anchor.diff:  
   Next, let's collect training data for this Engine. By default,
   the E-Commerce Recommendation Engine Template supports 2 types of entities and 2 events: **user** and
  -**item**; events **view** and **buy**. Each item has a **categories** property, which is a list of category names (String). A user can view and buy an item.
  -
  -There is also one special **constraint** entity with entity ID **unavailableItems**, which defines a list of unavailable items and is taken into account in real time during serving.
  +**item**; events **view** and **buy**. An item has the **categories** property, which is a list of category names (String). A user can view and buy an item. The specical **constraint** entiy with entityId **unavailableItems** defines a list of unavailable items and is taken into account in realtime during serving.
  +
  +In summary, this template requires '$set' user event, '$set' item event, user-view-item events, user-buy-item event and '$set' constraint event.
   
   <%= partial 'shared/quickstart/install_sdk' %>
  -
  -The following is a sample code of using different SDKs to import events of setting user and item properties, user-view-item events, user-buy-item events and setting the constraint **unavailableItems**.
   
   <div class="tabs">
     <div data-tab="Python SDK" data-lang="python">
  
positive.code: 
  ## 6. Use the Engine
  
  Now, You can retrieve predicted results. To recommend 4 items to user ID "u1". You send this JSON `{ "userEntityId": "u1", "number": 4 }` to the deployed engine and it will return a JSON of the recommended items. Simply send a query by making a HTTP request or through the `EngineClient` of an SDK:
  
  <div class="tabs">
    <div data-tab="Python SDK" data-lang="python">
  ```python
  import predictionio
  
negative.code:         "userEntityId", "u1",
          "number",  4
      ));
  ```
    </div>
  </div>
  