Python built-in constants

Introduction

Python has a few built-in constants, only 6, True, False, None, notimplemented, ellipsis, __debug__.

one. True

1. True is a constant of type bool used to represent truth.

>>> truetrue>>> type (True)<class'bool' >

2. Any assignment to the constant true will throw a syntax error.

>>> True = 1syntaxerror:can't assign to keyword

two. False

1. False is a constant of type bool used to represent false values.

>>> falsefalse>>> type (False)<class'bool' >

2. Any assignment to the constant false will throw a syntax error.

>>> False = 0syntaxerror:can't assign to keyword

three. None

1. None means none, it is the unique value of Nonetype.

>>> none  # means none, no content output >>> type (None)<class' Nonetype '>

2. Any assignment to the constant none will throw a syntax error.

>>> None = 2syntaxerror:can't assign to keyword

3. For a function, if there is no return statement, it is equivalent to returning none.

def SayHello ():  # define function    print('Hello')     >>> sayHello () Hello>>> result = SayHello () Hello>>> result>>> type (Result)<class'nonetype' >

four. notimplemented

1. notimplemented is a constant of type notimplementedtype.

>>> notimplementednotimplemented>>> type (notimplemented)<class ' Notimplementedtype '>

2. Testing with the bool () function reveals that notimplemented is a truth value.

>>> bool (notimplemented) True

3. notimplemented is not a constant in absolute sense, because he can be assigned but does not throw a grammatical error, and we should not assign a value to it, otherwise it will affect the execution result of the program.

>>> bool (notimplemented) True>>> notimplemented = False>>> >>> bool (notimplemented) False

4. notimplemented is used for some binary special methods (such as __eq__, __lt__, etc.) as the return value, indicating that there is no implementation method, and Python will be intelligent when the results return notimplemented to exchange two parameters for another attempt.

>>>classA (object):def __init__(self,name,value): Self.name=name Self.value=valuedef __eq__(self,other):Print('Self :', Self.name,self.value)Print('Other :', Other.name,other.value)returnSelf.value = = Other.value#determines whether the value of 2 objects is equal>>> A1 = A ('Tom', 1)>>> A2 = A ('Jay', 1)>>> A1 = =A2self:tom1Other:jay1True

>>>classA (object):def __init__(self,name,value): Self.name=name Self.value=valuedef __eq__(self,other):Print('Self :', Self.name,self.value)Print('Other :', Other.name,other.value)returnnotimplemented>>> A1 = A ('Tom', 1)>>> A2 = A ('Jay', 1)>>> A1 = =A2self:tom1Other:jay1Self:jay1Other:tom1False

When you execute A1==A2 (that is, call __eq__ (A1,A2)) and return notimplemented, Python automatically swaps the parameters again to invoke __eq__ (A2,A1).

Five. Ellipsis

1. Ellipsis is a constant of type ellipsis, and it is ... is equivalent.

>>> ellipsisellipsis>>> type (ellipsis)<class'  Ellipsis'>>>> ... Ellipsis>>> ... = = Ellipsistrue

2. Testing with the bool () function reveals that ellipsis is a truth value.

>>> bool (ellipsis) True

3. Ellipsis is not a constant in absolute sense, because he can be assigned but does not throw a grammatical error, and we should not assign a value to it, otherwise it will affect the execution result of the program.

>>> bool (ellipsis) True>>> ellipsis = false>>> bool (ellipsis) False 

4. Ellipsis is used to represent the data structure of a loop.

>>> a = [1,2,3,4]>>> a.append (a)>>> a[1, 2, 3, 4, [...] >>> a[1, 2, 3, 4, [...] >>> Len (a)5>>> a[4[1, 2, 3, 4, [...]] >>>

Six. __debug__

1. __debug__ is a constant of type bool.

__debug__ True>>> type (__debug__)<class'bool' >

2. Any assignment to the constant __debug__ will throw a syntax error.

__debug__ = falsesyntaxerror:assignment to keyword

3. If Python is not started with the-o option, this constant is true, otherwise it is a false value.

Python built-in constants