feat: migrate examples from Python to YAML format with enhanced CLI

Migrates Superset's example data system from Python-based scripts to YAML configuration files, providing a cleaner, more maintainable approach to managing example datasets, charts, and dashboards.

- Converted 9 Python example modules to YAML configurations
- Exported existing examples from database and added as YAML files:
  - 11 dashboards (USA Births Names, World Bank's Data, etc.)
  - 115 charts
  - 25 datasets
- Moved test-specific fixtures to `tests/fixtures/examples/`
- Removed theme_id from dashboard exports for compatibility

- **New command group**: `superset examples` with subcommands:
  - `load` - Load example data (replaces `load-examples`)
  - `clear-old` - Remove old Python-based examples
  - `clear` - Placeholder for future YAML clearing
  - `reload` - Clear and reload in one command
- **Backwards compatibility**: `superset load-examples` still works with deprecation warning
- **Safety mechanism**: Detects old examples and preserves them to avoid data loss

- Fixed JSON data loading - examples can now load `.json.gz` files from CDN
- Fixed Docker compose configuration for isolated development
- Fixed webpack WebSocket configuration for different ports

- Import operations now log what's being created vs updated:
  - "Creating new dashboard: Sales Dashboard"
  - "Updating existing chart: World's Population"
- Provides clear visibility into the import process

- Moved import logging to individual import functions (DRY principle)
- Non-destructive migration approach - no user data is deleted
- Deterministic UUID generation for consistent example data

- Tested migration from old Python examples to new YAML format
- Verified safety mechanism prevents accidental data overwrites
- Confirmed backwards compatibility with deprecated command
- All pre-commit checks pass

- Updated installation docs to use new CLI commands
- Added deprecation notice to UPDATING.md
- Updated development documentation

None - the old `load-examples` command continues to work with a deprecation warning.

For users with existing Python-based examples:
1. Run `superset examples clear-old --confirm` to remove old examples
2. Run `superset examples load` to load new YAML-based examples

tests/fixtures/examples/big_data.py

@@ -0,0 +1,78 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+import logging
+import random
+import string
+
+import sqlalchemy.sql.sqltypes
+
+from superset.utils.mock_data import add_data, ColumnInfo
+
+logger = logging.getLogger(__name__)
+
+COLUMN_TYPES = [
+    sqlalchemy.sql.sqltypes.INTEGER(),
+    sqlalchemy.sql.sqltypes.VARCHAR(length=255),
+    sqlalchemy.sql.sqltypes.TEXT(),
+    sqlalchemy.sql.sqltypes.BOOLEAN(),
+    sqlalchemy.sql.sqltypes.FLOAT(),
+    sqlalchemy.sql.sqltypes.DATE(),
+    sqlalchemy.sql.sqltypes.TIME(),
+    sqlalchemy.sql.sqltypes.TIMESTAMP(),
+]
+
+
+def load_big_data() -> None:
+    logger.debug("Creating table `wide_table` with 100 columns")
+    columns: list[ColumnInfo] = []
+    for i in range(100):
+        column: ColumnInfo = {
+            "name": f"col{i}",
+            "type": COLUMN_TYPES[i % len(COLUMN_TYPES)],
+            "nullable": False,
+            "default": None,
+            "autoincrement": "auto",
+            "primary_key": 1 if i == 0 else 0,
+        }
+        columns.append(column)
+    add_data(columns=columns, num_rows=1000, table_name="wide_table")
+
+    logger.debug("Creating 1000 small tables")
+    columns = [
+        {
+            "name": "id",
+            "type": sqlalchemy.sql.sqltypes.INTEGER(),
+            "nullable": False,
+            "default": None,
+            "autoincrement": "auto",
+            "primary_key": 1,
+        },
+        {
+            "name": "value",
+            "type": sqlalchemy.sql.sqltypes.VARCHAR(length=255),
+            "nullable": False,
+            "default": None,
+            "autoincrement": "auto",
+            "primary_key": 0,
+        },
+    ]
+    for i in range(1000):
+        add_data(columns=columns, num_rows=10, table_name=f"small_table_{i}")
+
+    logger.debug("Creating table with long name")
+    name = "".join(random.choices(string.ascii_letters + string.digits, k=60))  # noqa: S311
+    add_data(columns=columns, num_rows=10, table_name=name)