Index operator []

This article shows usage of [] operator for arrays and collections. In Javonet, every array or collection from called technology is treated as a reference.

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 arrays from NodeJs package like they were available in Python but invocation must be performed through Javonet SDK API.

Custom NodeJs package with arrays handling

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

Snippet below represents the sample code from NodeJs package that has methods which return or process the arrays:

get1DArray() {
	return ["one", "two", "three", "four", "five"]
}

get2DArray() {
	return [["S00", "S01"], ["S10", "S11"]]
}
addArrayElementsAndMultiply(myArray, myValue) {
	return myArray.reduce((accumulator, currentValue) => accumulator + currentValue) * myValue
}

Each array or collection from NodeJs package returns as InvocationContext which contains reference to the target data. Javonet SDK implements [] operator on InvocationContext to interact with complex data objects in Python:

Get element

I code in:
# use activate only once in your app
Javonet.activate("your-license-key")

# create called runtime context
called_runtime = Javonet.in_memory().nodejs()

# set up variables
library_path = resources_directory + '/TestClass.js'
class_name = 'TestClass'

# load custom library
called_runtime.load_library(library_path)

# get type from the runtime
called_runtime_type = called_runtime.get_type(class_name).execute()

# create type's instance
instance = called_runtime_type.create_instance().execute()

# invoke instance's method
array = instance.invoke_instance_method("get1DArray").execute()

# get element of array and invoke method on it
response = array[2].execute()

# get value from response
result = response.get_value()

# write result to console
print(result)

In the snippet above, get1DArray method is used to get reference to 1D array from NodeJs package. Operator [] is used to get element from the array.

Set element

I code in:
# use activate only once in your app
Javonet.activate("your-license-key")

# create called runtime context
called_runtime = Javonet.in_memory().nodejs()

# set up variables
library_path = resources_directory + '/TestClass.js'
class_name = 'TestClass'

# load custom library
called_runtime.load_library(library_path)

# get type from the runtime
called_runtime_type = called_runtime.get_type(class_name).execute()

# create type's instance
instance = called_runtime_type.create_instance().execute()

# invoke instance's method
array = instance.invoke_instance_method("get1DArray").execute()

# set element of array
array[2] = "zero"

# get element of array
response = array[2].execute()

# get value from response
result = response.get_value()

# write result to console
print(result)

In the snippet above, get1DArray method is used to get reference to 1D array from NodeJs package. Operator [] is used to set element of the 1D array.

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 NodeJs 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.

Additional references