As a programmer, demonstrating coding skills can not only improve programming efficiency and code quality, but also allow peers to recognize and respect your technical level. Here are some cool codes I personally think are written:
functional programming
Functional programming is known as one of the most popular paradigms in the field of modern programming. Based on ideas such as recursion and higher-order functions, it implements a programming method based on function composition. Functional programming focuses on modularity and the ability to abstract logic, which can be of great benefit in eliminating side effects, avoiding shared state, better handling exceptions, and more.
Example: In functional programming, using the Haskell language is a great way to demonstrate functional programming capabilities. Below is a code that calculates the Fibonacci sequence, using pattern matching and recursion to calculate the Fibonacci sequence without introducing any mutable state or side effects.
fib :: Int -> Int
fib 0 = 0
fib 1 = 1
fib n = fib (n-1) + fib (n-2)
reactive programming
Reactive programming is another popular programming idea in recent years. It is based on concepts such as observer mode, message passing mechanism, and data flow. It regards an application as a "reactor" composed of a set of input and output streams. Through similar Stream operations are connected in a pipeline-based way, thus simplifying and accelerating system development.
Example: In terms of reactive programming, the widespread use of ReactiveX is typical of this paradigm. In JavaScript, the following code uses RxJS to implement an observer pattern to continuously listen to user input and respond to it, instantiate a stream through RxJS, convert event stream data into streaming, and handle some advanced operations, such as preventing Shaking, deduplication, etc., to achieve a more flexible and intuitive interaction mode
var inputElement = document.getElementById('input');
Rx.Observable.fromEvent(inputElement, 'keyup')
.map(event => event.target.value)
.debounceTime(500)
.distinctUntilChanged()
.subscribe(searchTerm => {
// 发送请求并显示结果
});Currying
Currying is a functional programming technique that transforms a function that takes multiple arguments into a process where each argument returns a separate function. This method can make one function into multiple functions for processing, and can call required functions more flexibly and conveniently.
Example: In Python, currying can also be used to increase code readability and conciseness. For example, the following code uses the decorator function to curry the add function, and fundamentally changes the common Python function calling method through Currying and decorator functions, so as to achieve more efficient and elegant programming effects.
def curry(f):
def curried(*args, **kwargs):
if len(args) + len(kwargs) >= f.__code__.co_argcount:
return f(*args, **kwargs)
else:
return (lambda x: curried(*(args + (x,)), **kwargs))
return curried
@curry
def add(x, y):
return x + y
print(add(4)(5)) # 输出 9
Advanced Generics
It is universal and practical to use generics for code design in Java, C# and other languages, but if you can master the advanced features of generics (such as: generic constraints, covariance/inversion, etc.), you can make the code more Elegant and concise and reduce the occurrence rate of logic errors.
Example: In Java, a representative generics library is Google Guava. For example, in the following code, we will use the ImmutableSortedSet type and Ordering calculation method provided by Guava to implement a simple program for sorting a list of numbers. By introducing the type and calculation method in the Guava library, we can reduce manual state and variables Maintained for more decent programming effects.
List<Integer> unorderedIntegers = Arrays.asList(1, 3, 2);
ImmutableSortedSet<Integer> orderedIntegers = ImmutableSortedSet.copyOf(unorderedIntegers, Ordering.natural());
System.out.println(orderedIntegers); // 输出 [1, 2, 3]
Novel Algorithm Ideas
As a programmer, if you can come up with a novel and subtle algorithm when solving a difficult problem, and the algorithm is enough to generate great value to users, it will make you stand out among many programmers. Therefore, reading papers, strengthening knowledge in different fields, and brushing LeetCode question banks are all good ways to improve algorithmic thinking.
In terms of novel algorithms, AlphaZero represents a lot of work in the field of AI by research teams. It is an algorithm for evaluating and judging players of board games based on self-learning, which can achieve a game level beyond the professional level without manually setting value rules.
Generally speaking, the above technologies and techniques all have the effect of showing off skills, but they also require the ability to pursue precision and excellence in coding and flexible code programming thinking. Although they may also become important programming paradigms in the future, we still need to study hard and practice before we can succeed.