Invoke Perl static methods from Python package

This article provides an introduction to cross-technology invocation of static methods.

Javonet allows you to reference and use modules or packages written in (Java/Kotlin/Groovy/Clojure, C#/VB.NET, Ruby, Perl, Python, JavaScript/TypeScript) like they were created in your technology. If have not yet created your first project check Javonet overview and quick start guides for your technology.

With Javonet you can interact with static methods from Python package like they were available in Perl but invocation must be performed through Javonet SDK API, passing the name of the target method as String.

Javonet allows you to pass any Perl value type as argument to static method from Python package. In example: int, float, string, char, long and other. For reference type arguments (instances of other classes) you can create such instance with Javonet and pass the Invocation Context variable referencing that object as argument of static method invocation.

Custom Python package with Perl static method

With Javonet it is possible to reference any custom Python package and interact with public static methods declared on types defined within that module almost the same as with any other Perl library.

Snippet below represents the sample code from Python package which contains class and its methods:

@staticmethod
def multiply_by_two(a):
	return 2 * a

def multiply_two_numbers(self, a, b):
	return a * b

It is possible to invoke one of the declared static methods from Python package using following Perl code.

# use activate only once in your app
Javonet->activate("your-license-key");

# create Python runtime context
my $python_runtime = Javonet->in_memory()->python();

# set up variables
my $library_path = $resources_directory;
my $class_name = "TestClass.TestClass";

# load Python custom library
$python_runtime->load_library($library_path);

# get type from the runtime
my $python_type = $python_runtime->get_type($class_name)->execute();

#  invoke type's static method
my $response = $python_type->invoke_static_method("multiply_by_two", 25)->execute();

# get value from response
my $result = $response->get_value();

# print result to console
print("$result\n");

In code snippet above you can see how easily you can activate Javonet and instruct it using inMemory() method to create new RuntimeContext that will run python-package runtime within your current process. Next with addLibrary method it triggers the load of required python-package module and allows you to interact with any classes and their static methods defined in that package.

Further calls to invokeStaticMethod() allows to call "multiplyByTwo" python-package static method and pass the value type arguments. With Javonet you can invoke methods with any number and any type of arguments including value type arguments, reference type arguments, arrays and collections.

You can receive and further process and type of result returned by called python-package method, regardless if it is reference type that will get returned as another instance of Invocation Context that you can use for further interaction, or value type that you can obtain as perl value with getValue() method.

Perl framework static method

With Javonet you can interact not only with any custom python-package module but also with any python-package framework objects. The same steps are required to use types and methods from standard Python package framework class:

# use activate only once in your app
Javonet->activate("your-license-key");

# create Python runtime context
my $python_runtime = Javonet->in_memory()->python();

# get type from the runtime
my $python_type = $python_runtime->get_type("builtins")->execute();

# invoke type's static method
my $response = $python_type->invoke_static_method("abs", -50)->execute();

# get value from response
my $result = $response->get_value();

# print result to console
print("$result\n");

In sample above you see how the Javonet allows to create an instance of Python package Math class and interact with its static abs method. The same operation can be performed remotely by just changing the new Runtime Context invocation from in memory to tcp that will create and interact with your Python package objects on any remote node, container or service that hosts Javonet Code Gateway. This way you can preserve the same logic in your application and instantly switch between monolithic and microservices architecture without the need to implement the integration layer based on web services or other remote invocation methods.

Read more about use cases and software architecture scenarios where Javonet runtime bridging technology can support your development process.