text: import dash_html_components as html
  
  from dash.dependencies import Input, Output
  import dash_core_components as dcc
  import dash_html_components as html
  import pandas as pd
  
  from dash_docs import tools
  from dash_docs import styles
  from dash_docs import reusable_components
  
  examples = {
      example: tools.load_example('tutorial/examples/table/{}'.format(example))
      for example in ['virtualization.py']
  }
  
  layout = html.Div(
      [
          reusable_components.Markdown(
          """
          # Virtualization
  
          In addition to pagination, `DataTable` also has virtualization capabilities
          for viewing large datasets. Virtualization saves browser resources while
          still permitting the user to scroll through the entire dataset. It achieves this
          by only a rendering a subset of the data at any instant.
  
          The virtualiztion backend makes a few assumptions about the style of
          your `DataTable` which must be adhered to in order to ensure that the
          table scrolls smoothly.
  
          - the width of the columns is fixed
          - the height of the rows is always the same
          - runtime styling changes will not affect width and height compared to
          the table's first rendering
  
          The example below prevents runtime style changes by fixing the column
          widths and setting the white-space CSS property in the cells to normal.
          """
          ),
  
          reusable_components.Markdown(
              examples['virtualization.py'][0],
              style=styles.code_container
          ),
  
          html.Div(
              examples['virtualization.py'][1],
              className='example-container'
          ),
  
      ]
  )
  