Why Learn Rust in 2025?
According to developer survey data, Rust has entered the top 12 most widely used programming languages in the IT industry. The data shows that 10%-13% of software developers use Rust in their daily work. Notably, among those who are just starting to learn programming, this percentage even reaches 11%-18%. The number of Rust learners constitutes a strong driving force for its development.
Over the past six years, the usage rate of Rust has continued to rise, showing no signs of slowing down:
Notice the “Likely to adopt” column: Rust is the only language that has broken into double digits on this metric!
From the perspective of developer preference, Rust is far ahead. The Stack Overflow developer survey shows that Rust has been one of the most loved languages for several years, for a full eight years? Nine years? No one remembers clearly!
Those who are already using Rust often state that they would not easily switch back to other languages.
Developers also greatly appreciate Rust’s wide application across multiple technical fields and industries. The latest survey points out the following as some major application scenarios:
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Backend services and other server-side applications
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Cloud computing-related applications, services, and infrastructure
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Distributed systems
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Computer networks
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Security field
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Embedded development
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Game development
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Web front-end (including WebAssembly)
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And many other fields
Of course, Rust is not the only programming language choice in these fields; each field has its own competitors. Rust is often compared with C++ or Go because they overlap in many application scenarios, but each has its strengths and weaknesses in terms of memory safety guarantees, performance promises, richness of toolchains and libraries, language complexity, and industry acceptance. While Rust may be slightly inferior in the latter three dimensions, it can almost match C++ in performance while making it easier to avoid memory access errors, thus facilitating the creation of error-free applications.
Understanding Rust’s Core Concepts
Let’s take a macro view of Rust and its key features. Rust is neither an object-oriented language nor a purely functional language. It does not have the concept of classes and does not directly support object-oriented design patterns. It can operate on functions as first-class citizens to some extent, but this flexibility is far less than that of pure functional languages like Haskell or OCaml.
Writing Code with Functions, Values, and Types
Rust programs are organized into modules, which contain several functions. Functions handle various values, and these values must have explicit types at compile time. Rust provides basic types and composite types (such as arrays and structs), and its standard library offers a rich set of collection types. Additionally, Rust supports generic types, allowing developers to write generic code that does not depend on specific types.
Rust introduces the concept of “traits,” which is a collection of methods (i.e., functions) that can be implemented for specific types. Traits allow Rust to achieve a level of abstraction similar to inheritance and polymorphism in object-oriented languages.
Memory Management Mechanism
Rust’s memory management is based on the principle that: the compiler must clearly know when memory is allocated, how it is accessed, and when it is no longer needed. This design allows the compiler to automatically insert instructions to free memory when generating code, thus avoiding many common issues found in other languages. This approach differs from the runtime garbage collection mechanisms of Java, Python, JavaScript, or C#, which rely on runtime detection of unused memory segments for cleanup.
By not requiring runtime garbage collection, Rust avoids this overhead, achieving a balance between memory safety and high performance.
To infer memory access behavior, Rust sets strict rules for memory operations:
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Each piece of memory can only be owned by one variable — this is known as the “ownership model.”
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When modifying the contents of a piece of memory, exclusive access to that memory must be held (reading can be shared).
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Rust allows the creation of mutable or immutable references (i.e., borrowing memory), but correctness is ensured through a “borrow checker” (e.g., prohibiting multiple mutable references from existing simultaneously).
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The compiler calculates the “lifetime” of each variable, strictly tracking the entire process from creation to destruction.
Sometimes, the compiler’s requirements may seem overly strict, which is a common point of confusion for beginners. Sometimes, logically correct code may fail to pass the compiler’s checks.
To make these concepts easier to understand, let’s look at how this Python code is expressed in Rust:
def print_list(numbers):
for number in numbers:
print(number)
This Python code looks simple: it iterates over a list and prints each element. However, in Rust, such operations are constrained by ownership and borrowing mechanisms. In the following content, we will guide you step by step to understand the principles behind these rules and how to write code that complies with Rust’s specifications while accomplishing the task. The Python code is as follows:
def print_list(numbers):
for number in numbers:
print(str(number) + " ", end="")
print()
def add_one(numbers):
numbers.append(1)
def main():
numbers = [1, 1, 1]
print_list(numbers)
add_one(numbers)
print_list(numbers)
if __name__ == '__main__':
main()
Let’s first look at this Python code. It creates a list with three elements, prints it once; then adds a new element and prints it again. The entire process does not mention type or memory management issues. Python automatically handles memory allocation and deallocation, and we only need to focus on the logical implementation.
Next is the equivalent code in Rust:
fn print_vec(numbers: &Vec<i32>) {
for number in numbers {
print!("{} ", number);
}
println!();
}
fn add_one(numbers: &mut Vec<i32>) {
numbers.push(1);
}
fn main() {
let mut numbers = vec![1, 1, 1];
print_vec(&numbers);
add_one(&mut numbers);
print_vec(&numbers);
}
This Rust code not only differs in syntax but also has significant differences in type and memory management. For example, <span>print_vec</span> receives a read-only reference (<span>&Vec<i32></span>), while <span>add_one</span> receives a mutable reference (<span>&mut Vec<i32></span>). Rust does not allow arbitrary data modification by default; write permissions must be explicitly declared.
Ownership and Borrowing Mechanism
Rust has a core concept called “ownership,” which determines who is responsible for releasing memory. In this example, the <span>numbers</span> variable owns the memory of this vector. When we pass a reference, we are merely “borrowing” that memory without transferring ownership.
If we try to write this:
fn add_one_incorrect(mut numbers: Vec<i32>) {
numbers.push(1);
}
Then the problem arises — the function <span>add_one_incorrect</span> takes ownership of <span>numbers</span>. After the call, the original variable can no longer be used. This leads to an error when calling <span>print_vec</span> later, as the memory no longer belongs to <span>numbers</span>.
This mechanism may seem strict, but it is designed to prevent common memory errors, such as dangling pointers and data races. The Rust compiler checks these rules at compile time to ensure program safety and reliability.