用shell写一个100次运行strem.o并记录次数的脚本

可以这样写：

#!/bin/bash
count=0
while [ $count -lt 100 ]
do
    ./strem.o
    count=$((count+1))
done
echo "strem.o运行了 $count 次"

这个脚本使用了一个循环结构，执行了100次 `./strem.o` 命令，并计数器 `count` 递增。循环结束后，输出运行次数。

相关问题

strem.anyMatch

`stream.filter()` 是一个用于过滤流（Stream）中元素的操作。

在 Java 8 及以上版本中，`stream.filter()` 方法接受一个 Predicate（谓词）作为参数，并返回一个新的流，其中包含满足谓词条件的元素。

以下是一个示例，演示如何使用 `stream.filter()` 方法过滤出大于等于5的元素：

List<Integer> numbers = Arrays.asList(1, 2, 3, 4, 5, 6, 7, 8, 9, 10);

List<Integer> filteredNumbers = numbers.stream()
                                        .filter(n -> n >= 5)
                                        .collect(Collectors.toList());

System.out.println(filteredNumbers); // 输出 [5, 6,

javade strem

As an AI language model, I cannot provide a full explanation of Java Stream without any context. However, I can give you a brief overview of Java Stream.

Java Stream is a Java 8 feature that allows developers to process collections of data in a functional programming style. It provides a way to perform operations such as filtering, mapping, and reducing on a collection of data in a concise and readable way.

Using Java Stream, developers can perform operations on large data sets without having to manually iterate over each element. This results in cleaner and more maintainable code.

Java Stream is based on the concept of a pipeline, which consists of a source, zero or more intermediate operations, and a terminal operation. The source can be any collection or data structure, and the intermediate operations can be filter, map, flatMap, sorted, and more. The terminal operation is the final step in the pipeline, and it produces a result or a side effect.

Overall, Java Stream provides a powerful tool for processing collections of data in a functional way.