The reason is that Scala is not exactly Java; it’s not even near Java. Although it uses the JVM (Java Virtual Machine) Compiler, it is only partly similar to Java. One can say that Java is the Grand Father of
def speed(destination: Float, time: Float): Float { destination / time } println(speed(100, 10)) println(speed(time = 10, destination = 100)) 1. 2. 3. 4. 5. 6. 7.可变参数变参数(可传入任意多个相同类型的参数) java中 int… numbers JDK5+:可变参数def sum(number: Int*) = { va...
在Scala中for循环比Java的有更高级的形态,可以在for表达式中定义生成器、定义 变量、定义过滤器: 生成器for…yield:for循环迭代会将列表中的所有元素进行遍历,yield会产生一个值 ,这个值被循环记录下来,当循环结束 后,会返回所有yield的值组成的集合,返回集合的类型与被遍历的集合类型是一致。 caseclassPerson(name:...
def speed(destination: Float, time: Float): Float { destination / time } println(speed(100, 10)) println(speed(time = 10, destination = 100)) 可变参数变参数(可传入任意多个相同类型的参数) java中 int… numbers JDK5+:可变参数def sum(number: Int*) = { var result = 0 for(num <- ...
这里aWeirdValue 的值为 Unit,类型于 Java 中的 void。在 Scala 中,aVariable = 3 这种赋值并返回 Unit 的“表达式”被称为副作用( side effects ),println,while 都是。 在Scala 中,代码块返回最后一行的表达式: val aCodeBlock = { val y = 2 val z = y + 1 if (z > 2) "hello" else "wo...
defspeed(destination:Float, time:Float):Float{ destination / time }println(speed(100,10))println(speed(time =10, destination =100)) 可变参数 变参数(可传入任意多个相同类型的参数) java中 int... numbers JDK5+:可变参数 def sum(number: Int*) = { ...
2. Slow Compilation Speed Another disadvantage of Scala is that it takes a longer time to compile complex codes. This results in slow compilation speed when compared to what is observed in the case of Java or Kotlin. 3. Issues with Binary Compilation It is not binary compatible with a few...
To be able to guarantee a higher download speed, you have to shield your program from common in addition to serious damages that cause the data reduction. If you are not able to protect sensitive and confidential information, you’ll lose the company goal in long term. Different new ...
$ curl localhost:9000/simple-form | awk '!/^[[:space:]]*$/' % Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed 100 732 100 732 0 0 75046 0 --:--:-- --:--:-- --:--:-- 81333 i Numeric ...
Deep Learning (Python, C/C++, Java, Scala). Contribute to fancyspeed/DeepLearning development by creating an account on GitHub.