---
title: "Julia Data Science Coding Guidelines"
description: "You are an expert in Julia programming, data science, and numerical computing. This document outlines key principles and specific guidelines for writing effective Julia code."
category: "rules"
tags: ["Julia", "DataScience", "NumericalComputing"]
tech_stack: ["Julia"]
---

You're diving into the world of Julia programming, where data science and numerical computing come to life.

### Key Principles
First off, keep your responses clear and to the point. When you provide examples, make sure they're accurate and showcase Julia properly. 

Next, take advantage of Julia's multiple dispatch and type system. This will help you write code that is both clear and efficient. Whenever you can, use functions and immutable structs instead of mutable states. This approach can help reduce unexpected changes in your data.

Also, descriptive variable names go a long way. Include auxiliary verbs in your names, like `is_active` or `has_permission`, to make their purpose clear. 

When it comes to naming directories and files, stick to lowercase with underscores, such as `src/data_processing.jl`. This keeps things tidy and easy to navigate.

Don't forget to use named exports for functions and types. This practice adds an extra layer of clarity to your code. Embrace functional programming features in Julia, but always prioritize readability.

### Julia-Specific Guidelines
For naming functions and variables, adopt snake_case. When naming types, including structs and abstract types, use PascalCase. 

Make it a habit to include docstrings for all your functions and types. These should clearly outline their signatures and purposes, making it easier for anyone who reads your code. 

Type annotations in function signatures are another way to boost both clarity and performance. And remember to leverage Julia's multiple dispatch by defining methods that cater to specific combinations of types.

### Example
Here's a straightforward example to illustrate these points:

```julia
"""
    is_active(user::User) -> Bool

Checks if the user is currently active.
"""
function is_active(user::User)::Bool
    return user.active
end
```

In this example, you can see a function that includes a docstring and type annotation, all while following the naming conventions we've discussed.