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Julia is a high-level, high-performance programming language designed for technical computing, with syntax that is familiar to users of other technical computing environments. Introduced in 2012 by a team of four individuals - Viral B. Shah, Alan Edelman, Jeff Bezanson, and Stefan Karpinski - it aims to address the need for an expressive and efficient language for data manipulation and computation. Julia provides parallel computing capabilities out of the box and unlimited scalability with minimal effort. It has been utilized in a diverse range of applications including machine learning, scientific computing, and data science. The language's development and maintenance are managed by the Julia Computing company.

Ask the right questions secure the right Julia talent among an increasingly shrinking pool of talent.

First 20 minutes

General Julia app knowledge and experience

The first 20 minutes of the interview should seek to understand the candidate's general background in Julia application development, including their experience with various programming languages, databases, and their approach to designing scalable and maintainable systems.

How would you define Julia language?

Julia is a high-level, high-performance programming language for technical computing, with syntax that is familiar to users of other technical computing environments. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library.

What are the main uses of Julia programming language?

Julia is primarily used for numerical and scientific computing. It is also used in data analysis and data science, machine learning, and in the development of large mathematical models.

Describe the difference between Julia and Python.

While both Julia and Python are high-level programming languages used for scientific computing, they have some key differences. Julia is known for its speed and performance, which is comparable to languages like C and Fortran. Python is slower but is widely used due to its simplicity and the availability of libraries. Julia's syntax is more mathematical, making it more suitable for numerical and technical computing.

How would you handle missing values in Julia?

In Julia, missing values are handled using the 'missing' keyword. If a value is missing in a computation, the result is generally 'missing'. You can also use the 'ismissing()' function to check if a value is missing, and the 'coalesce()' function to replace missing values.

What are Macros in Julia and how would you use them?

Macros in Julia provide a method to include generated code in the final body of a program. A macro maps a tuple of arguments to a returned expression, and the resulting expression is compiled directly. This allows programmers to generate code programmatically, and to define custom language constructs.

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What you’re looking for early on

Does the candidate have a solid understanding of Julia's syntax and semantics?

Can the candidate effectively solve problems using Julia?

How well does the candidate understand and apply Julia's unique features, such as multiple dispatch and metaprogramming?

Is the candidate able to optimize Julia code for performance?

Next 20 minutes

Specific Julia development questions

The next 20 minutes of the interview should focus on the candidate's expertise with specific backend frameworks, their understanding of RESTful APIs, and their experience in handling data storage and retrieval efficiently.

How would you define and call a function in Julia?

Functions in Julia are defined using the 'function' keyword followed by the function name, parentheses enclosing any arguments, and the function body, ending with 'end'. Functions are called by writing the function name followed by parentheses enclosing any arguments.

Describe the difference between a Tuple and an Array in Julia.

In Julia, a Tuple is an ordered sequence of elements. It is immutable, meaning its elements cannot be changed once created. An Array, on the other hand, is a mutable data structure that can hold multiple items of the same type. Unlike Tuples, Arrays can be resized and their elements can be changed.

How would you perform error handling in Julia?

Error handling in Julia is done using the 'try', 'catch', and 'finally' keywords. The 'try' block contains the code that may potentially throw an error, the 'catch' block contains the code to handle the error, and the 'finally' block contains code that will be executed regardless of whether an error was thrown or not.

What are the benefits of using Julia for data analysis?

Julia has a number of benefits for data analysis. It has a simple, high-level syntax that is easy to read and write. It is also high-performance, meaning it can handle large datasets and complex computations efficiently. Furthermore, it has strong support for parallel and distributed computing, and a large number of libraries for data manipulation and analysis.

How would you implement multithreading in Julia?

Multithreading in Julia can be achieved using the '@threads' macro in combination with a 'for' loop. The '@threads' macro applies the loop iterations across the available computing cores, thus implementing multithreading.

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At this point, a skilled Julia engineer should demonstrate strong problem-solving abilities, proficiency in Julia programming language, and knowledge of software development methodologies. Red flags include lack of hands-on experience, inability to articulate complex concepts, or unfamiliarity with standard coding practices.

Digging deeper

Code questions

These will help you see the candidate's real-world development capabilities with Julia.

What does the following Julia code do?
println("Hello, World!")
This code prints the string 'Hello, World!' to the console.
What will be the output of the following Julia code?
x = 10
y = 20
println(x + y)
The output of the code will be 30. The code first assigns the values 10 and 20 to the variables x and y respectively, then it prints the sum of x and y.
What does the following Julia code do?
arr = [1, 2, 3, 4, 5]
println(sum(arr))
This code calculates the sum of all elements in the array 'arr' and prints the result, which is 15.
What does the following Julia code do?
@threads for i in 1:10
    println(i)
end
This code prints the numbers 1 through 10 in parallel using multiple threads. The order of the printed numbers may vary because the threads may not finish in the order they were started.

Wrap-up questions

Final candidate for Julia Developer role questions

The final few questions should evaluate the candidate's teamwork, communication, and problem-solving skills. Additionally, assess their knowledge of microservices architecture, serverless computing, and how they handle Julia application deployments. Inquire about their experience in handling system failures and their approach to debugging and troubleshooting.

Describe the difference between global and local scope in Julia.

In Julia, variables have either a global or local scope. Variables defined outside of any function or loop have a global scope and can be accessed from anywhere in the code. Variables defined inside a function or loop have a local scope and can only be accessed within that function or loop.

What are some ways to improve performance in Julia?

Performance in Julia can be improved in several ways. One is by avoiding global variables, which are slower than local variables. Another is by using type declarations, which allow the compiler to generate more efficient code. Using built-in functions and libraries, which are often optimized for performance, can also help.

How would you handle exceptions in Julia?

Exceptions in Julia are handled using a 'try-catch' block. The 'try' block contains the code that may throw an exception, and the 'catch' block contains the code to execute if an exception is thrown. The type of the exception can be specified to catch specific exceptions.

Julia application related

Product Perfect's Julia development capabilities

Beyond hiring for your Julia engineering team, you may be in the market for additional help. Product Perfect provides seasoned expertise in Julia projects, and can engage in multiple capacities.

Julia Consultive assessments

Julia Application Conversion Assessment Julia Application Integration Assessment Julia Data & Database Integration Assessment

Custom Julia development projects

Custom Julia App Conversion Julia Custom App Development Process App UI Design for Julia Facelifts

Hiring guide for Julia Engineers

Julia Developer Hiring Guide

What you’re looking for early on

The ideal back-end app developer

What you’re looking to see on the Julia engineer at this point.

Julia Consultive assessments

Custom Julia development projects