads (no 403) |
---
## Step 5: Test Discovery API (Phase 1)
In browser, go to `/admin/tables` and click "Discover tables from source".
### Checklist
| # | Check | Expected |
|---|-------|----------|
| 5.1 | Discovery button works | Loading spinner, then tables appear |
| 5.2 | Tables grouped by bucket | Buckets shown as collapsible sections |
| 5.3 | Table details shown | Name, columns, row count, size for each table |
| 5.4 | "Available" badge | All tables show "Available" (none registered yet) |
| 5.5 | API direct test | `curl -b cookies.txt https://HOST/api/admin/discover-tables \| jq .total` |
---
## Step 6: Test Table Registry (Phase 2)
### 6a: Register tables via Admin UI
1. Click "Register" on a table in discovery results
2. Fill in: sync_strategy=full_refresh, confirm primary key
3. Click "Register Table"
4. Repeat for 2-3 more tables (try incremental too)
### 6b: Verify registry
```bash
# On server
cat /data/src_data/metadata/table_registry.json | python3 -m json.tool | head -30
# Check generated data_description.md
head -10 /opt/data-analyst/repo/docs/data_description.md
# Should show: <!-- AUTO-GENERATED from table_registry.json -->
# Check audit log
cat /data/src_data/metadata/registry_audit.log
```
### 6c: Test via API
```bash
# List registry
curl -b cookies.txt https://HOST/api/admin/registry | jq '.tables | length'
# Update a table
curl -b cookies.txt -X PUT https://HOST/api/admin/registry/in.c-crm.company \
-H "Content-Type: application/json" \
-d '{"description": "Updated via API", "version": CURRENT_VERSION}'
# Delete a table
curl -b cookies.txt -X DELETE https://HOST/api/admin/registry/in.c-crm.company \
-H "Content-Type: application/json" \
-d '{"version": CURRENT_VERSION}'
```
### Checklist
| # | Check | Expected |
|---|-------|----------|
| 6.1 | Register table | Success, table appears in registry panel |
| 6.2 | Badge changes | Registered tables show green "Registered" badge |
| 6.3 | data_description.md | Generated with AUTO-GENERATED header + checksum |
| 6.4 | Audit log written | Actions logged with timestamps and emails |
| 6.5 | Optimistic locking | Stale version POST returns 409 |
| 6.6 | Edit table | PUT changes description/strategy |
| 6.7 | Delete table | Table removed, badge reverts to "Available" |
---
## Step 7: Test Data Sync + Auto-Profiling (Phase 3)
```bash
cd /opt/data-analyst/repo
source .venv/bin/activate
# Run sync for registered tables
python -m src.data_sync
```
### Checklist
| # | Check | Expected |
|---|-------|----------|
| 7.1 | Sync completes | Tables downloaded, Parquet created |
| 7.2 | Schema.yml generated | `cat docs/schema.yml \| head` |
| 7.3 | Auto-profiling ran | Log shows "Auto-profiling: N profiled" |
| 7.4 | profiles.json exists | `ls -la /data/src_data/metadata/profiles.json` |
| 7.5 | Catalog shows profiles | Browser: /catalog -> click table -> profile data loads |
---
## Step 8: Test Per-Table Subscriptions (Phase 4)
### 8a: Via API
```bash
# Get current subscriptions
curl -b cookies.txt https://HOST/api/table-subscriptions | jq .
# Switch to explicit mode, subscribe to specific tables
curl -b cookies.txt -X POST https://HOST/api/table-subscriptions \
-H "Content-Type: application/json" \
-d '{
"table_mode": "explicit",
"tables": {"company": true, "contact": true, "events": false}
}'
```
### 8b: Via Catalog UI
1. Go to /catalog
2. Tables should show subscription status (all subscribed in "all" mode)
3. After switching to "explicit" mode via API, unsubscribed tables should be visually different
### Checklist
| # | Check | Expected |
|---|-------|----------|
| 8.1 | Default is "all" mode | GET returns `table_mode: "all"` |
| 8.2 | Switch to explicit | POST succeeds, settings saved |
| 8.3 | Config YAML updated | `cat /home/USERNAME/.sync_settings.yaml` shows `table_mode: explicit` |
| 8.4 | Catalog reflects subs | Subscribed vs unsubscribed tables visually distinct |
---
## Step 9: Test Smart Sync (Phase 5)
### 9a: Check rsync filter generation
```bash
# After setting explicit subscriptions:
cat /home/USERNAME/.sync_rsync_filter
# Should show include/exclude rules
```
### 9b: Test from analyst machine
```bash
# On analyst machine (or simulate):
bash server/scripts/sync_data.sh --dry-run
# Should show filter-based sync when explicit mode is active
```
### Checklist
| # | Check | Expected |
|---|-------|----------|
| 9.1 | Filter file exists | `.sync_rsync_filter` created in user home |
| 9.2 | Correct include/exclude | Subscribed tables included, others excluded |
| 9.3 | Dry-run uses filter | `--filter="merge ..."` in rsync output |
| 9.4 | Fallback works | Without filter file, syncs everything (backwards compat) |
---
## Step 10: Migration Test (One-Time Bootstrap)
If you already have a `docs/data_description.md` with tables defined:
```bash
python3 -c "
from src.table_registry import TableRegistry
from pathlib import Path
registry = TableRegistry.import_from_data_description(
Path('docs/data_description.md'),
Path('/data/src_data/metadata/table_registry.json'),
registered_by='migration@test.com'
)
print(f'Migrated {len(registry.list_tables())} tables')
print(f'Version: {registry.version}')
"
```
### Checklist
| # | Check | Expected |
|---|-------|----------|
| 10.1 | Migration succeeds | All tables imported |
| 10.2 | Registry JSON valid | `cat table_registry.json \| python3 -m json.tool` |
| 10.3 | migrated_from marker | `"migrated_from": "docs/data_description.md"` in metadata |
| 10.4 | Admin UI shows tables | /admin/tables lists all migrated tables |
---
## Step 11: Regression Tests
```bash
cd /opt/data-analyst/repo
source .venv/bin/activate
python -m pytest tests/ -v
```
### Checklist
| # | Check | Expected |
|---|-------|----------|
| 11.1 | All tests pass | 132+ tests, 0 failures |
| 11.2 | No import errors | All modules load cleanly |
---
## Quick Smoke Test Script
Run this after full setup to verify the critical path:
```bash
#!/bin/bash
# smoke_test.sh - Quick verification of self-service onboarding
set -e
APP_DIR="/opt/data-analyst/repo"
cd "$APP_DIR"
source .venv/bin/activate
echo "=== Smoke Test ==="
# 1. Tests
echo "[1/5] Running tests..."
python -m pytest tests/ -q --tb=short
echo " PASS"
# 2. Registry module
echo "[2/5] Testing Table Registry..."
python -c "
from src.table_registry import TableRegistry
from pathlib import Path
import tempfile
r = TableRegistry(Path(tempfile.mktemp(suffix='.json')))
r.register_table({'id': 'test.t', 'name': 't', 'primary_key': 'id', 'sync_strategy': 'full_refresh'}, 'test')
assert r.is_registered('test.t')
r.unregister_table('test.t')
assert not r.is_registered('test.t')
print(' PASS')
"
# 3. Discovery (needs Keboola credentials)
echo "[3/5] Testing Discovery API..."
python -c "
try:
from src.data_sync import create_data_source
ds = create_data_source()
tables = ds.discover_tables()
print(f' PASS - Discovered {len(tables)} tables')
except Exception as e:
print(f' SKIP - {e}')
"
# 4. Profiler API
echo "[4/5] Testing Profiler API..."
python -c "
from src.profiler import profile_changed_tables
result = profile_changed_tables([])
assert result == {'success': 0, 'errors': 0, 'skipped': 0}
print(' PASS')
"
# 5. Webapp imports
echo "[5/5] Testing Webapp imports..."
python -c "
from webapp.auth import admin_required, login_required
from webapp.sync_settings_service import get_table_subscriptions, generate_rsync_filter
from src.table_registry import TableRegistry, ConflictError
print(' PASS')
"
echo ""
echo "=== All smoke tests passed ==="
```
---
## Troubleshooting
| Problem | Fix |
|---------|-----|
| `/admin/tables` returns 403 | User not in `data-ops` group. Run `usermod -aG data-ops USERNAME` |
| Discovery returns empty | Check `KEBOOLA_STORAGE_TOKEN` in `.env`, verify `DATA_SOURCE=keboola` |
| Profiles not generated | Check `/data/src_data/parquet/` has parquet files, check DuckDB installed |
| Rsync filter not created | Check `sudo` permissions for `www-data` in sudoers-webapp |
| `data_description.md` not updating | Check write permissions on `docs/` directory |
| Webapp won't start | Check `journalctl -u webapp -n 50` for errors |