Package Guide

To work with the PyCallJLD2.jl package, you should know:

• How to install the package
• How to use the package

Installation

The PyCallJLD2.jl package can be installed using the Julia package manager. From the Julia REPL, type ] to enter the Pkg REPL mode and run

julia> ]
(@v1.9) pkg> add PyCallJLD2

Alternatively, it can be added to your environment in a script with

using Pkg
Pkg.add("PyCallJLD2")

If you wish to have the latest changes between releases, you can directly add the GitHub repo at an arbitrary branch (such as develop) as a dependency with

julia> ]
(@v1.9) pkg> add https://github.com/AP6YC/PyCallJLD2.jl#develop

Basic Usage

To save and load JLD2, load PyCall, JLD2, and PyCallJLD2 in the same scope as where you intend to use the JLD2.save and JLD2.load functions. If you are coming from PyCallJLD, simply replace JLD with JLD2 everywhere in your usage:

# Import all of your dependencies
import PyCall, JLD2, PyCallJLD2

and use the JLD2 API to save:

JLD2.save("model_file.jld2", "model_name", model)

or load:

JLD2.load("model_file.jld2", "model_name")

The following example is take from PyCallJLD for direct comparison:

# Load all dependencies in the context where we plan on saving and loading
using PyCall, JLD2, PyCallJLD2

# Import the scikit-learn linear model module
@pyimport sklearn.linear_model as lm

# Create some Python objects
m1 = lm.LinearRegression()
m2 = lm.ARDRegression()

# Save them to models.jld2
JLD2.save("models.jld2", "mods", [m1, m2])

# Load them back
models = JLD2.load("models.jld2", "mods")

# Do a dance🕺

Just as in PyCallJLD, these objects are saved with pickle.dumps.