fix(superset): заменена нечитаемая гео-карта

- Зачем:
  - гео-блок дашборда должен показывать понятную метрику, единицы и сравнение стран.
- Что:
  - legacy world_map заменён на столбцы Top Countries by Events с tooltip и легендой.
  - синхронизирован экспорт дашборда и добавлены контрактные тесты.
  - обновлены документы и урок Superset по новому гео-блоку.
- Проверка:
  - uv run --with pytest pytest tests/test_superset_dashboard_config.py.
  - uv run python -m py_compile superset/create_dashboard.py tests/test_superset_dashboard_config.py.
  - jq empty superset/dashboards/ecommerce_analytics.zip.json.

docs/SUPERSET_DASHBOARD.md

@@ -67,7 +67,18 @@ KPI разложены в одну строку по 12-колоночной с
 - **📱 Traffic by Device** — pie chart распределения по устройствам
 
 #### География
-- **🌍 Geography Map** — world map с распределением по странам
+- **🌍 Top Countries by Events** — top-15 стран по количеству событий
+  (`COUNT(*)`, единицы — события, штуки). Столбцы заменили legacy world map:
+  на текущем разреженном распределении так видны страна, значение, порядок и
+  tooltip. Перекос стран приходит из гео-фактуры статического сида
+  `geo_by_click_id`; своя генерация гео описана как отдельный будущий шаг в
+  ADR-0006 и не лечится настройкой чарта.
+
+> **Что проверили по Superset.** Через MCP Context7 проверили `/apache/superset`:
+> legacy world map описан как отдельный legacy-плагин, а ECharts bar chart имеет
+> штатные параметры `show_legend`, `rich_tooltip`, подписи осей и формат чисел.
+> Поэтому для разреженной географии выбран top-N bar chart
+> (`viz_type: echarts_timeseries_bar`), а не донастройка `world_map`.
 
 #### Маркетинг
 - **🔗 UTM Effectiveness Table** — таблица эффективности UTM-меток

docs/course/lessons/06_superset_bi.md

@@ -119,7 +119,7 @@ http://localhost:8088/superset/dashboard/ecommerce-analytics/
 - KPI сверху: `Total Events`, `Unique Users`, `Avg Events/Visit`,
   `Conversion to /confirmation`;
 - динамика: `Events over Time`, `Traffic by Device`;
-- география: `Geography Map`;
+- география: `Top Countries by Events`;
 - маркетинг: `UTM Effectiveness Table`, `Page Funnel`;
 - прохождение строк по слоям: `Rows by Layer (event)`.
 

superset/create_dashboard.py

@@ -147,18 +147,40 @@ CHARTS_CONFIG = [
     },
     # География
     {
-        "slice_name": "🌍 Geography Map",
+        "slice_name": "🌍 Top Countries by Events",
-        "viz_type": "world_map",
+        "previous_slice_names": ["🌍 Geography Map"],
+        # Legacy world_map показывает разреженную географию плохо: нет явной
+        # легенды, подписи единиц и стабильного tooltip. Для текущего сида
+        # читаемее top-N стран столбцами: сразу видны страна, значение и порядок.
+        # Перекос стран — свойство geo-фактуры из сида, а не настройка чарта.
+        "viz_type": "echarts_timeseries_bar",
         "dataset_name": "v_events_enriched",
         "params": {
-            "entity": "geo_country",
+            "x_axis": "geo_country",
-            "metric": {
+            "metrics": [
+                {
                     "expressionType": "SQL",
                     "sqlExpression": "COUNT(*)",
-                "label": "Events"
+                    "label": "Events, pcs",
-            },
+                }
-            "row_limit": 500,
+            ],
-            "linear_color_scheme": "blue_white_yellow",
+            "row_limit": 15,
+            "order_desc": True,
+            "sort_series_type": "sum",
+            "orientation": "vertical",
+            "color_scheme": "supersetColors",
+            "show_legend": True,
+            "legendOrientation": "top",
+            "legendType": "scroll",
+            "rich_tooltip": True,
+            "tooltipTimeFormat": "smart_date",
+            "x_axis_title": "Country",
+            "x_axis_title_margin": 15,
+            "truncateXAxis": True,
+            "y_axis_title": "Events, pcs",
+            "y_axis_title_margin": 15,
+            "y_axis_title_position": "Left",
+            "y_axis_format": ",d",
             "time_range": "No filter"
         }
     },
@@ -290,7 +312,7 @@ DASHBOARD_ROWS = [
     # Динамика во времени + разрез по устройствам
     [("📅 Events over Time", 8), ("📱 Traffic by Device", 4)],
     # География + эффективность маркетинговых каналов
-    [("🌍 Geography Map", 6), ("🔗 UTM Effectiveness Table", 6)],
+    [("🌍 Top Countries by Events", 6), ("🔗 UTM Effectiveness Table", 6)],
     # Популярные страницы + прохождение строк по слоям
     [("🪜 Page Funnel", 6), ("🧱 Rows by Layer (event)", 6)],
 ]
@@ -360,6 +382,19 @@ def sync_query_context(chart, params: dict, dataset_id: int) -> None:
     chart.query_context = json.dumps(query_context)
 
 
+def choose_chart_to_sync(existing_charts: list, current_name: str):
+    """Выбирает один chart для синхронизации и отдаёт лишние дубли на удаление."""
+    if not existing_charts:
+        return None, []
+
+    selected = next(
+        (chart for chart in existing_charts if chart.slice_name == current_name),
+        existing_charts[0],
+    )
+    duplicates = [chart for chart in existing_charts if chart is not selected]
+    return selected, duplicates
+
+
 def build_dashboard_metadata(filter_dataset_id: int | None) -> str:
     """Формирует json_metadata с валидными datasetId для native filters."""
     native_filters = []
@@ -467,11 +502,23 @@ def main() -> bool:
                 # идемпотентного rename без дублей в списке Charts.
                 chart_names = [chart_config["slice_name"]]
                 chart_names.extend(chart_config.get("previous_slice_names", []))
-                existing = db.session.query(Slice).filter(
+                existing_charts = db.session.query(Slice).filter(
                     Slice.slice_name.in_(chart_names)
-                ).order_by(Slice.id.asc()).first()
+                ).order_by(Slice.id.asc()).all()
+                existing, duplicate_charts = choose_chart_to_sync(
+                    existing_charts,
+                    chart_config["slice_name"],
+                )
 
                 if existing:
+                    for duplicate in duplicate_charts:
+                        db.session.delete(duplicate)
+                        logger.info(
+                            "Deleted duplicate chart after rename: %s (ID: %s)",
+                            duplicate.slice_name,
+                            duplicate.id,
+                        )
+
                     # Синхронизируем параметры существующего чарта с конфигом.
                     existing.slice_name = chart_config["slice_name"]
                     existing.viz_type = chart_config["viz_type"]

superset/dashboards/ecommerce_analytics.zip.json

@@ -3,12 +3,23 @@
     {
       "__Dashboard__": {
         "dashboard_title": "🛒 E-commerce Analytics Dashboard",
-        "description": "Аналитический дашборд для e-commerce кликстрима: трафик, конверсии, география и качество данных.",
+        "description": "Аналитический дашборд для e-commerce кликстрима: трафик, конверсии, география и прохождение строк по слоям.",
         "slug": "ecommerce-analytics",
         "published": true,
         "json_metadata": "{\"native_filter_configuration\": [{\"id\": \"date_filter\", \"name\": \"📅 Date Range\", \"filterType\": \"filter_time\", \"targets\": [{\"datasetId\": null, \"column\": {\"name\": \"event_date\"}}], \"defaultValue\": \"Last week\", \"scope\": {\"root\": [\"ROOT_ID\"], \"excluded\": []}, \"cascadeParentIds\": [], \"isInstant\": true}, {\"id\": \"country_filter\", \"name\": \"🌍 Country\", \"filterType\": \"filter_select\", \"targets\": [{\"datasetId\": null, \"column\": {\"name\": \"geo_country\"}}], \"scope\": {\"root\": [\"ROOT_ID\"], \"excluded\": []}, \"isInstant\": true, \"allowsMultipleValues\": true, \"isRequired\": false}, {\"id\": \"device_filter\", \"name\": \"📱 Device Type\", \"filterType\": \"filter_select\", \"targets\": [{\"datasetId\": null, \"column\": {\"name\": \"device_type\"}}], \"scope\": {\"root\": [\"ROOT_ID\"], \"excluded\": []}, \"isInstant\": true, \"allowsMultipleValues\": true, \"isRequired\": false}, {\"id\": \"browser_filter\", \"name\": \"🌐 Browser\", \"filterType\": \"filter_select\", \"targets\": [{\"datasetId\": null, \"column\": {\"name\": \"browser_name\"}}], \"scope\": {\"root\": [\"ROOT_ID\"], \"excluded\": []}, \"isInstant\": true, \"allowsMultipleValues\": true, \"isRequired\": false}], \"color_scheme\": \"supersetColors\", \"label_colors\": {}}",
-        "position_json": "{\"DASHBOARD_VERSION_KEY\": \"v2\", \"CHART-1\": {\"id\": \"CHART-1\", \"type\": \"CHART\", \"parents\": [\"ROOT_ID\"], \"meta\": {\"chartId\": 1, \"sliceName\": \"📊 Total Events\", \"height\": 50, \"width\": 4, \"x\": 0, \"y\": 0}}, \"CHART-2\": {\"id\": \"CHART-2\", \"type\": \"CHART\", \"parents\": [\"ROOT_ID\"], \"meta\": {\"chartId\": 2, \"sliceName\": \"👤 Unique Users\", \"height\": 50, \"width\": 4, \"x\": 4, \"y\": 0}}, \"CHART-3\": {\"id\": \"CHART-3\", \"type\": \"CHART\", \"parents\": [\"ROOT_ID\"], \"meta\": {\"chartId\": 3, \"sliceName\": \"🎯 Unique Sessions\", \"height\": 50, \"width\": 4, \"x\": 8, \"y\": 0}}, \"CHART-4\": {\"id\": \"CHART-4\", \"type\": \"CHART\", \"parents\": [\"ROOT_ID\"], \"meta\": {\"chartId\": 4, \"sliceName\": \"📈 Avg Events/Session\", \"height\": 50, \"width\": 4, \"x\": 0, \"y\": 50}}, \"CHART-5\": {\"id\": \"CHART-5\", \"type\": \"CHART\", \"parents\": [\"ROOT_ID\"], \"meta\": {\"chartId\": 5, \"sliceName\": \"📅 Events by Hour\", \"height\": 50, \"width\": 8, \"x\": 0, \"y\": 100}}, \"CHART-6\": {\"id\": \"CHART-6\", \"type\": \"CHART\", \"parents\": [\"ROOT_ID\"], \"meta\": {\"chartId\": 6, \"sliceName\": \"📱 Traffic by Device\", \"height\": 50, \"width\": 4, \"x\": 8, \"y\": 100}}, \"CHART-7\": {\"id\": \"CHART-7\", \"type\": \"CHART\", \"parents\": [\"ROOT_ID\"], \"meta\": {\"chartId\": 7, \"sliceName\": \"🌍 Geography Map\", \"height\": 50, \"width\": 6, \"x\": 0, \"y\": 150}}, \"CHART-8\": {\"id\": \"CHART-8\", \"type\": \"CHART\", \"parents\": [\"ROOT_ID\"], \"meta\": {\"chartId\": 8, \"sliceName\": \"🔗 UTM Effectiveness Table\", \"height\": 50, \"width\": 6, \"x\": 6, \"y\": 150}}, \"CHART-9\": {\"id\": \"CHART-9\", \"type\": \"CHART\", \"parents\": [\"ROOT_ID\"], \"meta\": {\"chartId\": 9, \"sliceName\": \"📄 Top Pages\", \"height\": 50, \"width\": 6, \"x\": 0, \"y\": 200}}, \"CHART-10\": {\"id\": \"CHART-10\", \"type\": \"CHART\", \"parents\": [\"ROOT_ID\"], \"meta\": {\"chartId\": 10, \"sliceName\": \"🔍 Data Quality Summary\", \"height\": 50, \"width\": 6, \"x\": 6, \"y\": 200}}}",
+        "position_json": "{\"DASHBOARD_VERSION_KEY\": \"v2\", \"ROOT_ID\": {\"id\": \"ROOT_ID\", \"type\": \"ROOT\", \"children\": [\"GRID_ID\"]}, \"GRID_ID\": {\"id\": \"GRID_ID\", \"type\": \"GRID\", \"children\": [\"ROW-0\", \"ROW-1\", \"ROW-2\", \"ROW-3\"], \"parents\": [\"ROOT_ID\"], \"meta\": {\"background\": \"BACKGROUND_TRANSPARENT\"}}, \"CHART-1\": {\"id\": \"CHART-1\", \"type\": \"CHART\", \"children\": [], \"parents\": [\"ROOT_ID\", \"GRID_ID\", \"ROW-0\"], \"meta\": {\"chartId\": 1, \"sliceName\": \"📊 Total Events\", \"width\": 3, \"height\": 30}}, \"CHART-2\": {\"id\": \"CHART-2\", \"type\": \"CHART\", \"children\": [], \"parents\": [\"ROOT_ID\", \"GRID_ID\", \"ROW-0\"], \"meta\": {\"chartId\": 2, \"sliceName\": \"👤 Unique Users\", \"width\": 3, \"height\": 30}}, \"CHART-3\": {\"id\": \"CHART-3\", \"type\": \"CHART\", \"children\": [], \"parents\": [\"ROOT_ID\", \"GRID_ID\", \"ROW-0\"], \"meta\": {\"chartId\": 3, \"sliceName\": \"📈 Avg Events/Visit\", \"width\": 3, \"height\": 30}}, \"CHART-4\": {\"id\": \"CHART-4\", \"type\": \"CHART\", \"children\": [], \"parents\": [\"ROOT_ID\", \"GRID_ID\", \"ROW-0\"], \"meta\": {\"chartId\": 4, \"sliceName\": \"🎯 Conversion to /confirmation\", \"width\": 3, \"height\": 30}}, \"ROW-0\": {\"id\": \"ROW-0\", \"type\": \"ROW\", \"children\": [\"CHART-1\", \"CHART-2\", \"CHART-3\", \"CHART-4\"], \"parents\": [\"ROOT_ID\", \"GRID_ID\"], \"meta\": {\"background\": \"BACKGROUND_TRANSPARENT\"}}, \"CHART-5\": {\"id\": \"CHART-5\", \"type\": \"CHART\", \"children\": [], \"parents\": [\"ROOT_ID\", \"GRID_ID\", \"ROW-1\"], \"meta\": {\"chartId\": 5, \"sliceName\": \"📅 Events over Time\", \"width\": 8, \"height\": 60}}, \"CHART-6\": {\"id\": \"CHART-6\", \"type\": \"CHART\", \"children\": [], \"parents\": [\"ROOT_ID\", \"GRID_ID\", \"ROW-1\"], \"meta\": {\"chartId\": 6, \"sliceName\": \"📱 Traffic by Device\", \"width\": 4, \"height\": 60}}, \"ROW-1\": {\"id\": \"ROW-1\", \"type\": \"ROW\", \"children\": [\"CHART-5\", \"CHART-6\"], \"parents\": [\"ROOT_ID\", \"GRID_ID\"], \"meta\": {\"background\": \"BACKGROUND_TRANSPARENT\"}}, \"CHART-7\": {\"id\": \"CHART-7\", \"type\": \"CHART\", \"children\": [], \"parents\": [\"ROOT_ID\", \"GRID_ID\", \"ROW-2\"], \"meta\": {\"chartId\": 7, \"sliceName\": \"🌍 Top Countries by Events\", \"width\": 6, \"height\": 60}}, \"CHART-8\": {\"id\": \"CHART-8\", \"type\": \"CHART\", \"children\": [], \"parents\": [\"ROOT_ID\", \"GRID_ID\", \"ROW-2\"], \"meta\": {\"chartId\": 8, \"sliceName\": \"🔗 UTM Effectiveness Table\", \"width\": 6, \"height\": 60}}, \"ROW-2\": {\"id\": \"ROW-2\", \"type\": \"ROW\", \"children\": [\"CHART-7\", \"CHART-8\"], \"parents\": [\"ROOT_ID\", \"GRID_ID\"], \"meta\": {\"background\": \"BACKGROUND_TRANSPARENT\"}}, \"CHART-9\": {\"id\": \"CHART-9\", \"type\": \"CHART\", \"children\": [], \"parents\": [\"ROOT_ID\", \"GRID_ID\", \"ROW-3\"], \"meta\": {\"chartId\": 9, \"sliceName\": \"🪜 Page Funnel\", \"width\": 6, \"height\": 60}}, \"CHART-10\": {\"id\": \"CHART-10\", \"type\": \"CHART\", \"children\": [], \"parents\": [\"ROOT_ID\", \"GRID_ID\", \"ROW-3\"], \"meta\": {\"chartId\": 10, \"sliceName\": \"🧱 Rows by Layer (event)\", \"width\": 6, \"height\": 60}}, \"ROW-3\": {\"id\": \"ROW-3\", \"type\": \"ROW\", \"children\": [\"CHART-9\", \"CHART-10\"], \"parents\": [\"ROOT_ID\", \"GRID_ID\"], \"meta\": {\"background\": \"BACKGROUND_TRANSPARENT\"}}}",
-        "slices": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
+        "slices": [
+          1,
+          2,
+          3,
+          4,
+          5,
+          6,
+          7,
+          8,
+          9,
+          10
+        ]
       }
     }
   ],
@@ -16,51 +27,51 @@
     {
       "__Slice__": {
         "slice_name": "📊 Total Events",
-        "viz_type": "big_number",
+        "viz_type": "big_number_total",
         "datasource_type": "table",
         "datasource_name": "dm.v_events_enriched",
-        "params": "{\"datasource\": \"1__table\", \"viz_type\": \"big_number\", \"metric\": {\"expressionType\": \"SQL\", \"sqlExpression\": \"COUNT(*)\", \"column\": null, \"aggregate\": null, \"label\": \"Total Events\", \"optionName\": \"metric_1\"}, \"y_axis_format\": \",d\", \"show_trend_line\": false, \"time_range\": \"No filter\"}",
+        "params": "{\"metric\": {\"expressionType\": \"SQL\", \"sqlExpression\": \"COUNT(*)\", \"column\": null, \"aggregate\": null, \"label\": \"Total Events\", \"optionName\": \"metric_1\"}, \"y_axis_format\": \",d\", \"time_range\": \"No filter\", \"datasource\": \"1__table\", \"viz_type\": \"big_number_total\"}",
-        "description": "Общее количество событий"
+        "description": "Chart created automatically for v_events_enriched"
       }
     },
     {
       "__Slice__": {
         "slice_name": "👤 Unique Users",
-        "viz_type": "big_number",
+        "viz_type": "big_number_total",
         "datasource_type": "table",
         "datasource_name": "dm.v_events_enriched",
-        "params": "{\"datasource\": \"1__table\", \"viz_type\": \"big_number\", \"metric\": {\"expressionType\": \"SQL\", \"sqlExpression\": \"COUNT(DISTINCT user_domain_id)\", \"label\": \"Unique Users\", \"optionName\": \"metric_2\"}, \"y_axis_format\": \",d\", \"show_trend_line\": false, \"time_range\": \"No filter\"}",
+        "params": "{\"metric\": {\"expressionType\": \"SQL\", \"sqlExpression\": \"COUNT(DISTINCT user_domain_id)\", \"label\": \"Unique Users\", \"optionName\": \"metric_2\"}, \"y_axis_format\": \",d\", \"time_range\": \"No filter\", \"datasource\": \"1__table\", \"viz_type\": \"big_number_total\"}",
-        "description": "Уникальные пользователи"
+        "description": "Chart created automatically for v_events_enriched"
       }
     },
     {
       "__Slice__": {
-        "slice_name": "🎯 Unique Sessions",
+        "slice_name": "📈 Avg Events/Visit",
-        "viz_type": "big_number",
+        "viz_type": "big_number_total",
         "datasource_type": "table",
         "datasource_name": "dm.v_events_enriched",
-        "params": "{\"datasource\": \"1__table\", \"viz_type\": \"big_number\", \"metric\": {\"expressionType\": \"SQL\", \"sqlExpression\": \"COUNT(DISTINCT click_id)\", \"label\": \"Unique Sessions\", \"optionName\": \"metric_3\"}, \"y_axis_format\": \",d\", \"show_trend_line\": false, \"time_range\": \"No filter\"}",
+        "params": "{\"metric\": {\"expressionType\": \"SQL\", \"sqlExpression\": \"COUNT(*) / COUNT(DISTINCT click_id)\", \"label\": \"Avg Events/Visit\", \"optionName\": \"metric_4\"}, \"y_axis_format\": \".1f\", \"time_range\": \"No filter\", \"datasource\": \"1__table\", \"viz_type\": \"big_number_total\"}",
-        "description": "Уникальные сессии"
+        "description": "Chart created automatically for v_events_enriched"
       }
     },
     {
       "__Slice__": {
-        "slice_name": "📈 Avg Events/Session",
+        "slice_name": "🎯 Conversion to /confirmation",
-        "viz_type": "big_number",
+        "viz_type": "big_number_total",
         "datasource_type": "table",
         "datasource_name": "dm.v_events_enriched",
-        "params": "{\"datasource\": \"1__table\", \"viz_type\": \"big_number\", \"metric\": {\"expressionType\": \"SQL\", \"sqlExpression\": \"COUNT(*) / COUNT(DISTINCT click_id)\", \"label\": \"Avg Events/Session\", \"optionName\": \"metric_4\"}, \"y_axis_format\": \".2f\", \"show_trend_line\": false, \"time_range\": \"No filter\"}",
+        "params": "{\"metric\": {\"expressionType\": \"SQL\", \"sqlExpression\": \"if(countIf(page_url_path = '/home') = 0, 0, countIf(page_url_path = '/confirmation') / countIf(page_url_path = '/home'))\", \"label\": \"Conversion to /confirmation\", \"optionName\": \"metric_5\"}, \"y_axis_format\": \".1%\", \"time_range\": \"No filter\", \"datasource\": \"1__table\", \"viz_type\": \"big_number_total\"}",
-        "description": "Среднее количество событий на сессию"
+        "description": "Chart created automatically for v_events_enriched"
       }
     },
     {
       "__Slice__": {
-        "slice_name": "📅 Events by Hour",
+        "slice_name": "📅 Events over Time",
         "viz_type": "echarts_timeseries_line",
         "datasource_type": "table",
         "datasource_name": "dm.v_events_enriched",
-        "params": "{\"datasource\": \"1__table\", \"viz_type\": \"echarts_timeseries_line\", \"granularity_sqla\": \"event_ts\", \"time_grain_sqla\": \"PT1H\", \"metrics\": [{\"expressionType\": \"SQL\", \"sqlExpression\": \"COUNT(*)\", \"label\": \"Events\"}], \"groupby\": [], \"time_range\": \"Last week\", \"adhoc_filters\": [], \"row_limit\": 10000}",
+        "params": "{\"granularity_sqla\": \"event_ts\", \"time_grain_sqla\": \"PT5M\", \"metrics\": [{\"expressionType\": \"SQL\", \"sqlExpression\": \"COUNT(*)\", \"label\": \"Events\"}], \"groupby\": [], \"time_range\": \"No filter\", \"adhoc_filters\": [], \"row_limit\": 10000, \"datasource\": \"1__table\", \"viz_type\": \"echarts_timeseries_line\"}",
-        "description": "События по часам"
+        "description": "Chart created automatically for v_events_enriched"
       }
     },
     {
@@ -69,18 +80,18 @@
         "viz_type": "pie",
         "datasource_type": "table",
         "datasource_name": "dm.v_events_enriched",
-        "params": "{\"datasource\": \"1__table\", \"viz_type\": \"pie\", \"groupby\": [\"device_type\"], \"metric\": {\"expressionType\": \"SQL\", \"sqlExpression\": \"COUNT(*)\", \"label\": \"Count\"}, \"row_limit\": 100, \"donut\": true, \"show_legend\": true, \"labels_outside\": true, \"time_range\": \"No filter\"}",
+        "params": "{\"groupby\": [\"device_type\"], \"metric\": {\"expressionType\": \"SQL\", \"sqlExpression\": \"COUNT(*)\", \"label\": \"Count\"}, \"row_limit\": 100, \"donut\": true, \"show_legend\": true, \"labels_outside\": true, \"time_range\": \"No filter\", \"datasource\": \"1__table\", \"viz_type\": \"pie\"}",
-        "description": "Распределение трафика по устройствам"
+        "description": "Chart created automatically for v_events_enriched"
       }
     },
     {
       "__Slice__": {
-        "slice_name": "🌍 Geography Map",
+        "slice_name": "🌍 Top Countries by Events",
-        "viz_type": "world_map",
+        "viz_type": "echarts_timeseries_bar",
         "datasource_type": "table",
         "datasource_name": "dm.v_events_enriched",
-        "params": "{\"datasource\": \"1__table\", \"viz_type\": \"world_map\", \"entity\": \"geo_country\", \"metric\": {\"expressionType\": \"SQL\", \"sqlExpression\": \"COUNT(*)\", \"label\": \"Events\"}, \"row_limit\": 500, \"linear_color_scheme\": \"blue_white_yellow\", \"time_range\": \"No filter\"}",
+        "params": "{\"x_axis\": \"geo_country\", \"metrics\": [{\"expressionType\": \"SQL\", \"sqlExpression\": \"COUNT(*)\", \"label\": \"Events, pcs\"}], \"row_limit\": 15, \"order_desc\": true, \"sort_series_type\": \"sum\", \"orientation\": \"vertical\", \"color_scheme\": \"supersetColors\", \"show_legend\": true, \"legendOrientation\": \"top\", \"legendType\": \"scroll\", \"rich_tooltip\": true, \"tooltipTimeFormat\": \"smart_date\", \"x_axis_title\": \"Country\", \"x_axis_title_margin\": 15, \"truncateXAxis\": true, \"y_axis_title\": \"Events, pcs\", \"y_axis_title_margin\": 15, \"y_axis_title_position\": \"Left\", \"y_axis_format\": \",d\", \"time_range\": \"No filter\", \"datasource\": \"1__table\", \"viz_type\": \"echarts_timeseries_bar\"}",
-        "description": "География посетителей"
+        "description": "Chart created automatically for v_events_enriched"
       }
     },
     {
@@ -89,28 +100,28 @@
         "viz_type": "table",
         "datasource_type": "table",
         "datasource_name": "dm.v_utm_effectiveness",
-        "params": "{\"datasource\": \"2__table\", \"viz_type\": \"table\", \"groupby\": [\"utm_source\", \"utm_medium\", \"utm_campaign\"], \"metrics\": [{\"expressionType\": \"SQL\", \"sqlExpression\": \"SUM(clicks)\", \"label\": \"Clicks\"}, {\"expressionType\": \"SQL\", \"sqlExpression\": \"SUM(uniq_users)\", \"label\": \"Users\"}, {\"expressionType\": \"SQL\", \"sqlExpression\": \"SUM(uniq_sessions)\", \"label\": \"Sessions\"}], \"row_limit\": 100, \"time_range\": \"No filter\", \"adhoc_filters\": [{\"clause\": \"WHERE\", \"expressionType\": \"SQL\", \"sqlExpression\": \"utm_source IS NOT NULL\", \"subject\": null, \"operator\": null, \"comparator\": null}]}\n",
+        "params": "{\"groupby\": [\"utm_source\", \"utm_medium\", \"utm_campaign\"], \"metrics\": [{\"expressionType\": \"SQL\", \"sqlExpression\": \"SUM(clicks)\", \"label\": \"Clicks\"}, {\"expressionType\": \"SQL\", \"sqlExpression\": \"SUM(uniq_users)\", \"label\": \"Users\"}, {\"expressionType\": \"SQL\", \"sqlExpression\": \"SUM(uniq_sessions)\", \"label\": \"Sessions\"}], \"row_limit\": 100, \"time_range\": \"No filter\", \"adhoc_filters\": [{\"clause\": \"WHERE\", \"expressionType\": \"SQL\", \"sqlExpression\": \"utm_source IS NOT NULL\", \"subject\": null, \"operator\": null, \"comparator\": null}], \"datasource\": \"2__table\", \"viz_type\": \"table\"}",
-        "description": "Эффективность UTM-кампаний"
+        "description": "Chart created automatically for v_utm_effectiveness"
       }
     },
     {
       "__Slice__": {
-        "slice_name": "📄 Top Pages",
+        "slice_name": "🪜 Page Funnel",
-        "viz_type": "dist_bar",
+        "viz_type": "funnel",
         "datasource_type": "table",
         "datasource_name": "dm.v_top_pages_daily",
-        "params": "{\"datasource\": \"3__table\", \"viz_type\": \"dist_bar\", \"groupby\": [\"page_url_path\"], \"metrics\": [{\"expressionType\": \"SQL\", \"sqlExpression\": \"SUM(pageviews)\", \"label\": \"Pageviews\"}], \"row_limit\": 20, \"order_by_cols\": [[\"SUM(pageviews)\", false]], \"time_range\": \"No filter\", \"orientation\": \"vertical\", \"show_legend\": false}",
+        "params": "{\"groupby\": [\"page_url_path\"], \"metric\": {\"expressionType\": \"SQL\", \"sqlExpression\": \"SUM(pageviews)\", \"label\": \"Pageviews\"}, \"row_limit\": 20, \"time_range\": \"No filter\", \"sort_by_metric\": true, \"percent_calculation_type\": \"first_step\", \"color_scheme\": \"supersetColors\", \"show_legend\": true, \"legendOrientation\": \"top\", \"legendMargin\": 50, \"tooltip_label_type\": 5, \"number_format\": \"SMART_NUMBER\", \"show_labels\": true, \"show_tooltip_labels\": true, \"datasource\": \"3__table\", \"viz_type\": \"funnel\"}",
-        "description": "Топ страниц по просмотрам"
+        "description": "Chart created automatically for v_top_pages_daily"
       }
     },
     {
       "__Slice__": {
-        "slice_name": "🔍 Data Quality Summary",
+        "slice_name": "🧱 Rows by Layer (event)",
         "viz_type": "dist_bar",
         "datasource_type": "table",
         "datasource_name": "dm.dq_summary",
-        "params": "{\"datasource\": \"4__table\", \"viz_type\": \"dist_bar\", \"groupby\": [\"layer\"], \"metrics\": [{\"expressionType\": \"SQL\", \"sqlExpression\": \"SUM(check_value)\", \"label\": \"Row Count\"}], \"adhoc_filters\": [{\"clause\": \"WHERE\", \"expressionType\": \"SQL\", \"sqlExpression\": \"check_name = 'total_rows'\", \"subject\": null, \"operator\": null, \"comparator\": null}], \"row_limit\": 100, \"time_range\": \"No filter\", \"show_legend\": false}",
+        "params": "{\"groupby\": [{\"expressionType\": \"SQL\", \"sqlExpression\": \"multiIf(layer = 'stg', '1 · stg', layer = 'ods', '2 · ods', layer = 'dds', '3 · dds', '4 · dm')\", \"label\": \"Layer\"}], \"metrics\": [{\"expressionType\": \"SQL\", \"sqlExpression\": \"SUM(check_value)\", \"label\": \"Rows\"}], \"adhoc_filters\": [{\"clause\": \"WHERE\", \"expressionType\": \"SQL\", \"sqlExpression\": \"check_name = 'total_rows' AND table_name IN ('browser_raw', 'browser_event', 'event', 'v_events_enriched')\", \"subject\": null, \"operator\": null, \"comparator\": null}], \"order_bars\": true, \"row_limit\": 100, \"time_range\": \"No filter\", \"y_axis_format\": \",d\", \"show_legend\": false, \"datasource\": \"4__table\", \"viz_type\": \"dist_bar\"}",
-        "description": "Сводка по качеству данных"
+        "description": "Chart created automatically for dq_summary"
       }
     }
   ],
@@ -122,18 +133,66 @@
         "database": "clickhouse_dwh",
         "description": "Полная обогащённая витрина событий (event + click)",
         "columns": [
-          {"column_name": "event_id", "type": "UUID", "description": "UUID события"},
+          {
-          {"column_name": "event_ts", "type": "DateTime64(6)", "description": "Время события"},
+            "column_name": "event_id",
-          {"column_name": "event_date", "type": "Date", "description": "Дата события"},
+            "type": "UUID",
-          {"column_name": "event_type", "type": "String", "description": "Тип события"},
+            "description": "UUID события"
-          {"column_name": "click_id", "type": "UUID", "description": "ID сессии"},
+          },
-          {"column_name": "user_domain_id", "type": "UUID", "description": "ID пользователя"},
+          {
-          {"column_name": "device_type", "type": "String", "description": "Тип устройства"},
+            "column_name": "event_ts",
-          {"column_name": "geo_country", "type": "String", "description": "Страна"},
+            "type": "DateTime64(6)",
-          {"column_name": "browser_name", "type": "String", "description": "Браузер"},
+            "description": "Время события"
-          {"column_name": "utm_source", "type": "String", "description": "UTM Source"},
+          },
-          {"column_name": "utm_medium", "type": "String", "description": "UTM Medium"},
+          {
-          {"column_name": "page_url_path", "type": "String", "description": "Путь URL"}
+            "column_name": "event_date",
+            "type": "Date",
+            "description": "Дата события"
+          },
+          {
+            "column_name": "event_type",
+            "type": "String",
+            "description": "Тип события"
+          },
+          {
+            "column_name": "click_id",
+            "type": "UUID",
+            "description": "ID сессии"
+          },
+          {
+            "column_name": "user_domain_id",
+            "type": "UUID",
+            "description": "ID пользователя"
+          },
+          {
+            "column_name": "device_type",
+            "type": "String",
+            "description": "Тип устройства"
+          },
+          {
+            "column_name": "geo_country",
+            "type": "String",
+            "description": "Страна"
+          },
+          {
+            "column_name": "browser_name",
+            "type": "String",
+            "description": "Браузер"
+          },
+          {
+            "column_name": "utm_source",
+            "type": "String",
+            "description": "UTM Source"
+          },
+          {
+            "column_name": "utm_medium",
+            "type": "String",
+            "description": "UTM Medium"
+          },
+          {
+            "column_name": "page_url_path",
+            "type": "String",
+            "description": "Путь URL"
+          }
         ]
       }
     },
@@ -144,13 +203,41 @@
         "database": "clickhouse_dwh",
         "description": "Эффективность UTM-кампаний",
         "columns": [
-          {"column_name": "event_date", "type": "Date", "description": "Дата"},
+          {
-          {"column_name": "utm_source", "type": "String", "description": "UTM Source"},
+            "column_name": "event_date",
-          {"column_name": "utm_medium", "type": "String", "description": "UTM Medium"},
+            "type": "Date",
-          {"column_name": "utm_campaign", "type": "String", "description": "UTM Campaign"},
+            "description": "Дата"
-          {"column_name": "clicks", "type": "UInt64", "description": "Клики"},
+          },
-          {"column_name": "uniq_users", "type": "UInt64", "description": "Уникальные пользователи"},
+          {
-          {"column_name": "uniq_sessions", "type": "UInt64", "description": "Уникальные сессии"}
+            "column_name": "utm_source",
+            "type": "String",
+            "description": "UTM Source"
+          },
+          {
+            "column_name": "utm_medium",
+            "type": "String",
+            "description": "UTM Medium"
+          },
+          {
+            "column_name": "utm_campaign",
+            "type": "String",
+            "description": "UTM Campaign"
+          },
+          {
+            "column_name": "clicks",
+            "type": "UInt64",
+            "description": "Клики"
+          },
+          {
+            "column_name": "uniq_users",
+            "type": "UInt64",
+            "description": "Уникальные пользователи"
+          },
+          {
+            "column_name": "uniq_sessions",
+            "type": "UInt64",
+            "description": "Уникальные сессии"
+          }
         ]
       }
     },
@@ -161,10 +248,26 @@
         "database": "clickhouse_dwh",
         "description": "Популярность страниц по дням",
         "columns": [
-          {"column_name": "event_date", "type": "Date", "description": "Дата"},
+          {
-          {"column_name": "page_url_path", "type": "String", "description": "Путь URL"},
+            "column_name": "event_date",
-          {"column_name": "pageviews", "type": "UInt64", "description": "Просмотры"},
+            "type": "Date",
-          {"column_name": "uniq_clicks", "type": "UInt64", "description": "Уникальные клики"}
+            "description": "Дата"
+          },
+          {
+            "column_name": "page_url_path",
+            "type": "String",
+            "description": "Путь URL"
+          },
+          {
+            "column_name": "pageviews",
+            "type": "UInt64",
+            "description": "Просмотры"
+          },
+          {
+            "column_name": "uniq_clicks",
+            "type": "UInt64",
+            "description": "Уникальные клики"
+          }
         ]
       }
     },
@@ -175,11 +278,31 @@
         "database": "clickhouse_dwh",
         "description": "Сводка по качеству данных",
         "columns": [
-          {"column_name": "check_date", "type": "Date", "description": "Дата проверки"},
+          {
-          {"column_name": "layer", "type": "String", "description": "Слой (stg/ods/dds)"},
+            "column_name": "check_date",
-          {"column_name": "table_name", "type": "String", "description": "Имя таблицы"},
+            "type": "Date",
-          {"column_name": "check_name", "type": "String", "description": "Тип проверки"},
+            "description": "Дата проверки"
-          {"column_name": "check_value", "type": "UInt64", "description": "Значение"}
+          },
+          {
+            "column_name": "layer",
+            "type": "String",
+            "description": "Слой (stg/ods/dds)"
+          },
+          {
+            "column_name": "table_name",
+            "type": "String",
+            "description": "Имя таблицы"
+          },
+          {
+            "column_name": "check_name",
+            "type": "String",
+            "description": "Тип проверки"
+          },
+          {
+            "column_name": "check_value",
+            "type": "UInt64",
+            "description": "Значение"
+          }
         ]
       }
     }

tests/test_superset_dashboard_config.py

@@ -0,0 +1,130 @@
+import importlib.util
+import json
+from pathlib import Path
+
+
+def load_dashboard_module():
+    module_path = Path(__file__).resolve().parents[1] / "superset" / "create_dashboard.py"
+    spec = importlib.util.spec_from_file_location("create_dashboard", module_path)
+    module = importlib.util.module_from_spec(spec)
+    spec.loader.exec_module(module)
+    return module
+
+
+def chart_config(module, slice_name):
+    return next(chart for chart in module.CHARTS_CONFIG if chart["slice_name"] == slice_name)
+
+
+def exported_chart(exported_dashboard, slice_name):
+    return next(
+        chart["__Slice__"]
+        for chart in exported_dashboard["charts"]
+        if chart["__Slice__"]["slice_name"] == slice_name
+    )
+
+
+def load_exported_dashboard():
+    export_path = Path(__file__).resolve().parents[1] / "superset" / "dashboards" / "ecommerce_analytics.zip.json"
+    return json.loads(export_path.read_text())
+
+
+class FakeChart:
+    def __init__(self, chart_id, slice_name):
+        self.id = chart_id
+        self.slice_name = slice_name
+
+
+def test_geo_chart_uses_readable_top_countries_bar_config():
+    module = load_dashboard_module()
+
+    geo_chart = chart_config(module, "🌍 Top Countries by Events")
+
+    assert geo_chart["viz_type"] == "echarts_timeseries_bar"
+    assert geo_chart["previous_slice_names"] == ["🌍 Geography Map"]
+
+    params = geo_chart["params"]
+    assert params["x_axis"] == "geo_country"
+    assert params["metrics"] == [
+        {
+            "expressionType": "SQL",
+            "sqlExpression": "COUNT(*)",
+            "label": "Events, pcs",
+        }
+    ]
+    assert params["row_limit"] == 15
+    assert params["order_desc"] is True
+    assert params["sort_series_type"] == "sum"
+    assert params["show_legend"] is True
+    assert params["rich_tooltip"] is True
+    assert params["y_axis_title"] == "Events, pcs"
+    assert params["x_axis_title"] == "Country"
+    assert params["y_axis_format"] == ",d"
+
+
+def test_exported_dashboard_uses_same_readable_geo_chart():
+    exported_dashboard = load_exported_dashboard()
+
+    geo_chart = exported_chart(exported_dashboard, "🌍 Top Countries by Events")
+
+    assert geo_chart["viz_type"] == "echarts_timeseries_bar"
+    params = json.loads(geo_chart["params"])
+    assert params["viz_type"] == "echarts_timeseries_bar"
+    assert params["x_axis"] == "geo_country"
+    assert params["metrics"][0]["label"] == "Events, pcs"
+    assert params["show_legend"] is True
+    assert params["rich_tooltip"] is True
+    assert params["y_axis_title"] == "Events, pcs"
+
+    position_json = json.loads(exported_dashboard["dashboards"][0]["__Dashboard__"]["position_json"])
+    assert position_json["CHART-7"]["meta"]["sliceName"] == "🌍 Top Countries by Events"
+
+
+def test_exported_dashboard_chart_names_match_current_config():
+    module = load_dashboard_module()
+    exported_dashboard = load_exported_dashboard()
+
+    expected_names = [chart["slice_name"] for chart in module.CHARTS_CONFIG]
+    actual_names = [chart["__Slice__"]["slice_name"] for chart in exported_dashboard["charts"]]
+
+    assert actual_names == expected_names
+
+
+def test_exported_dashboard_layout_matches_current_rows():
+    module = load_dashboard_module()
+    exported_dashboard = load_exported_dashboard()
+
+    position_json = json.loads(exported_dashboard["dashboards"][0]["__Dashboard__"]["position_json"])
+    chart_titles_by_id = {
+        component_id: component["meta"]["sliceName"]
+        for component_id, component in position_json.items()
+        if isinstance(component, dict) and component.get("type") == "CHART"
+    }
+
+    actual_rows = []
+    for row_id in position_json["GRID_ID"]["children"]:
+        row = []
+        for chart_component_id in position_json[row_id]["children"]:
+            chart_component = position_json[chart_component_id]
+            row.append(
+                (
+                    chart_titles_by_id[chart_component_id],
+                    chart_component["meta"]["width"],
+                )
+            )
+        actual_rows.append(row)
+
+    assert actual_rows == module.DASHBOARD_ROWS
+
+
+def test_choose_chart_to_sync_prefers_current_name_and_marks_old_name_duplicate():
+    module = load_dashboard_module()
+    old_chart = FakeChart(7, "🌍 Geography Map")
+    current_chart = FakeChart(11, "🌍 Top Countries by Events")
+
+    selected, duplicates = module.choose_chart_to_sync(
+        [old_chart, current_chart],
+        "🌍 Top Countries by Events",
+    )
+
+    assert selected is current_chart
+    assert duplicates == [old_chart]