【Java】Java流中的API

人不走空

🌈个人主页：人不走空

💖系列专栏：算法专题

⏰诗词歌赋：斯是陋室，惟吾德馨

🌈个人主页：人不走空

💖系列专栏：算法专题

⏰诗词歌赋：斯是陋室，惟吾德馨

概述：

关键概念：

使用案例：

摘要：

作者其他作品：

概述：

Java Stream API 有助于处理元素序列，提供过滤、映射和减少等操作。流可用于以声明方式执行操作，类似于对数据的类似 SQL 的操作

关键概念：

流：支持顺序和并行聚合操作的元素序列

中间操作：返回另一个流且延迟的操作（例如，filter、map）

码头运营：产生结果或副作用且不懒惰的操作（例如，collect、forEach）

示例场景：
假设我们有一个 Person 对象列表，并且我们希望使用 Stream API 对该列表执行各种操作

<span style="color:var(--syntax-text-color)"><span style="color:var(--syntax-text-color)"><code>public class Person {
    private String name;
    private int age;
    private String city;

    public Person(String name, int age, String city) {
        this.name = name;
        this.age = age;
        this.city = city;
    }

    public String getName() {
        return name;
    }

    public int getAge() {
        return age;
    }

    public String getCity() {
        return city;
    }

    @Override
    public String toString() {
        return "Person{name='" + name + "', age=" + age + ", city='" + city + "'}";
    }
}
</code></span></span>

使用案例：

滤波
映射
收集
减少
平面映射
排序
查找和匹配
统计学

滤波：过滤允许您选择与给定条件匹配的元素

<span style="color:var(--syntax-text-color)"><span style="color:var(--syntax-text-color)"><code>import java.util.Arrays;
import java.util.List;
import java.util.stream.Collectors;

public class Main {
    public static void main(String[] args) {
        List<Person> people = Arrays.asList(
            new Person("Alice", 30, "New York"),
            new Person("Bob", 20, "Los Angeles"),
            new Person("Charlie", 25, "New York"),
            new Person("David", 40, "Chicago")
        );

        // Filter people older than 25
        List<Person> filteredPeople = people.stream().filter(person -> person.getAge() > 25)                                       .collect(Collectors.toList());
        filteredPeople.forEach(System.out::println);
    }
}
</code></span></span>

映射：映射使用函数将每个元素转换为另一种形式

<span style="color:var(--syntax-text-color)"><span style="color:var(--syntax-text-color)"><code>public class Main {
    public static void main(String[] args) {
        List<Person> people = Arrays.asList(
            new Person("Alice", 30, "New York"),
            new Person("Bob", 20, "Los Angeles"),
            new Person("Charlie", 25, "New York"),
            new Person("David", 40, "Chicago")
        );
        // Get list of names
        List<String> names = people.stream()
                                   .map(Person::getName)
                                   .collect(Collectors.toList());
        names.forEach(System.out::println);
    }
}
</code></span></span>

收集：收集将流的元素收集到集合或其他数据结构中

<span style="color:var(--syntax-text-color)"><span style="color:var(--syntax-text-color)"><code>public class Main {
    public static void main(String[] args) {
        List<Person> people = Arrays.asList(
            new Person("Alice", 30, "New York"),
            new Person("Bob", 20, "Los Angeles"),
            new Person("Charlie", 25, "New York"),
            new Person("David", 40, "Chicago")
        );
        // Collect names into a set
        Set<String> uniqueCities = people.stream()
         .map(Person::getCity).collect(Collectors.toSet());
        uniqueCities.forEach(System.out::println);
    }
}
</code></span></span>

减少：Reducing 使用关联累积函数对流的元素执行 Reduction 并返回 Optional

<span style="color:var(--syntax-text-color)"><span style="color:var(--syntax-text-color)"><code>public class Main {
    public static void main(String[] args) {
         List<Person> people = Arrays.asList(
            new Person("Alice", 30, "New York"),
            new Person("Bob", 20, "Los Angeles"),
            new Person("Charlie", 25, "New York"),
            new Person("David", 40, "Chicago")
        );
        // Sum of ages
        int totalAge = people.stream()
                 .map(Person::getAge).reduce(0, Integer::sum);
        System.out.println("Total Age: " + totalAge);
    }
}
</code></span></span>

平面映射：FlatMapping 将嵌套结构展平到单个流中。

<span style="color:var(--syntax-text-color)"><span style="color:var(--syntax-text-color)"><code>public class Main {
    public static void main(String[] args) {
        List<List<String>> namesNested = Arrays.asList(
            Arrays.asList("John", "Doe"),
            Arrays.asList("Jane", "Smith"),
            Arrays.asList("Peter", "Parker")
        );

        List<String> namesFlat = namesNested.stream()
             .flatMap(List::stream).collect(Collectors.toList());
        namesFlat.forEach(System.out::println);
    }
}
</code></span></span>

排序：排序允许您对流的元素进行排序

<span style="color:var(--syntax-text-color)"><span style="color:var(--syntax-text-color)"><code>public class Main {
    public static void main(String[] args) {
        List<Person> people = Arrays.asList(
            new Person("Alice", 30, "New York"),
            new Person("Bob", 20, "Los Angeles"),
            new Person("Charlie", 25, "New York"),
            new Person("David", 40, "Chicago")
        );

        // Sort by age
        List<Person> sortedPeople = people.stream()
            .sorted(Comparator.comparing(Person::getAge))
            .collect(Collectors.toList());
        sortedPeople.forEach(System.out::println);
    }
}
</code></span></span>

查找和匹配：
查找和匹配操作检查流的元素，看看它们是否与给定的谓词匹配

<span style="color:var(--syntax-text-color)"><span style="color:var(--syntax-text-color)"><code>public class Main {
    public static void main(String[] args) {
        List<Person> people = Arrays.asList(
            new Person("Alice", 30, "New York"),
            new Person("Bob", 20, "Los Angeles"),
            new Person("Charlie", 25, "New York"),
            new Person("David", 40, "Chicago")
        );

        // Find any person living in New York
        Optional<Person> personInNY = people.stream()
               .filter(person -> "NewYork".equals(person.getCity())).findAny();

        personInNY.ifPresent(System.out::println);

        // Check if all people are older than 18
        boolean allAdults = people.stream()
          .allMatch(person -> person.getAge() > 18);

        System.out.println("All adults: " + allAdults);
    }
}

</code></span></span>

统计学：Stream API 还可用于执行各种统计操作，例如计数、平均等。

<span style="color:var(--syntax-text-color)"><span style="color:var(--syntax-text-color)"><code>public class Main {
    public static void main(String[] args) {
       List<Person> people = Arrays.asList(
            new Person("Alice", 30, "New York"),
            new Person("Bob", 20, "Los Angeles"),
            new Person("Charlie", 25, "New York"),
            new Person("David", 40, "Chicago")
        );

        // Count number of people
        long count = people.stream().count();
        System.out.println("Number of people: " + count);

        // Calculate average age
        Double averageAge = people.stream()
        .collect(Collectors.averagingInt(Person::getAge));

        System.out.println("Average Age: " + averageAge);
    }
}

</code></span></span>

实际示例：
这是一个使用上述几个功能的综合示例：

<span style="color:var(--syntax-text-color)"><span style="color:var(--syntax-text-color)"><code>import java.util.*;
import java.util.stream.*;

public class Main {
    public static void main(String[] args) {
        List<Person> people = Arrays.asList(
            new Person("Alice", 30, "New York"),
            new Person("Bob", 20, "Los Angeles"),
            new Person("Charlie", 25, "New York"),
            new Person("David", 40, "Chicago")
        );

        // Filter, map, sort, and collect
        List<String> names = people.stream()
                                   .filter(person -> person.getAge() > 20)
                                   .map(Person::getName)
                                   .sorted()
                                   .collect(Collectors.toList());

        names.forEach(System.out::println);

        // Find the oldest person
        Optional<Person> oldestPerson = people.stream()
                                              .max(Comparator.comparing(Person::getAge));

        oldestPerson.ifPresent(person -> System.out.println("Oldest Person: " + person));

        // Group by city
        Map<String, List<Person>> peopleByCity = people.stream()
                                                       .collect(Collectors.groupingBy(Person::getCity));

        peopleByCity.forEach((city, peopleInCity) -> {
            System.out.println("People in " + city + ": " + peopleInCity);
        });

        // Calculate total and average age
        IntSummaryStatistics ageStatistics = people.stream()
                                                   .collect(Collectors.summarizingInt(Person::getAge));

        System.out.println("Total Age: " + ageStatistics.getSum());
        System.out.println("Average Age: " + ageStatistics.getAverage());
    }
}

</code></span></span>