:doc:`ForecastService <../../forecast>` / Client / list_predictors

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list_predictors
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.. py:method:: ForecastService.Client.list_predictors(**kwargs)

  

  Returns a list of predictors created using the  CreateAutoPredictor or  CreatePredictor operations. For each predictor, this operation returns a summary of its properties, including its Amazon Resource Name (ARN).

   

  You can retrieve the complete set of properties by using the ARN with the  DescribeAutoPredictor and  DescribePredictor operations. You can filter the list using an array of  Filter objects.

  

  See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/forecast-2018-06-26/ListPredictors>`_  


  **Request Syntax**
  ::

    response = client.list_predictors(
        NextToken='string',
        MaxResults=123,
        Filters=[
            {
                'Key': 'string',
                'Value': 'string',
                'Condition': 'IS'|'IS_NOT'
            },
        ]
    )
    
  :type NextToken: string
  :param NextToken: 

    If the result of the previous request was truncated, the response includes a ``NextToken``. To retrieve the next set of results, use the token in the next request. Tokens expire after 24 hours.

    

  
  :type MaxResults: integer
  :param MaxResults: 

    The number of items to return in the response.

    

  
  :type Filters: list
  :param Filters: 

    An array of filters. For each filter, you provide a condition and a match statement. The condition is either ``IS`` or ``IS_NOT``, which specifies whether to include or exclude the predictors that match the statement from the list, respectively. The match statement consists of a key and a value.

     

    **Filter properties**

     

    
    * ``Condition`` - The condition to apply. Valid values are ``IS`` and ``IS_NOT``. To include the predictors that match the statement, specify ``IS``. To exclude matching predictors, specify ``IS_NOT``.
     
    * ``Key`` - The name of the parameter to filter on. Valid values are ``DatasetGroupArn`` and ``Status``.
     
    * ``Value`` - The value to match.
    

     

    For example, to list all predictors whose status is ACTIVE, you would specify:

     

    ``"Filters": [ { "Condition": "IS", "Key": "Status", "Value": "ACTIVE" } ]``

    

  
    - *(dict) --* 

      Describes a filter for choosing a subset of objects. Each filter consists of a condition and a match statement. The condition is either ``IS`` or ``IS_NOT``, which specifies whether to include or exclude the objects that match the statement, respectively. The match statement consists of a key and a value.

      

    
      - **Key** *(string) --* **[REQUIRED]** 

        The name of the parameter to filter on.

        

      
      - **Value** *(string) --* **[REQUIRED]** 

        The value to match.

        

      
      - **Condition** *(string) --* **[REQUIRED]** 

        The condition to apply. To include the objects that match the statement, specify ``IS``. To exclude matching objects, specify ``IS_NOT``.

        

      
    

  
  :rtype: dict
  :returns: 
    
    **Response Syntax**

    
    ::

      {
          'Predictors': [
              {
                  'PredictorArn': 'string',
                  'PredictorName': 'string',
                  'DatasetGroupArn': 'string',
                  'IsAutoPredictor': True|False,
                  'ReferencePredictorSummary': {
                      'Arn': 'string',
                      'State': 'Active'|'Deleted'
                  },
                  'Status': 'string',
                  'Message': 'string',
                  'CreationTime': datetime(2015, 1, 1),
                  'LastModificationTime': datetime(2015, 1, 1)
              },
          ],
          'NextToken': 'string'
      }
      
    **Response Structure**

    

    - *(dict) --* 
      

      - **Predictors** *(list) --* 

        An array of objects that summarize each predictor's properties.

        
        

        - *(dict) --* 

          Provides a summary of the predictor properties that are used in the  ListPredictors operation. To get the complete set of properties, call the  DescribePredictor operation, and provide the listed ``PredictorArn``.

          
          

          - **PredictorArn** *(string) --* 

            The ARN of the predictor.

            
          

          - **PredictorName** *(string) --* 

            The name of the predictor.

            
          

          - **DatasetGroupArn** *(string) --* 

            The Amazon Resource Name (ARN) of the dataset group that contains the data used to train the predictor.

            
          

          - **IsAutoPredictor** *(boolean) --* 

            Whether AutoPredictor was used to create the predictor.

            
          

          - **ReferencePredictorSummary** *(dict) --* 

            A summary of the reference predictor used if the predictor was retrained or upgraded.

            
            

            - **Arn** *(string) --* 

              The ARN of the reference predictor.

              
            

            - **State** *(string) --* 

              Whether the reference predictor is ``Active`` or ``Deleted``.

              
        
          

          - **Status** *(string) --* 

            The status of the predictor. States include:

             

            
            * ``ACTIVE``
             
            * ``CREATE_PENDING``, ``CREATE_IN_PROGRESS``, ``CREATE_FAILED``
             
            * ``DELETE_PENDING``, ``DELETE_IN_PROGRESS``, ``DELETE_FAILED``
             
            * ``CREATE_STOPPING``, ``CREATE_STOPPED``
            

             

            .. note::

              

              The ``Status`` of the predictor must be ``ACTIVE`` before you can use the predictor to create a forecast.

              

            
          

          - **Message** *(string) --* 

            If an error occurred, an informational message about the error.

            
          

          - **CreationTime** *(datetime) --* 

            When the model training task was created.

            
          

          - **LastModificationTime** *(datetime) --* 

            The last time the resource was modified. The timestamp depends on the status of the job:

             

            
            * ``CREATE_PENDING`` - The ``CreationTime``.
             
            * ``CREATE_IN_PROGRESS`` - The current timestamp.
             
            * ``CREATE_STOPPING`` - The current timestamp.
             
            * ``CREATE_STOPPED`` - When the job stopped.
             
            * ``ACTIVE`` or ``CREATE_FAILED`` - When the job finished or failed.
            

            
      
    
      

      - **NextToken** *(string) --* 

        If the response is truncated, Amazon Forecast returns this token. To retrieve the next set of results, use the token in the next request.

        
  
  **Exceptions**
  
  *   :py:class:`ForecastService.Client.exceptions.InvalidNextTokenException`

  
  *   :py:class:`ForecastService.Client.exceptions.InvalidInputException`

  