Detailed description of functions in python

Fibonacci Sequence

>>> fibs
[0, 1]>>> n=input('How many Fibonacci numbers do your what?')
How many Fibonacci numbers do your what?10
>>> for n in range(n-2):
    fibs.append(fibs[-2]+fibs[-1])    
>>> fibs
[0, 1, 1, 2, 3, 5, 8, 13, 21, 34]

Note: The built-in callable function can be used to determine whether the function can be called

def Define function

>>> def hello(name):
    print "Hello"+name

    
>>> hello('world')
Helloworld

Use function to write Fibonacci sequence

>>> def fibs(num):
    s=[0,1]
    for i in range(num-2):
        s.append(s[-2]+s[-1])

        
>>> fibs(10)

Note: The return statement returns the value from the function

Function description: If you document the function so that others can understand it, you can add comments ( #beginning). Another way is to write the string directly.

>>> def square(x):
    'Calculates the square of the number x.'
    return x*x

>>> square.__doc__
'Calculates the square of the number x.'

The built-in help function can get information about the function, including its documentation string

>>> help(square)
Help on function square in module __main__:

square(x)
    Calculates the square of the number x.

Assigning new values ​​to parameters within a function does not change the value of external variables:

>>> def try_to_change(n):
    n='Mr,Gumby'

    
>>> name='Mrs,Entity'
>>> try_to_change(name)
>>> name
'Mrs,Entity'

Strings (as well as numbers and tuples) It is immutable, that is, it cannot be modified. If the changeable data structure (list or dictionary) is modified, the parameters will be modified

>>> n=['Bob','Alen']
>>> def change(m):
    m[0]='Sandy'

    
>>> change(n[:])
>>> n
['Bob', 'Alen']
>>> change(n)
>>> n
['Sandy', 'Alen']

Keyword parameters and default values

>>> def hello(name,greeting='Hello',punctuation='!'):
    print '%s,%s%s' % (greeting,name,punctuation)

    
>>> hello(name='Nsds')
Hello,Nsds!
>>> hello(name='Nsds',greeting='Hi')
Hi,Nsds!

Collect parameters

Return tuple:

>>> def print_params(*params):
    print params

    
>>> print_params('Testing') #返回元组
('Testing',)
>>> print_params(1,2,3)
(1, 2, 3)
>>> def print_params_2(title,*params):
    print title
    print params

    
>>> print_params_2('Params:',1,2,3)
Params:
(1, 2, 3)

Return dictionary

>>> def print_params_3(**params):
    print params

    
>>> print_params_3(x=1,y=2,z=3)
{'y': 2, 'x': 1, 'z': 3}
>>> def print_params_4(x,y,z=3,*pospar,**keypar):
    print x,y,z
    print pospar
    print keypar

    
>>> print_params_4(1,2,3,5,6,7,foo=1,bar=2)
2 3
(5, 6, 7)
{'foo': 1, 'bar': 2}
>>> print_params_4(1,2)
2 3
()
{}

## Call tuple, dictionary

>>> def add(x,y):return x+y

>>> params=(1,2)
>>> add(*params)
>>> def with_stars(**kwds):
    print kwds['name'],'is',kwds['age'],'years old']
>>> def without_starts(kwds):
    print kwds['name'],'is',kwds['age'],'years old'
>>> args={'name':'Nsds','age':24}
>>> with_stars(**args)
Nsds is 24 years old
>>> without_starts(args)
Nsds is 24 years old
>>> add(2,args['age'])

The asterisk is only useful when defining a function (allowing an indefinite number of parameters) or calling ("splitting" a dictionary or sequence)

>>> def foo(x,y,z,m=0,n=0):
    print x,y,z,m,n

    
>>> def call_foo(*args,**kwds):
    print "Calling foo!"
    foo(*args,**kwds)

>>> d=(1,3,4)
>>> f={'m':'Hi','n':'Hello'}
>>> foo(*d,**f)
3 4 Hi Hello
>>> call_foo(*d,**f)
Calling foo!
3 4 Hi Hello

A few examples

>>> def story(**kwds):
    return 'Once upon a time,there was a' \
           '%(job)s called %(name)s.' % kwds

>>> def power(x,y,*others):
    if others:
        print 'Received redundant parameters:',others
    return pow(x,y)

>>> def interval(start,stop=None,step=1):
    if stop is None:
        start,stop=0,start  #start=0,stop=start
    result=[]
    i=start
    while i<stop:
        result.append(i)
        i+=step
    return result

>>> print story(job=&#39;king&#39;,name=&#39;Gumby&#39;)
Once upon a time,there was aking called Gumby.
>>> print story(name=&#39;Sir Robin&#39;,job=&#39;brave knight&#39;)
Once upon a time,there was abrave knight called Sir Robin.
>>> params={&#39;job&#39;:&#39;language&#39;,&#39;name&#39;:&#39;Python&#39;}
>>> print story(**params)
Once upon a time,there was alanguage called Python.
>>> del params[&#39;job&#39;]
>>> print story(job=&#39;store of genius&#39;,**params)
Once upon a time,there was astore of genius called Python.
>>> power(2,3)
>>> power(y=3,x=2)
>>> params=(5,)*2
>>> power(*params)
>>> power(3,3,&#39;Helld,world&#39;)
Received redundant parameters: (&#39;Helld,world&#39;,)
>>> interval(10)
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
>>> interval(1,5)
[1, 2, 3, 4]
>>> power(*interval(3,7))
Received redundant parameters: (5, 6)

Modify global variables

>>> def f():
    global x
    x=x+1

    
>>> f()
>>> x
>>> f()
>>> x

Nesting

>>> def multiplier(factor):
    def multiplyByFactor(number):
        return number*factor
    return multiplyByFactor

>>> double=multiplier(2)
>>> double(5)
>>> multiplier(2*5)
<function multiplyByFactor at 0x0000000002F8C6D8>
>>> multiplier(2)(5)

Recursive (call)

Factorial and power

>>> def factorial(n):
    if n==1:
        return 1
    else:
        return n*factorial(n-1)
    
>>> factorial(5)
>>> range(3)
[0, 1, 2]
>>> def power(x,n):
    result=1
    for i in range(n):
        result *= x
    return result
>>> power(5,3)

>>> def power(x,n):
    if n==0:
        return 1
    else:
        return x*power(x,n-1)

    
>>> power(2,3)

## Binary search

>>> def search(s,n,min=0,max=0):
    if max==0:
        max=len(s)-1
    if min==max:
        assert n==s[max]
        return max
    else:
        middle=(min+max)/2
        if n>s[middle]:
            return search(s,n,middle+1,max)
        else:
            return search(s,n,min,middle)

        
>>> search(seq,100)

map function

It receives a function and a list, and uses the function to act on each element of the list in turn to get a new list and returns

>>> map(str,range(10))
['0', '1', '2', '3', '4', '5', '6', '7', '8', '9']
>>> def f(x):
    return x*x

>>> print map(f,[1,2,3,4,5,6,7])
[1, 4, 9, 16, 25, 36, 49]

>>> def format_name(s):
    s1=s[0].upper()+s[1:].lower()
    return s1

>>> print map(format_name,['ASDF','jskk'])
['Asdf', 'Jskk']

filter function

it Receives a function and a list (list). This function judges each element in turn and returns True or False. filter() automatically filters out elements that do not meet the conditions based on the judgment results and returns a new list composed of elements that meet the conditions.

>>> def is_not_empty(s):
    return s and len(s.strip())>0

>>> filter(is_not_empty,[None,'dshk','  ','sd'])
['dshk', 'sd']
>>> def pfg(x):
    s=math.sqrt(x)
    if s%1==0:
        return x

>>> import math
>>> pfg(100)
>>> pfg(5)
>>> filter(pfg,range(100))
[1, 4, 9, 16, 25, 36, 49, 64, 81]
>>> def is_sqr(x):
    return math.sqrt(x)%1==0

>>> is_sqr(100)
True
>>> filter(is_sqr,range(100))
[0, 1, 4, 9, 16, 25, 36, 49, 64, 81]

lambda function

is also called an anonymous function, that is, the function has no specific name and is created with def The method is named

>>> def foo():return 'Begin'

>>> lambda:'begin'
<function <lambda> at 0x0000000002ECC2E8>
>>> s=lambda:&#39;begin&#39;
>>> print s()
begin
>>> s= lambda x,y:x+y
>>> print s(1,2)
>>> def sum(x,y=6):return x+y

>>> sum2=lambda x,y=6:x+y
>>> sum2(4)

>>> filter(lambda x:x*x,range(1,5))
[1, 2, 3, 4]>>> map(lambda x:x*x,range(1,5))
[1, 4, 9, 16]>>> filter(lambda x:x.isalnum(),['8ui','&j','lhg',')j'])
['8ui', 'lhg']

reduce function

It receives a function and A list (list), the function must receive two parameters. This function calls each element of the list in turn and returns a new list composed of the result values

>>> reduce(lambda x,y:x*y,range(1,5))
24
>>> reduce(lambda x,y:x+y,[23,9,5,6],100) #初始值为100，依次相加列表中的值
143

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