Java is everywhere in backend systems, enterprise applications, and production environments. But when it comes to numerical computing, data manipulation, and scientific-style operations, Python's NumPy ecosystem has become the standard.
I wanted a similar experience in Java: a lightweight, dependency-free library for working with multidimensional arrays and linear algebra.
That idea became NumPy4J.
What is NumPy4J?
NumPy4J is an open-source numerical computing library for Java inspired by NumPy.
It provides:
Multidimensional arrays (NDArray)
NumPy-style broadcasting
Array creation utilities
Reshaping and slicing
Element-wise operations
Linear algebra operations
Example:
NDArray A = NDArray.of(new double[]{
1, 2,
3, 4
}, 2, 2);
NDArray B = NDArray.ones(2, 2);
NDArray C = A.add(B);
Matrix operations:
NDArray result = LinearAlgebra.matmul(A, B);
Solving equations:
NDArray x = LinearAlgebra.solve(A, b);
Why build another numerical library?
There are already excellent Java math libraries available.
The goal of NumPy4J is different:
Provide a NumPy-like API experience
Make multidimensional arrays a first-class concept in Java
Keep the API simple and approachable
Create a foundation for future scientific computing features
Testing approach
To make sure behavior stays consistent, NumPy4J uses Python NumPy as a reference implementation.
Test cases are generated with NumPy and validated against the Java implementation, covering:
Broadcasting
Matrix operations
Reshaping
Transpose
Linear solving
Element-wise calculations
What's next?
The roadmap includes:
More NumPy-compatible operations
Matrix decompositions (QR, LU, Cholesky)
Eigenvalue computation
More statistics functions
Performance improvements
Try it out
If you work with Java and need NumPy-style numerical operations, I would love for you to try NumPy4J, provide feedback, and contribute ideas.
GitHub: https://github.com/darius1973/numpy4j
Documentation: https://darius1973.github.io/numpy4j/index.html
Wiki: https://github.com/darius1973/numpy4j/wiki/NumPy4J-Wiki
Available at: https://central.sonatype.com/artifact/io.github.darius1973/numpy4j
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