Python Tutorial - Lambda Expression

Python Exercise Lists

For defining a simple function, Python also provides another method, which is to use the lambda expression described in this section.

Lambda expressions, also known as anonymous functions, are often used to represent functions that contain only one line of expression. If the body of a function has only one line of expression, the function can be replaced with a lambda expression.

The syntax of a lambda expression is as follows:

name = lambda [list]: expression

Among them, to define a lambda expression, you must use:

• lambda keyword;
• [list] as an optional parameter is equivalent to defining the function to be a specified parameter list;
• value is the name of the expression.

The syntax format is converted to the form of ordinary functions, as follows:

def name (list):
   return expression
name (list)

Obviously, using a normal method to define this function requires 3 lines of code, while using a lambda expression requires only 1 line.

For example, if you design a function that sums 2 numbers, use the ordinary function, which is defined as follows:

def add (x, y):
    return x + y
print (add (3,4))
           

The output is:

7

Since there is only 1 line of expression inside the add function in the above program, this function can be directly expressed by a lambda expression:

add = lambda x, y: x + y
print (add (3,4))
           

The output is:

7

A lambda expression can be understood as a shorthand version of a simple function (the body of which is a single-line expression). Lambda expressions have two advantages over functions:

• For single-line functions, using lambda expressions can save the process of defining functions and make the code more concise;
• For functions that do not require multiple reuse, lambda expressions can be released immediately after they are used up, improving the performance of program execution.

Python Eval and Exec Functions

The eval and exec functions are both built-in functions of Python. Since these two functions are similar in function and usage, they are introduced in this section.

The functions of the eval and exec functions are similar, and both can execute Python code as a string (the code is provided as a string), which is equivalent to a Python interpreter. The difference between the two is that eval returns results after execution, while exec returns no results (detailed examples will be given later in the article).

Python Eval and Exec Usage

The syntax of the eval function is:

eval (source, globals = None, locals = None, /) /p>

The syntax of the exec () function is as follows:

exec (source, globals = None, locals = None, /)

It can be seen that the syntax format of the two is the same except for the function name. The specific meaning of each parameter is as follows:

• expression: This parameter is a string representing the statement to be executed. This statement is restricted by the last two dictionary type parameters globals and locals. Only functions and variables in the scope of the globals dictionary and locals dictionary can be executed.
• globals: This parameter controls a global namespace, that is, expression can use functions in the global namespace. If the globals parameter is provided without a custom __builtins__, the system will copy the __builtins__ in the current environment to the globals provided by itself, and then calculate it; if the globals parameter is not provided, Use Python's global namespace.
• locals: This parameter controls a local namespace, similar to globals. When it overlaps or conflicts with globals, locals will prevail. If locals is not provided, it defaults to globals.

Note that __builtins__ is a Python built-in module. The int, str, and abs that are usually used are in this module. The print (dic ["__ builtins__"]) statement lets you see the value of __builtins__.

First, use the following example to demonstrate the effect of the parameter globals scope, and notice when it copies __builtins__ to the globals dictionary:

dic = {} #define a word
dic ['b'] = 3 #Add an element to dic with key b
print (dic.keys ()) #Print the key of dic first, there is an element b
exec ("a = 4", dic) #The statement executed by exec is followed by a scope dic
print (dic.keys ()) #exec, dic has one more key
           

The output is:

dict_keys(['b'])
dict_keys(['b', '__builtins__', 'a'])

The following code executes a = 4 code under the scope dic. It can be seen that the key in dic before exec () has only one b. After executing exec (), the system generates two new keys in dic, a and __builtins__. Among them, a is the variable generated by the execution statement, and the system places it in the specified scope dictionary; __builtins__ is a built-in key added by the system.

The usage of the locals parameter is very simple, for example:

a = 10
b = 20
c = 30
g = {'a': 6, 'b': 8} #define a dictionary
t = {'b': 100, 'c': 10} #define a dictionary
print (eval ('a + b + c', g, t)) #define a dictionary 116
           

The output is:

116

The Difference Between Exec () and Eval () in Python

As mentioned earlier, the difference is that eval () returns a result after execution, while exec() does not return a result after execution. for example:

a = 1
exec ("a = 2") #Equivalent to directly executing a = 2
print (a)
a = exec ("2 + 3") #Equivalent to executing 2 + 3 directly, but there is no return value, a should be None
print (a)
a = eval ('2 + 3') #Execute 2 + 3 and return the result to a
print (a)
           

The output is:

2
None
5