NDScala

What it is

NDScala provides N-dimensional arrays for Scala 3, offering compile-time type-checking and inference over shapes, tensor/axis labels, and numeric data types. It is inspired by NumPy ndarray but tailored for the Scala ecosystem.

NDScala stands out by offering compile-time safety and efficiency for N-dimensional arrays in Scala, making it ideal for projects that require strict type-checking over shapes, labels, and numeric types.

When it fits — and when it doesn’t

Known weaknesses

Each one links to the public issue, changelog or docs page it came from, where we have one.

1. 01

   Limited community and support

   Being a niche library for Scala, the user base is relatively small compared to more established libraries like NumPy or TensorFlow.

2. 02

   Complex setup process

   Integrating NDScala into existing projects requires careful configuration of Scala 3 and potential dependency conflicts with other libraries.

3. 03

   Performance limitations for large-scale operations

   While optimized, NDScala may not match the performance of native C/Fortran implementations used in libraries like NumPy due to JVM overhead.

4. 04

   Sparse documentation and examples

   The project's documentation lacks comprehensive guides and practical examples, making it harder for new users to get started quickly.

What it does well

• Compile-time type-checking and inference over shapes, tensor/axis labels, and numeric data types.

• Inspired by NumPy ndarray but tailored for Scala 3.

• Supports N-dimensional arrays.

Pricing

Free tier

YesOpen source — free to use

Paid from

$0

Model

Flat rate

Enterprise plan

No

Pricing not independently confirmed — check the vendor’s page.