refactor: streamline HTML rendering documentation

Author: kosiew

docs/source/user-guide/dataframe.rst

@@ -90,94 +90,47 @@ You can customize how DataFrames are rendered in HTML by configuring the formatt
 
 The formatter settings affect all DataFrames displayed after configuration.
 
-Custom Style Providers
-----------------------
+Performance Optimization with Shared Styles
+------------------------------------------
 
-For advanced styling needs, you can create a custom style provider:
+The ``use_shared_styles`` parameter (enabled by default) optimizes performance when displaying 
+multiple DataFrames in notebook environments:
 
 .. code-block:: python
 
-    from datafusion.html_formatter import StyleProvider, configure_formatter
+    # Default: Use shared styles (recommended for notebooks)
+    configure_formatter(use_shared_styles=True)
     
-    class MyStyleProvider(StyleProvider):
-        def get_table_styles(self):
-            return {
-                "table": "border-collapse: collapse; width: 100%;",
-                "th": "background-color: #007bff; color: white; padding: 8px; text-align: left;",
-                "td": "border: 1px solid #ddd; padding: 8px;",
-                "tr:nth-child(even)": "background-color: #f2f2f2;",
-            }
-            
-        def get_value_styles(self, dtype, value):
-            """Return custom styles for specific values"""
-            if dtype == "float" and value < 0:
-                return "color: red;"
-            return None
-    
-    # Apply the custom style provider
-    configure_formatter(style_provider=MyStyleProvider())
-
-Creating a Custom Formatter
----------------------------
-
-For complete control over rendering, you can implement a custom formatter:
-
-.. code-block:: python
-
-    from datafusion.html_formatter import Formatter, get_formatter
-    
-    class MyFormatter(Formatter):
-        def format_html(self, batches, schema, has_more=False, table_uuid=None):
-            # Create your custom HTML here
-            html = "<div class='my-custom-table'>"
-            # ... formatting logic ...
-            html += "</div>"
-            return html
-    
-    # Set as the global formatter
-    configure_formatter(formatter_class=MyFormatter)
-    
-    # Or use the formatter just for specific operations
-    formatter = get_formatter()
-    custom_html = formatter.format_html(batches, schema)
-
-Managing Formatters
--------------------
-
-Reset to default formatting:
+    # Disable shared styles (each DataFrame includes its own styles)
+    configure_formatter(use_shared_styles=False)
 
-.. code-block:: python
+When ``use_shared_styles=True``:
 
-    from datafusion.html_formatter import reset_formatter
-    
-    # Reset to default settings
-    reset_formatter()
+- CSS styles and JavaScript are included only once per notebook session
+- This reduces HTML output size and prevents style duplication
+- Improves rendering performance with many DataFrames
+- Applies consistent styling across all DataFrames
 
-Get the current formatter settings:
+If you switch between notebooks or need to refresh styles:
 
 .. code-block:: python
 
-    from datafusion.html_formatter import get_formatter
+    from datafusion.html_formatter import reset_styles_loaded_state
     
-    formatter = get_formatter()
-    print(formatter.max_rows)
-    print(formatter.theme)
+    # Force styles to be included in the next DataFrame display
+    reset_styles_loaded_state()
 
-Contextual Formatting
----------------------
+Memory and Display Controls
+--------------------------
 
-You can also use a context manager to temporarily change formatting settings:
+You can control how much data is displayed and how much memory is used for rendering:
 
 .. code-block:: python
 
-    from datafusion.html_formatter import formatting_context
-    
-    # Default formatting
-    df.show()
-    
-    # Temporarily use different formatting
-    with formatting_context(max_rows=100, theme="dark"):
-        df.show()  # Will use the temporary settings
-    
-    # Back to default formatting
-    df.show()
+    configure_formatter(
+        max_memory_bytes=4 * 1024 * 1024,  # 4MB maximum memory for display
+        min_rows_display=50,               # Always show at least 50 rows
+        repr_rows=20                       # Show 20 rows in __repr__ output
+    )
+
+These parameters help balance comprehensive data display against performance considerations.