Julia vs Pharo

Julia runs almost as fast as (and in fact in some cases faster than) C code.

Dynamic and high level, but does not isolate the user from properly thinking about types. Can do explicit type signatures which is great for teaching structured thinking.

Out of the box Julia has a very good Read-Eval-Print-Loop, which both completes functions and types, as well as completion based on history of previous statements. It integrates well with the shell and has an excellent online help system.

Julia code is easy to read and avoid a lot of unnecessary special symbols and fluff. It uses newline to end statements and "end" to end blocks so there is no need for lots of semicolons and curly braces. It is regular in that unless it is a variable assignment, function name always comes first. No need to be confused about whether something is a method on an object or a free function.

Unlike Python and Ruby, since you can annotate the types a function operates on, you can overload function names, so that you can use the same function name for many data types. So you can keep simple descriptive function names and not have to invent artificial function names to separate them from the type they operate on.

The Julia language is written in itself to a much larger extent than most other languages, so a budding programmer can read through the depths of the standard library and learn exactly how things work all the way down to the low-level bit-twiddling details, which can be englightening.

Julia has built in n-dimensional arrays similar in functionality as Python's numpy.

You can have multiple functions with the same name, but doing different things depending on function arguments and argument types.

Julia requires no boilerplate code – a beginner needs to write only the parts they care about. This combined with the REPL provides the best learning experience available.

Julia provides a high level of abstraction, making platform-independent programming trivial and easing the learning curve.

You can perform operations on scalars, for example 2^2 or [1, 2, 3].^2.

Julia allows you to edit Julia code in the language itself and write powerful macros. It is a great introduction to metaprogramming features

The Julia REPL allows quickly testing how some code behaves and gives access to documentation and package management immediately in the REPL.

In Pharo everything is an object. Compiler - object, network - object, method - also an object. And objects communicate with messages. No operators, no control-flow statements. Just objects and messages. Few things to learn, but you can learn OOP well.

There is good, free documentation including several books written by experts with extensive examples. There is an online MOOC. There are many tutorial videos. Supportive conferences and community. Even a professional support option if desired.

The nature of Pharo being a "live" environment allows you to perform live updates to your system without requiring to restart it. You can upgrade/modify classes while serving requests at the same time.

The framework for developing sophisticated web applications in Smalltalk is developed in Pharo. Seaside lets you build highly interactive web applications quickly, reusably and maintainably.

No need to search google for compact beautiful examples of how to do things, your live environment source is available and you can easily live search, see how it works and copy how the masters would do it (examples most languages still copy too).

Most languages are still copying the Smalltalk tools of yesterday - GTInspector (written in Glamorous) takes live exploration of code/running objects to a new level. It's really slick, and better yet, you can easily write your own inspectors in 10 lines of code.

Use 32 bit or 64 bit versions of Pharo on Windows, Mac & Linux.

MOOSE environment provides extensive, easily leveraged and class leading tools for code analysis and improvement.

Roassal and Mondrian provide fantastic and easily used frameworks for graphics, graphing and advanced visualisations (comparable to D3.js) but with much less code. Visualisations can be rendered into web friendly graphics (SVG, .png etc.) without additional work.