ddadmin
2e48f6065a
- Добавлен сервис superset-init в docker-compose для автоматической инициализации - Созданы Python-скрипты для инициализации подключения ClickHouse и создания датасетов - Создан скрипт для автоматического создания дашборда с 10 чартами - Создан скрипт экспорта дашборда в JSON - Добавлен экспортируемый JSON дашборда (ecommerce_analytics.zip.json) - Обновлен Makefile с командами superset-init, superset-dashboard, superset-export - Добавлена документация docs/SUPERSET_DASHBOARD.md Дашборд включает: - KPI блок (Total Events, Unique Users, Sessions, Avg/Session) - Динамика трафика (Events by Hour, Traffic by Device) - География (World Map) - Маркетинг (UTM Effectiveness Table, Top Pages) - Качество данных (DQ Summary) - Native Filters (Date Range, Country, Device, Browser)
108 lines
4.1 KiB
Python
108 lines
4.1 KiB
Python
#!/usr/bin/env python3
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"""
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================================================================================
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Экспорт дашборда Superset в JSON-формат
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================================================================================
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Назначение:
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- Экспорт созданного дашборда в JSON для версионирования
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- Формат совместимый с superset import-dashboards
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Запуск:
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docker compose exec superset python /app/superset_init/export_dashboard.py
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================================================================================
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"""
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import json
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import sys
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import os
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sys.path.insert(0, '/app')
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try:
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from superset.app import create_app
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from superset.dashboards.data_access_layer import DashboardDAO
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from superset.charts.data_access_layer import ChartDAO
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except ImportError as e:
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print(f"Error importing: {e}")
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sys.exit(1)
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def export_dashboard(slug: str, output_path: str):
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"""Экспорт дашборда в JSON"""
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app = create_app()
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with app.app_context():
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dashboard = DashboardDAO.get_by_slug(slug)
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if not dashboard:
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print(f"Dashboard with slug '{slug}' not found")
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return False
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# Собираем данные дашборда
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dashboard_data = {
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"dashboards": [
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{
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"__Dashboard__": {
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"dashboard_title": dashboard.dashboard_title,
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"description": dashboard.description,
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"slug": dashboard.slug,
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"json_metadata": dashboard.json_metadata,
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"position_json": dashboard.position_json,
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"published": dashboard.published,
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"slices": []
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}
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}
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],
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"charts": [],
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"datasets": []
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}
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# Добавляем чарты
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for slice_obj in dashboard.slices:
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chart_data = {
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"__Slice__": {
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"slice_name": slice_obj.slice_name,
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"viz_type": slice_obj.viz_type,
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"params": slice_obj.params,
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"description": slice_obj.description,
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"datasource_type": slice_obj.datasource_type,
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"datasource_name": slice_obj.datasource.name if slice_obj.datasource else None
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}
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}
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dashboard_data["dashboards"][0]["__Dashboard__"]["slices"].append(slice_obj.id)
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dashboard_data["charts"].append(chart_data)
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# Добавляем датасет
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if slice_obj.datasource:
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ds = slice_obj.datasource
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dataset_data = {
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"__SqlaTable__": {
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"table_name": ds.table_name,
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"schema": ds.schema,
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"database": ds.database.database_name if ds.database else None,
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"description": ds.description,
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"columns": [
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{
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"column_name": col.column_name,
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"type": col.type,
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"description": col.description
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}
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for col in ds.columns
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]
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}
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}
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# Добавляем уникальные датасеты
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if dataset_data not in dashboard_data["datasets"]:
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dashboard_data["datasets"].append(dataset_data)
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# Сохраняем в файл
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with open(output_path, 'w', encoding='utf-8') as f:
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json.dump(dashboard_data, f, indent=2, ensure_ascii=False)
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print(f"Dashboard exported to: {output_path}")
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return True
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if __name__ == "__main__":
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output_file = "/app/superset_init/dashboards/ecommerce_analytics.json"
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export_dashboard("ecommerce-analytics", output_file)
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