• 05 Python 3 Variable Types


    Variables are nothing but reserved memory locations to store values. It means that when you create a variable, you reserve some space in the memory.

    Based on the data type of a variable, the interpreter allocates memory and decides what can be stored in the reserved memory. Therefore, by assigning different data types to the variables, you can store integers, decimals or characters in these variables.

    Assigning Values to Variables

    Python variables do not need explicit declaration to reserve memory space. The declaration happens automatically when you assign a value to a variable. The equal sign (=) is used to assign values to variables.

    The operand to the left of the = operator is the name of the variable and the operand to the right of the = operator is the value stored in the variable. For example −

     
    #!/usr/bin/python3
    
    counter = 100          # An integer assignment
    miles   = 1000.0       # A floating point
    name    = "John"       # A string
    
    print (counter)
    print (miles)
    print (name)

    Here, 100, 1000.0 and "John" are the values assigned to counter, miles, and name variables, respectively. This produces the following result −

    100
    1000.0
    John
    

    Multiple Assignment

    Python allows you to assign a single value to several variables simultaneously.

    For example −

    a = b = c = 1
    

    Here, an integer object is created with the value 1, and all the three variables are assigned to the same memory location. You can also assign multiple objects to multiple variables. For example −

    a, b, c = 1, 2, "john"
    

    Here, two integer objects with values 1 and 2 are assigned to the variables a and b respectively, and one string object with the value "john" is assigned to the variable c.

    Standard Data Types

    The data stored in memory can be of many types. For example, a person's age is stored as a numeric value and his or her address is stored as alphanumeric characters. Python has various standard data types that are used to define the operations possible on them and the storage method for each of them.

    Python has five standard data types −

    • Numbers
    • String
    • List
    • Tuple
    • Dictionary

    Python Numbers

    Number data types store numeric values. Number objects are created when you assign a value to them. For example −

    var1 = 1
    var2 = 10
    

    You can also delete the reference to a number object by using the del statement. The syntax of the del statement is −

    del var1[,var2[,var3[....,varN]]]]
    

    You can delete a single object or multiple objects by using the del statement.

    For example −

    del var
    del var_a, var_b
    

    Python supports three different numerical types −

    • int (signed integers)
    • float (floating point real values)
    • complex (complex numbers)

    All integers in Python3 are represented as long integers. Hence, there is no separate number type as long.

    Examples

    Here are some examples of numbers −

    intfloatcomplex
    10 0.0 3.14j
    100 15.20 45.j
    -786 -21.9 9.322e-36j
    080 32.3+e18 .876j
    -0490 -90. -.6545+0J
    -0x260 -32.54e100 3e+26J
    0x69 70.2-E12 4.53e-7j

    A complex number consists of an ordered pair of real floating-point numbers denoted by x + yj, where x and y are real numbers and j is the imaginary unit.

    Python Strings

    Strings in Python are identified as a contiguous set of characters represented in the quotation marks. Python allows either pair of single or double quotes. Subsets of strings can be taken using the slice operator ([ ] and [:] ) with indexes starting at 0 in the beginning of the string and working their way from -1 to the end.

    The plus (+) sign is the string concatenation operator and the asterisk (*) is the repetition operator. For example −

     
    #!/usr/bin/python3
    
    str = 'Hello World!'
    
    print (str)          # Prints complete string
    print (str[0])       # Prints first character of the string
    print (str[2:5])     # Prints characters starting from 3rd to 5th
    print (str[2:])      # Prints string starting from 3rd character
    print (str * 2)      # Prints string two times
    print (str + "TEST") # Prints concatenated string

    This will produce the following result −

    Hello World!
    H
    llo
    llo World!
    Hello World!Hello World!
    Hello World!TEST
    

    Python Lists

    Lists are the most versatile of Python's compound data types. A list contains items separated by commas and enclosed within square brackets ([]). To some extent, lists are similar to arrays in C. One of the differences between them is that all the items belonging to a list can be of different data type.

    The values stored in a list can be accessed using the slice operator ([ ] and [:]) with indexes starting at 0 in the beginning of the list and working their way to end -1. The plus (+) sign is the list concatenation operator, and the asterisk (*) is the repetition operator. For example −

     
    #!/usr/bin/python3
    
    list = [ 'abcd', 786 , 2.23, 'john', 70.2 ]
    tinylist = [123, 'john']
    
    print (list)          # Prints complete list
    print (list[0])       # Prints first element of the list
    print (list[1:3])     # Prints elements starting from 2nd till 3rd 
    print (list[2:])      # Prints elements starting from 3rd element
    print (tinylist * 2)  # Prints list two times
    print (list + tinylist) # Prints concatenated lists

    This produces the following result −

    ['abcd', 786, 2.23, 'john', 70.200000000000003]
    abcd
    [786, 2.23]
    [2.23, 'john', 70.200000000000003]
    [123, 'john', 123, 'john']
    ['abcd', 786, 2.23, 'john', 70.200000000000003, 123, 'john']
    

    Python Tuples

    A tuple is another sequence data type that is similar to the list. A tuple consists of a number of values separated by commas. Unlike lists, however, tuples are enclosed within parenthesis.

    The main difference between lists and tuples are − Lists are enclosed in brackets ( [ ] ) and their elements and size can be changed, while tuples are enclosed in parentheses ( ( ) ) and cannot be updated. Tuples can be thought of as read-only lists. For example −

     
    #!/usr/bin/python3
    
    tuple = ( 'abcd', 786 , 2.23, 'john', 70.2  )
    tinytuple = (123, 'john')
    
    print (tuple)           # Prints complete tuple
    print (tuple[0])        # Prints first element of the tuple
    print (tuple[1:3])      # Prints elements starting from 2nd till 3rd 
    print (tuple[2:])       # Prints elements starting from 3rd element
    print (tinytuple * 2)   # Prints tuple two times
    print (tuple + tinytuple) # Prints concatenated tuple

    This produces the following result −

    ('abcd', 786, 2.23, 'john', 70.200000000000003)
    abcd
    (786, 2.23)
    (2.23, 'john', 70.200000000000003)
    (123, 'john', 123, 'john')
    ('abcd', 786, 2.23, 'john', 70.200000000000003, 123, 'john')
    

    The following code is invalid with tuple, because we attempted to update a tuple, which is not allowed. Similar case is possible with lists −

    #!/usr/bin/python3
    
    tuple = ( 'abcd', 786 , 2.23, 'john', 70.2  )
    list = [ 'abcd', 786 , 2.23, 'john', 70.2  ]
    tuple[2] = 1000    # Invalid syntax with tuple
    list[2] = 1000     # Valid syntax with list

    Python Dictionary

    Python's dictionaries are kind of hash-table type. They work like associative arrays or hashes found in Perl and consist of key-value pairs. A dictionary key can be almost any Python type, but are usually numbers or strings. Values, on the other hand, can be any arbitrary Python object.

    Dictionaries are enclosed by curly braces ({ }) and values can be assigned and accessed using square braces ([]). For example −

     
    #!/usr/bin/python3
    
    dict = {}
    dict['one'] = "This is one"
    dict[2]     = "This is two"
    
    tinydict = {'name': 'john','code':6734, 'dept': 'sales'}
    
    print (dict['one'])       # Prints value for 'one' key
    print (dict[2])           # Prints value for 2 key
    print (tinydict)          # Prints complete dictionary
    print (tinydict.keys())   # Prints all the keys
    print (tinydict.values()) # Prints all the values

    This produces the following result −

    This is one
    This is two
    {'name': 'john', 'dept': 'sales', 'code': 6734}
    dict_keys(['name', 'dept', 'code'])
    dict_values(['john', 'sales', 6734])
    

    Dictionaries have no concept of order among the elements. It is incorrect to say that the elements are "out of order"; they are simply unordered.

    Data Type Conversion

    Sometimes, you may need to perform conversions between the built-in types. To convert between types, you simply use the type-names as a function.

    There are several built-in functions to perform conversion from one data type to another. These functions return a new object representing the converted value.

    Sr.No.Function & Description
    1

    int(x [,base])

    Converts x to an integer. The base specifies the base if x is a string.

    2

    float(x)

    Converts x to a floating-point number.

    3

    complex(real [,imag])

    Creates a complex number.

    4

    str(x)

    Converts object x to a string representation.

    5

    repr(x)

    Converts object x to an expression string.

    6

    eval(str)

    Evaluates a string and returns an object.

    7

    tuple(s)

    Converts s to a tuple.

    8

    list(s)

    Converts s to a list.

    9

    set(s)

    Converts s to a set.

    10

    dict(d)

    Creates a dictionary. d must be a sequence of (key,value) tuples.

    11

    frozenset(s)

    Converts s to a frozen set.

    12

    chr(x)

    Converts an integer to a character.

    13

    unichr(x)

    Converts an integer to a Unicode character.

    14

    ord(x)

    Converts a single character to its integer value.

    15

    hex(x)

    Converts an integer to a hexadecimal string.

    16

    oct(x)

    Converts an integer to an octal string.

     

    From

    https://www.tutorialspoint.com/python3/python_variable_types.htm

  • 相关阅读:
    IP查询网和traceroute找到的网络出口不一致的原因
    [转载] 深入理解VMware虚拟机网络通信原理
    https工作流程
    HTTP1.1协议-RFC2616-中文版
    条件变量调用Signal的时候是否需要持有mutex
    HTTP Get一定是幂等的吗,统计访问量的时候呢?
    unix网络编程
    MySQL-SQL基础-DCL
    MySQL-SQL基础-查询1
    MySQL-SQL基础-子查询
  • 原文地址:https://www.cnblogs.com/emanlee/p/15851124.html
Copyright © 2020-2023  润新知