  We present FrankWolfe.jl, an open-source implementation of several popular
Frank-Wolfe and Conditional Gradients variants for first-order constrained
optimization. The package is designed with flexibility and high-performance in
mind, allowing for easy extension and relying on few assumptions regarding the
user-provided functions. It supports Julia's unique multiple dispatch feature,
and interfaces smoothly with generic linear optimization formulations using
MathOptInterface.jl.
