I've been using py4j to build a user-friendly Python library around a less user-friendly Java library. For the most part, this has been a breeze, and py4j has been a great tool. However, I've come across a snag when sending matrices between Python and Java.
Specifically, I have a static function in java that accepts, as its arguments, an integer matrix:
public class MyClass {
// ...
public static MyObject create(int[][] matrix) {
// ...
}
}
I'd like to be able to call this from Py4j like so:
def create_java_object(numpy_matrix):
# <code here checks that numpy_matrix is a (3 x n) integer matrix>
# ...
return java_instance.jvm.my.namespace.MyClass.create(numpy_matrix)
This doesn't work, which isn't too surprising, nor does it work if the numpy_matrix
is instead converted to a list of plain python lists. I had expected that the solution would be to construct a java array and transfer the data over prior to the function call:
def create_java_object(numpy_matrix):
# <code here checks that numpy_matrix is a (3 x n) integer matrix>
# ...
java_matrix = java_instance.new_array(java_instance.jvm.int, 3, n)
for i in range(numpy_matrix.shape[1]):
java_matrix[0][i] = int(numpy_matrix[0, i])
java_matrix[1][i] = int(numpy_matrix[1, i])
java_matrix[2][i] = int(numpy_matrix[2, i])
return java_instance.jvm.my.namespace.MyClass.create(java_matrix)
Now, this code runs correctly. However, it requires approximately two minutes to run. The matrices I'm working with, by the way, are on the order of (3 x ~300,000) elements.
Is there a canonical way to do this in Py4j that doesn't require incredible amounts of time just to convert a matrix? I don't mind it taking a second or two, but this is far too slow. If Py4j isn't setup for this kind of communication, is there a Java interop library for Python that is?
Note: The Java library treats the int[][]
matrix as an immutable array; i.e., it never attempts to modify it.