不幸的是，术语“动态类型”具有误导性。所有语言都是静态类型的，类型是表达式的属性(而不是一些人认为的值的属性)。然而，有些语言只有一种类型。这些被称为单一类型语言。这种语言的一个例子是无类型lambda演算。

在无类型lambda演算中，所有的项都是lambda项，对一个项执行的唯一操作是将它应用到另一个项。因此，所有的操作总是导致无限递归或lambda项，但永远不会发出错误信号。

However, were we to augment the untyped lambda calculus with primitive numbers and arithmetic operations, then we could perform nonsensical operations, such adding two lambda terms together: (λx.x) + (λy.y). One could argue that the only sane thing to do is to signal an error when this happens, but to be able to do this, each value has to be tagged with an indicator that indicates whether the term is a lambda term or a number. The addition operator will then check that indeed both arguments are tagged as numbers, and if they aren't, signal an error. Note that these tags are not types, because types are properties of programs, not of values produced by those programs.

这样做的单一类型语言称为动态类型语言。

JavaScript、Python和Ruby等语言都是单一类型的。同样，JavaScript中的typeof操作符和Python中的type函数的名称具有误导性;它们返回与操作数相关的标记，而不是操作数的类型。类似地，c++中的dynamic_cast和Java中的instanceof不做类型检查。

下面是一个对比Python(动态类型)和Go(静态类型)如何处理类型错误的例子:

def silly(a):
    if a > 0:
        print 'Hi'
    else:
        print 5 + '3'

Python在运行时执行类型检查，因此:

silly(2)

运行完全正常，并产生预期的输出Hi。只有当有问题的行被击中时才会引发错误:

silly(-1)

生产

不支持'int'和'str'的操作数类型

因为相关的行已经被执行了。

另一方面，Go在编译时进行类型检查:

package main

import ("fmt"
)

func silly(a int) {
    if (a > 0) {
        fmt.Println("Hi")
    } else {
        fmt.Println("3" + 5)
    }
}

func main() {
    silly(2)
}

上述文件将无法编译，并出现以下错误:

无效的操作:"3" + 5(不匹配的类型字符串和int)

甜蜜和简单的定义，但符合需求: 静态类型语言将类型绑定到整个作用域的变量(Seg: SCALA) 动态类型语言将类型绑定到变量引用的实际值。

http://en.wikipedia.org/wiki/Type_system

Static typing A programming language is said to use static typing when type checking is performed during compile-time as opposed to run-time. In static typing, types are associated with variables not values. Statically typed languages include Ada, C, C++, C#, JADE, Java, Fortran, Haskell, ML, Pascal, Perl (with respect to distinguishing scalars, arrays, hashes and subroutines) and Scala. Static typing is a limited form of program verification (see type safety): accordingly, it allows many type errors to be caught early in the development cycle. Static type checkers evaluate only the type information that can be determined at compile time, but are able to verify that the checked conditions hold for all possible executions of the program, which eliminates the need to repeat type checks every time the program is executed. Program execution may also be made more efficient (i.e. faster or taking reduced memory) by omitting runtime type checks and enabling other optimizations. Because they evaluate type information during compilation, and therefore lack type information that is only available at run-time, static type checkers are conservative. They will reject some programs that may be well-behaved at run-time, but that cannot be statically determined to be well-typed. For example, even if an expression always evaluates to true at run-time, a program containing the code if <complex test> then 42 else <type error> will be rejected as ill-typed, because a static analysis cannot determine that the else branch won't be taken.[1] The conservative behaviour of static type checkers is advantageous when evaluates to false infrequently: A static type checker can detect type errors in rarely used code paths. Without static type checking, even code coverage tests with 100% code coverage may be unable to find such type errors. Code coverage tests may fail to detect such type errors because the combination of all places where values are created and all places where a certain value is used must be taken into account. The most widely used statically typed languages are not formally type safe. They have "loopholes" in the programming language specification enabling programmers to write code that circumvents the verification performed by a static type checker and so address a wider range of problems. For example, Java and most C-style languages have type punning, and Haskell has such features as unsafePerformIO: such operations may be unsafe at runtime, in that they can cause unwanted behaviour due to incorrect typing of values when the program runs. Dynamic typing A programming language is said to be dynamically typed, or just 'dynamic', when the majority of its type checking is performed at run-time as opposed to at compile-time. In dynamic typing, types are associated with values not variables. Dynamically typed languages include Groovy, JavaScript, Lisp, Lua, Objective-C, Perl (with respect to user-defined types but not built-in types), PHP, Prolog, Python, Ruby, Smalltalk and Tcl. Compared to static typing, dynamic typing can be more flexible (e.g. by allowing programs to generate types and functionality based on run-time data), though at the expense of fewer a priori guarantees. This is because a dynamically typed language accepts and attempts to execute some programs which may be ruled as invalid by a static type checker. Dynamic typing may result in runtime type errors—that is, at runtime, a value may have an unexpected type, and an operation nonsensical for that type is applied. This operation may occur long after the place where the programming mistake was made—that is, the place where the wrong type of data passed into a place it should not have. This makes the bug difficult to locate. Dynamically typed language systems, compared to their statically typed cousins, make fewer "compile-time" checks on the source code (but will check, for example, that the program is syntactically correct). Run-time checks can potentially be more sophisticated, since they can use dynamic information as well as any information that was present during compilation. On the other hand, runtime checks only assert that conditions hold in a particular execution of the program, and these checks are repeated for every execution of the program. Development in dynamically typed languages is often supported by programming practices such as unit testing. Testing is a key practice in professional software development, and is particularly important in dynamically typed languages. In practice, the testing done to ensure correct program operation can detect a much wider range of errors than static type-checking, but conversely cannot search as comprehensively for the errors that both testing and static type checking are able to detect. Testing can be incorporated into the software build cycle, in which case it can be thought of as a "compile-time" check, in that the program user will not have to manually run such tests. References Pierce, Benjamin (2002). Types and Programming Languages. MIT Press. ISBN 0-262-16209-1.

简单地说:在静态类型语言中，变量的类型是静态的，这意味着一旦将变量设置为类型，就不能更改它。这是因为类型是与变量而不是它所引用的值相关联的。

例如，在Java中:

String str = "Hello";  // variable str statically typed as string
str = 5;               // would throw an error since str is
                       // supposed to be a string only

另一方面:在动态类型语言中，变量的类型是动态的，这意味着在你将变量设置为类型后，你可以更改它。这是因为输入与它假设的值相关，而不是变量本身。

例如，在Python中:

some_str = "Hello"  # variable some_str is linked to a string value
some_str = 5        # now it is linked to an integer value; perfectly OK

因此，最好将动态类型语言中的变量视为指向类型值的泛型指针。

总而言之，类型描述(或应该描述)语言中的变量，而不是语言本身。恕我直言，它本可以更好地用作带有静态类型变量的语言，而不是带有动态类型变量的语言。

静态类型语言通常是编译语言，因此，编译器检查类型(这很有意义，对吧?因为类型不允许稍后在运行时更改)。

动态类型语言通常是解释型的，因此类型检查(如果有的话)发生在使用它们时的运行时。这当然会带来一些性能损失，也是动态语言(例如python、ruby、php)伸缩性不如类型化语言(java、c#等)的原因之一。从另一个角度来看，静态类型语言的启动成本更高:通常会让你编写更多、更难的代码。但这在以后是有回报的。

好在双方都在借鉴对方的特点。类型语言融合了更多的动态特性，例如c#中的泛型和动态库，而动态语言则包含了更多的类型检查，例如python中的类型注释，或PHP的HACK变体，这些通常不是语言的核心，可按需使用。

在技术选择方面，任何一方都没有内在的优势。这只是一个偏好的问题，你想要更多的控制或灵活性。只要为工作选择合适的工具，并确保在考虑转换之前检查相反的可用工具。

在编程中，数据类型是一种分类，它告诉变量将持有什么类型的值，以及可以对这些值进行哪些数学、关系和逻辑操作而不会出错。

在每种编程语言中，为了尽量减少出错的机会，类型检查都是在程序执行之前或执行过程中进行的。根据类型检查的时间，编程语言有两种类型:静态类型语言和动态类型语言。

也取决于是否发生隐式类型转换，编程语言有两种类型:强类型语言和弱类型语言。

静态类型:

Type checking is done at compile time In source code, at the time of variable declaration, data type of that variable must be explicitly specified. Because if data type is specified in source code then at compile time that source code will be converted to machine code and type checking can happen Here data type is associated with variable like, int count. And this association is static or fixed If we try to change data type of an already declared variable (int count) by assigning a value of other data type (int count = "Hello") into it, then we will get error If we try to change data type by redeclaring an already declared variable (int count) using other data type (boolean count) then also we will get error

int count;         /* count is int type, association between data type
                      and variable is static or fixed */

count = 10;        // no error 
count = 'Hello';   // error 
boolean count;     // error 

由于类型检查和类型错误检测是在编译时完成的，这就是为什么在运行时不需要进一步的类型检查。因此，程序变得更加优化，结果在更快的执行 如果我们想要更严格的代码，那么选择这种类型的语言是更好的选择 例如:Java, C, c++， Go, Swift等。

动态类型:

Type checking is done at runtime In source code, at the time of variable declaration, no need to explicitly specify data type of that variable. Because during type checking at runtime, the language system determines variable type from data type of the assigned value to that variable Here data type is associated with the value assigned to the variable like, var foo = 10, 10 is a Number so now foo is of Number data type. But this association is dynamic or flexible we can easily change data type of an already declared variable (var foo = 10), by assigning a value of other data type (foo = "Hi") into it, no error we can easily change data type of an already declared variable (var foo = 10), by redeclaring it using value of other data type (var foo = true), no error

var foo;            // without assigned value, variable holds undefined data type 

var foo = 10;       // foo is Number type now, association between data 
                    // type and value is dynamic / flexible 
foo = 'Hi';         // foo is String type now, no error 
var foo = true;     // foo is Boolean type now, no error 

由于类型检查和类型错误检测是在运行时完成的，这就是为什么程序变得不那么优化，导致执行速度变慢。尽管如果它们实现了JIT编译器，这些类型的语言的执行速度会更快 如果我们想要轻松地编写和执行代码，那么这种类型的语言是更好的选择，但在这里我们可能会得到运行时错误 例如:Python, JavaScript, PHP, Ruby等。