Julia Tools and Editors¶

Contents¶

• Julia Tools and Editors
  • Preliminary Setup
  • The REPL
  • Atom
  • Package Environments

Co-authored with Arnav Sood

While Jupyter notebooks are a great way to get started with the language, eventually you will want to use more powerful tools.

We’ll discuss a few of them here, such as

• Text editors like Atom, which come with rich Julia support for debugging, documentation, git integration, plotting and inspecting data, and code execution.
• The Julia REPL, which has specialized modes for package management, shell commands, and help.

Note that we assume you’ve already completed the getting started and interacting with Julia lectures.

Preliminary Setup¶

Follow the instructions for setting up Julia on your local computer.

The REPL¶

Previously, we discussed basic use of the Julia REPL (“Read-Evaluate-Print Loop”).

Here, we’ll consider some more advanced features.

Shell Mode¶

Hitting ; brings you into shell mode, which lets you run bash commands (PowerShell on Windows)

You can also use Julia variables from shell mode

Package Mode¶

Hitting ] brings you into package mode.

• ] add Expectations will add a package (here, Expectations.jl).
• Likewise, ] rm Expectations will remove that package.
• ] st will show you a snapshot of what you have installed.
• ] up will (intelligently) upgrade versions of your packages.
• ] precompile will precompile everything possible.
• ] build will execute build scripts for all packages.
• Running ] preview before a command (i.e., ] preview up) will display the changes without executing.

You can get a full list of package mode commands by running

On some operating systems (such as OSX) REPL pasting may not work for package mode, and you will need to access it in the standard way (i.e., hit ] first and then run your commands).

Help Mode¶

Hitting ? will bring you into help mode.

The key use case is to find docstrings for functions and macros, e.g.

Note that objects must be loaded for Julia to return their documentation, e.g.

will fail, but

will succeed.

Atom¶

As discussed previously, eventually you will want to use a fully fledged text editor.

The most feature-rich one for Julia development is Atom, with the Juno package.

There are several reasons to use a text editor like Atom, including

• Git integration (more on this in the next lecture).
• Painless inspection of variables and data.
• Easily run code blocks, and drop in custom snippets of code.
• Integration with Julia documentation and plots.

Installation and Configuration¶

Installing Atom¶

1. Download and Install Atom from the Atom website.

2. (Optional, but recommended): Change default Atom settings

   • Use Ctrl-, to get the Settings pane
   • Choose the Packages tab

   • Type line-ending-selector into the Filter and then click “Settings” for that package

     • Change the default line ending to LF (only necessary on Windows)

   • Choose the Editor tab

     • Turn on Soft Wrap
     • Set the Tab Length default to 4

Installing Juno¶

1. Use Ctrl-, to get the Settings pane.
2. Go to the Install tab.
3. Type uber-juno into the search box and then click Install on the package that appears.
4. Wait while Juno installs dependencies.
5. When it asks you whether or not to use the standard layout, click yes.

At that point, you should see a built-in REPL at the bottom of the screen and be able to start using Julia and Atom.

Troubleshooting¶

Sometimes, Juno will fail to find the Julia executable (say, if it’s installed somewhere nonstandard, or you have multiple).

To do this

1. Ctrl-, to get Settings pane, and select the Packages tab.
2. Type in julia-client and choose Settings.
3. Find the Julia Path, and fill it in with the location of the Julia binary.

• To find the binary, you could run Sys.BINDIR in the REPL, then add in an additional /julia to the end of the screen.
• e.g. C:\Users\YOURUSERNAME\AppData\Local\Julia-1.0.1\bin\julia.exe on Windows as /Applications/Julia-1.0.app/Contents/Resources/julia/bin/julia on OSX.

See the setup instructions for Juno if you have further issues.

If you upgrade Atom and it breaks Juno, run the following in a terminal.

If you aren’t able to install apm in your PATH, you can do the above by running the following in PowerShell:

Then navigating to a folder like C:\Users\USERNAME\AppData\Local\atom\bin (which will contain the apm tool), and running:

Upgrading Julia¶

To get a new release working with Jupyter, run (in the new version’s REPL)

This will install (and build) the IJulia kernel.

To get it working with Atom, open the command palette and type “Julia Client: Settings.”

Then, in the box labelled “Julia Path,” enter the path to yor Julia executabe.

You can find the folder by running Sys.BINDIR in a new REPL, and then add the /julia at the end to give the exact path.

For example:

Standard Layout¶

If you follow the instructions, you should see something like this when you open a new file.

If you don’t, simply go to the command palette and type “Julia standard layout”

The bottom pane is a standard REPL, which supports the different modes above.

The “workspace” pane is a snapshot of currently-defined objects.

For example, if we define an object in the REPL

Our workspace should read

The ans variable simply captures the result of the last computation.

The Documentation pane simply lets us query Julia documentation

The Plots pane captures Julia plots output (the code is as follows)

Note: The plots feature is not perfectly reliable across all plotting backends, see the Basic Usage page.

Other Features¶

• Shift + Enter will evaluate a highlighted selection or line (as above).
• The run symbol in the left sidebar (or Ctrl+Shift+Enter) will run the whole file.

See basic usage for an exploration of features, and the FAQ for more advanced steps.

Package Environments¶

Julia’s package manager lets you set up Python-style “virtualenvs,” or subsets of packages that draw from an underlying pool of assets on the machine.

This way, you can work with (and specify) the dependencies (i.e., required packages) for one project without worrying about impacts on other projects.

• An environment is a set of packages specified by a Project.toml (and optionally, a Manifest.toml).
• A registry is a git repository corresponding to a list of (typically) registered packages, from which Julia can pull (for more on git repositories, see version control).
• A depot is a directory, like ~/.julia, which contains assets (compile caches, registries, package source directories, etc.).

Essentially, an environment is a dependency tree for a project, or a “frame of mind” for Julia’s package manager.

• We can see the default (v1.1) environment as such

• We can also create and activate a new environment

• And go to it

• To activate the directory, simply

where “.” stands in for the “present working directory”.

• Let’s make some changes to this

Note the lack of commas

• To see the changes, simply open the ExampleEnvironment directory in an editor like Atom.

The Project TOML should look something like this

We can also

Note The TOML files are independent of the actual assets (which live in ~/.julia/packages, ~/.julia/dev, and ~/.julia/compiled).

You can think of the TOML as specifying demands for resources, which are supplied by the ~/.julia user depot.

• To return to the default Julia environment, simply

without any arguments.

• Lastly, let’s clean up

InstantiateFromURL¶

With this knowledge, we can explain the operation of the setup block

What this github_project function does is activate (and if necessary, download, instantiate and precompile) a particular Julia environment.