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Vectorflow

From Netflix·Updated May 13, 2026·View on GitHub·

**Vectorflow** is a minimalist neural network library optimized for sparse data and single machine environments. The project is written primarily in D, distributed under the Apache License 2.0 license, first published in 2017. It has gained significant community traction with 1,294 stars and 86 forks on GitHub.

<img src="http://ae.nflximg.net/vectorflow/vectorflow_logo.png" width="200">

Vectorflow is a minimalist neural network library optimized for sparse data and single machine environments.

Original blog post here.

Build Status

Installation

dub package

The library is distributed as a dub package. Add vectorflow to the dependencies section of your dub.json:

"vectorflow": "~>1.0.2"

The library itself doesn't have any dependencies. All you need is a recent D compiler.

LDC is the recommended compiler for the fastest runtime speed.

Tested on:

  • Linux, OSX
  • LDC version: >= 1.1.1
  • DMD version: >= 2.073.1

Setting up a D environment

If you're new to D, keep reading. You will need dub (the D package manager) and LDC (the LLVM-based D compiler).

macOS
brew install dub
brew install ldc
Ubuntu
apt-get install -y curl xz-utils
curl -fsS https://dlang.org/install.sh | bash -s ldc
source ~/dlang/ldc-{VERSION}/activate

Examples

To run the RCV1 example (sparse logistic regression):

cd examples && ./compile_run.sh rcv1.d

Tests

To run the tests:

dub test

Documentation

vectorflow uses ddoc.
One way of building and serving the documentation locally (you will need libevent for serving) is:

dub build -b ddox && dub run -b ddox

Or use your favorite DDOC compiler.

Please also refer to the repo wiki.

Contributors

Showing top 8 contributors by commit count.

View all contributors on GitHub →

This article is auto-generated from Netflix/vectorflow via the GitHub API.Last fetched: 6/1/2026