
- Julia - Home
- Julia - Overview
- Julia - Environment Setup
- Julia - Basic Syntax
- Julia - Arrays
- Julia - Tuples
- Integers & Floating-Point Numbers
- Julia - Rational & Complex Numbers
- Julia - Basic Operators
- Basic Mathematical Functions
- Julia - Strings
- Julia - Functions
- Julia - Flow Control
- Julia - Dictionaries & Sets
- Julia - Date & Time
- Julia - Files I/O
- Julia - Metaprogramming
- Julia - Plotting
- Julia - Data Frames
- Working with Datasets
- Julia - Modules and Packages
- Working with Graphics
- Julia - Networking
- Julia - Databases
- Julia Useful Resources
- Julia - Quick Guide
- Julia - Useful Resources
- Julia - Cheatsheet
- Julia - Discussion
Julia Cheatsheet
The Julia cheatsheet provides a quick reference to all its fundamental topics. Julia is a high-performance, dynamic language designed for fast numerical and scientific computing. By learning this cheat sheet, the user can prepare for the interviews and exams. Go through this cheat sheet and learn the Julia programming language.
Table of Content
- Introduction to Julia
- Comments
- Julia REPL Shortcuts
- Comments
- Variable Assignment and Scope
- Data Types
- Type Conversion
- Constants in Julia
- Operators
- Conditional Statements (if, else, elseif)
- Loops (for and while)
- Exception Handling (try, catch, finally)
- Defining and Calling Functions
- Anonymous and Higher-Order Functions
- Multiple Dispatch
- Type Annotations
- Arrays
- Matrices
- Indexing
- Tuples
- Named Tuples
- Dictionaries
- Sets
- String Manipulation
- String Interpolation
- Regular Expressions in Julia
- File Handling
- Working with CSV and JSON Files
- Creating Modules
- Installing and Managing Packages
- Metaprogramming and Macros
- Multithreading and Parallel Computing
- Benchmarking & Performance Optimization
- Just-In-Time (JIT) Compilation with LLVM
- Broadcasting and Vectorized Operations
- Working with Dates and Time
- Random Number
- Linear Algebra and Matrix Operations
- Plotting with Plots.jl
- DataFrames.jl for Data Manipulation
1. Introduction to Julia
Julia is a high−level programming language designed for scientific and technical computing. Its program is used in various fields such as machine learning, data analysis, numerical computing, and distributed computing.
println("Hello, World!")
2. Comments
Comments are used to show the information about the code.
# single line comments #= multi-line comments =#
3. Julia REPL Shortcuts
The Julia REPL provides various shortcuts to improve user productivity. Below are a few commands −
- Ctrl + C − To interrupt the execution.
- Ctrl + D − To exit the REPL.
- Tab − For autocompletion of commands.
- ?command − To get help on a command.
# Help on println function ?println
4. Variable Assignment and Scope
In Julia, users can assign values to variables using the = operator. The global variables are defined under the scope, whereas local variables are defined inside the function. The local variable is also known as the actual variable.
# Global variable x = 10 y = 5 function example() # Local variable z = 20 println(x, y, z) end example()
5. Data Types
In Julia, we have various data types such as Int, Float, String, and more.
# Data types a = 10 # Integer b = 3.14 # Float c = "Hello" # String
6. Type Conversion
In Julia, we can perform the type conversion using functions like Int(), Float(), etc.
# Type conversion x = 3.14 # Converts float to integer y = Int(x)
7. Constants in Julia
In Julia, constant are defined by the keyword consts and their values cannot be reassigned.
# Constant definition const Pi = 3.14159
8. Operators
Julia supports various operators, including arithmetic, logical, and comparison operators.
Operators | Description | Example |
---|---|---|
Arithmetic Operators | Basic mathematical operations. | 'a + b', 'a - b', 'a * b', 'a / b', 'a % b' |
Relational Operators | Compare two values. | 'a == b', 'a != b', 'a > b', 'a = b', 'a |
Logical Operators | Combine conditional statements. | 'a && b', 'a || b', '!a' |
Bitwise Operators | Operate at the bit level. | 'a & b', 'a | b', 'a b', '~a', 'a > b' |
Assignment Operators | Assign values to variables. | 'a = b', 'a += b', 'a -= b', 'a *= b', 'a /= b', 'a %= b' |
9. Conditional Statements (if, else, elseif)
In Julia, conditional statements allow users to control the flow of the program based on conditions.
# Conditional statements if x > y println("x is greater than y") elseif x == y println("x is equal to y") else println("x is less than y") end
10. Loops (for and while)
Loops are used for the repeated execution of a block of code.
for i in 1:5 println(i) end
The implementation of while loop −
i = 1 while i <= 5 println(i) i += 1 end
11. Exception Handling (try, catch, finally)
In Julia, exception handling is the process to handle the error in a controlled way. This prevents the program from crashing.
# Exception handling try x = 10 / 0 catch e println("Error: ", e) finally println("Execution finished") end
12. Defining and Calling Functions
In Julia, functions are defined using the keyword "function" and can be called directly by the function name.
# Defining the greet function function fun(name) println("Hello, $name!") end # Calling the greet function fun("Julia")
13. Anonymous and Higher-Order Functions
The anonymous functions are defined without names, whereas higher-order functions accept other functions as arguments.
# Anonymous function f = x -> x^2 println(f(3)) # Higher-order function function apply_function(f, x) return f(x) end println(apply_function(f, 4))
14. Multiple Dispatch
The multiple dispatch in Julia means the method is determined by the types of all its arguments.
# Multiple dispatch function area(r::Int) return * r^2 end function area(l::Int, w::Int) return l * w end # Circle println(area(5)) # Rectangle println(area(4, 6))
15. Type Annotations
Type annotations are used to specify the types of function arguments and return values.
# Type annotations function add(x::Int, y::Int)::Int return x + y end println(add(2, 3))
16. Arrays
In Julia, arrays are defined by the ordered collections of elements. They can hold any type of data.
# Array arr = [1, 2, 3, 4] # Accessing the first element println(arr[1])
17. Matrices
Matrices are two−dimensional arrays that are particularly useful for linear algebra.
# Define two 2D matrices A = [1 2 3; 4 5 6; 7 8 9] B = [9 8 7; 6 5 4; 3 2 1] # Add the matrices C = A + B # Display the result println("Matrix A:") println(A) println("\nMatrix B:") println(B) println("\nSum of A and B:") println(C)
18. Indexing
In Julia, indexing is used to access elements from arrays or matrices.
# Indexing # Access second element println(arr[2]) # Access element in row 1, column 2 println(mat[1, 2])
19. Tuples
Tuples are defined by immutable ordered collections. They are useful for grouping different types of data.
# Tuple t = (1, "Hello", 3.14) # Access first element println(t[1])
20. Named Tuples
In Julia, named tuples are tuples where each element has a name.
# Named Tuple nt = (x = 100, y = 2) println(nt.x)
21. Dictionaries
In Julia, dictionaries are defined by key-value pairs that are used to store data.
# Dictionary d = Dict("a" => 10, "b" => 20) # Access value by key println(d["a"])
22. Sets
In Julia, sets are unordered collections of unique elements.
# Set s = Set([1, 2, 3, 4]) # Check if element exists println(3 in s)
23. String Manipulation
Below is the execution of string manipulation −
# String manipulation str = "Hello, Julia!" # Get length of string println(length(str)) println(string(str, " is awesome"))
24. String Interpolation
In Julia, string interpolation is the process of inserting the variable into the string.
# Define a variable name = "Julia" age = 25 # Use string interpolation to create a sentence result = "Hello, my name is $name and I am $age years old." # Display the result println(result)
25. Regular Expressions in Julia
In Julia, regular expressions are used for pattern matching.
# Regular expressions str = "TOM MIKE RAM SHYAM" r = r"\b\w+" matches = eachmatch(r, str) for m in matches println(m.match) end
26. File Handling
Julia provides functions for reading from and writing to files.
open("example.txt", "w") do f write(f, "Hello, World!") end
27. Working with CSV and JSON Files
In Julia, a CSV file is a text file that stores tabular data, where each line represents a row, and values are separated by commas. While JSON files are commonly used to store data as key-value pairs.
# Reading CSV using CSV data = CSV.File("data.csv") for row in data println(row) end
28. Creating Modules
Modules in Julia allow users to organize code into namespaces.
# Creating module module MyModule export my_function function my_function(x) return x^2 end end
29. Installing and Managing Packages
Julia is a package manager that allows users to easily install and manage packages.
# Installing a package using Pkg Pkg.add("Plots")
30. Metaprogramming and Macros
Metaprogramming allows users to write code for generating program, while macros provide a way to transform code before evaluation.
# Simple macro macro say_hello() return quote println("Hello, Tutorialspoint!") end end @say_hello
31. Multithreading and Parallel Computing
Julia has multithreading and parallel computing for faster execution.
# Multithreading Threads.@threads for i in 1:10 println(i) end
32. Benchmarking and Performance Optimization
The benchmarking defines the process to check the performance of the program. While performance optimization improves the efficiency of the program.
# Benchmarking using BenchmarkTools @btime sum(1:1000)
33. Just-In-Time (JIT) Compilation with LLVM
Julia uses LLVM for Just-In-Time (JIT) compilation, providing high-performance execution.
# JIT compilation function fib(n) if n <= 1 return n else return fib(n-1) + fib(n-2) end end println(fib(10))
34. Broadcasting and Vectorized Operations
Broadcasting allows for element-wise operations on arrays and matrices without explicitly writing loops.
# Example: Broadcasting a = [1, 2, 3] b = [4, 5, 6] println(a .+ b) # Element-wise addition
35. Working with Dates and Time
In Julia, we can use the package along with its built-in function to get the current time and date.
# Dates and Time using Dates today = today() println(today)
36. Random Number
In Julia, the function rand() is used to generate random numbers within a specified range.
# Random number generation using Random # Random integer between 1 and 10 println(rand(1:10))
37. Linear Algebra and Matrix Operations
Below is the implementation to perform the matrix operation −
# Example: Matrix operations A = [1 2; 3 4] B = [5 6; 7 8] # Matrix multiplication println(A * B)
38. Plotting with Plots.jl
Julia provides excellent plotting capabilities through the Plots.jl package.
# Plotting using Plots plot([1, 2, 3], [4, 5, 6])
39. DataFrames.jl for Data Manipulation
In Julia, DataFrames.jl is a powerful package for handling and manipulating data in Julia.
# DataFrames using DataFrames df = DataFrame(A = 1:3, B = 4:6) println(df)