Class PythonServiceConfig

  • All Implemented Interfaces:

    public class PythonServiceConfig
    extends java.lang.Object
    Configuration object for the Python service factory, used in a mapUsingPython stage.

    Hazelcast Jet expects you to have a Python project in a local directory. It must contain the definition of a transform_list() function that receives a list of strings and returns a list of strings of the same size, with a one-to-one mapping between input and output elements. Here's a simple example of a function that transforms every input string by prepending "echo-" to it:

     def transform_list(input_list):
         return ["echo-%s" % i for i in input_list]
    If you have a very simple setup with everything in a single Python file, you can use setHandlerFile(java.lang.String). Let's say you saved the above Python code to a file named You can use it from Jet like this:
     StreamStage<String> inputStage = createInputStage();
     StreamStage<String> outputStage = inputStage.apply(
             mapUsingPython(new PythonServiceConfig()
    In more complex setups you can tell Jet the location of your project directory and the name of the Python module containing transform_list(). You can also use a different name for the function.

    Jet uploads the entire directory to the cluster, creates one or more Python processes on each member, and sends the pipeline data through your function. The number of processes is controlled by the local parallelism of the Python mapping stage.

    Jet recognizes these special files in the base directory:

    • requirements.txt is assumed to list the dependencies of your Python code. Jet will automatically install them to a job-local virtual environment. You can also install the modules to the Jet servers' global Python environment in order to speed up job initialization. Jet reuses the global modules and adds the missing ones.
    • is assumed to be a shell script that Jet will run when initializing the job.
    • is assumed to be a shell script that Jet will run when completing the job.
    Regardless of local parallelism, the init and cleanup scripts run only once per cluster member. They run within the context of the job-local virtual Python environment.

    To use this stage in a Hazelcast Jet cluster, Python must be installed on every cluster member. Jet supports Python versions 3.5-3.7. If the code has dependencies on non-standard Python modules, these must either be pre-installed or the member machines must have access to the public internet so that Jet can download and install them. A third option is to write that uses a different way of installing the dependencies. In that case make sure not to use the standard filename requirements.txt, which Jet uses automatically.

    The Python mapping stage produces log output at the FINE level under the com.hazelcast.jet.python log category. This includes all the output from launched subprocesses.

    Jet 4.0
    See Also:
    Serialized Form
    • Constructor Detail

      • PythonServiceConfig

        public PythonServiceConfig()
    • Method Detail

      • baseDir

        public baseDir()
        Returns the Python base directory.
      • setBaseDir

        public PythonServiceConfig setBaseDir​(@Nonnull
                                              java.lang.String baseDir)
        Sets the base directory where the Python files reside. When you set this, also set the name of the handler module to identify the location of the handler function (named transform_list() by convention).

        If all you need to deploy to Jet is in a single file, you can call setHandlerFile(java.lang.String) instead.

      • handlerFile

        public handlerFile()
        Returns the Python handler file.
      • handlerModule

        public java.lang.String handlerModule()
        Returns the handler module name.
      • setHandlerModule

        public PythonServiceConfig setHandlerModule​(@Nonnull
                                                    java.lang.String handlerModule)
        Sets the name of the Python module that has the function that transforms Jet pipeline data.
      • handlerFunction

        public java.lang.String handlerFunction()
        Returns the name of the handler function. The default value is transform_list.
      • setHandlerFunction

        public PythonServiceConfig setHandlerFunction​(@Nonnull
                                                      java.lang.String handlerFunction)
        Overrides the default name of the Python function that transforms Jet pipeline data. The default name is "transform_list". It must be defined in the module you configured with setHandlerModule(java.lang.String), must take a single argument that is a list of strings, and return another list of strings which has the results of transforming each item in the input list. There must be a strict one-to-one match between the input and output lists.
      • setChannelFn

        public PythonServiceConfig setChannelFn​(@Nonnull
                                                BiFunctionEx<java.lang.String,​java.lang.Integer,​? extends io.grpc.ManagedChannelBuilder<?>> channelFn)
        Sets the channel function. The function receives a host+port tuple, and it's supposed to return a configured instance of ManagedChannelBuilder. You can use this to configure the channel, for example to configure the maximum message size etc.

        The default value is NettyChannelBuilder::forAddress.