python之常用builtins

分为class和function

1. class
1.1 class range
help(__builtins__.range)
class range(object)
 |  range(stop) -> range object
 |  range(start, stop[, step]) -> range object
 |  Return a sequence of numbers from start to stop by step.
平时我们在for循环中经常用到range，其实这里的range是类而非function
python3.x中range取代了xrange，从原来的内置函数变成了类

for num in range(4):
    print(num, end = ' ')

output:

0 1 2 3 

1.2 class filter
class filter(object)
 |  filter(function or None, iterable) --> filter object
 |  Return an iterator yielding those items of iterable for which function(item)
 |  is true. If function is None, return the items that are true.

values = ['1', '2', '-3', '-', '4', 'N/A', '5']
def is_int(val):
    try:
        if int(val):
            return True
    except ValueError:
        return False
ivals = list(filter(is_int, values))
print(ivals)

output:

['1', '2', '-3', '4', '5']

1.3 class enumerate
class enumerate(object)
 |  enumerate(iterable[, start]) -> iterator for index, value of iterable
 |  
 |  Return an enumerate object.  iterable must be another object that supports
 |  iteration.  The enumerate object yields pairs containing a count (from
 |  start, which defaults to zero) and a value yielded by the iterable argument.
 |  enumerate is useful for obtaining an indexed list:
 |      (0, seq[0]), (1, seq[1]), (2, seq[2]), ...

S = 'abcdefghijk'
for (index,char) in enumerate(S):
    print(str(index).center(2), end = ' ')
    print(char)

output:

0  a
1  b
2  c
3  d
4  e
5  f
6  g
7  h
8  i
9  j
10 k

1.4 class zip(object)
 |  zip(iter1 [,iter2 [...]]) --> zip object
 |  
 |  Return a zip object whose .__next__() method returns a tuple where
 |  the i-th element comes from the i-th iterable argument.  The .__next__()
 |  method continues until the shortest iterable in the argument sequence
 |  is exhausted and then it raises StopIteration.
1.4.1
一般应用

#列表以及迭代器的压缩和解压缩
ta = [1,2,3]
tb = [9,8,7]
tc = ['a','b','c']
for (a,b,c) in zip(ta,tb,tc):
    print(a,b,c)

# cluster
# zipped is a generator
zipped = zip(ta,tb)
print(zipped)
print(type(zipped))

# decompose
na, nb = zip(*zipped)
print(na, nb)

output:

1 9 a
2 8 b
3 7 c
<zip object at 0x00000000023CDEC8>
<class 'zip'>
(1, 2, 3) (9, 8, 7)

1.4.2
列表相邻元素压缩器
zip(*[iter(s)]*n)应用
How does zip(*[iter(s)]*n) work in Python? 
解释1：
iter() is an iterator over a sequence. [x] * n produces a list containing n quantity of x, i.e. a list of length n, 
where each element is x. *arg unpacks a sequence into arguments for a function call. 
Therefore you're passing the same iterator 3 times to zip(), and it pulls an item from the iterator each time.
解释2：
iter(s) returns an iterator for s.
[iter(s)]*n makes a list of n times the same iterator for s.
So, when doing zip(*[iter(s)]*n), it extracts an item from all the three iterators from the list in order. 
Since all the iterators are the same object, it just groups the list in chunks of n.

example1:

s = [1,2,3,4,5,6,7,8,9]
n = 3

zz = zip(*[iter(s)]*n) # returns [(1,2,3),(4,5,6),(7,8,9)]
for i in zz:
    print(i)

output:

(1, 2, 3)
(4, 5, 6)
(7, 8, 9)

example2:

x = iter([1,2,3,4,5,6,7,8,9])
for i in zip(x, x, x):
    print(i)

output:

(1, 2, 3)
(4, 5, 6)
(7, 8, 9)

1.4.3
针对上面的扩展
One word of advice for using zip like 1.4.2. It will truncate your list if it's length is not evenly divisible.
you could use something like this:

def n_split(iterable, n):
    num_extra = len(iterable) % n
    zipped = zip(*[iter(iterable)] * n)
    return list(zipped) if not num_extra else list(zipped) + n_split(iterable[-num_extra:],num_extra)

for ints in n_split(range(1,12), 3):
    print(', '.join([str(i) for i in ints]))

output:

1, 2, 3
4, 5, 6
7, 8, 9
10, 11

注：
a.帖子上对n_split函数的return是return zipped if not num_extra else zipped + [iterable[-num_extra:], ],
但是这样会报错 TypeError: unsupported operand type(s) for +: 'zip' and 'list'，所以最终修改成以上形式。
b.print(', '.join([str(i) for i in ints])) 中i必须是str形式，不然会报错
1.4.4 针对二维矩阵的行列互换

a = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
b = map(list,zip(*a))
for i in b:
    print(i)

output:

[1, 4, 7]
[2, 5, 8]
[3, 6, 9]

1.4.5 反转字典

m = {'a': 1, 'b': 2, 'c': 3, 'd': 4}
print(dict(zip(m.values(), m.keys())))

output:

{1: 'a', 2: 'b', 3: 'c', 4: 'd'}

1.5 class map
class map(object)
 |  map(func, *iterables) --> map object
 |  
 |  Make an iterator that computes the function using arguments from
 |  each of the iterables.  Stops when the shortest iterable is exhausted.

re = map((lambda x,y: x+y),[1,2,3],[6,7,9])
for i in re:
    print(i)

output:

7
9
12

1.6 class slice
class slice(object)
 |  slice(stop)
 |  slice(start, stop[, step])
 |  
 |  Create a slice object.  This is used for extended slicing (e.g. a[0:10:2]).
 |  
 |  Methods defined here:
 |  indices(...)
 |      S.indices(len) -> (start, stop, stride)
 |      
 |      Assuming a sequence of length len, calculate the start and stop
 |      indices, and the stride length of the extended slice described by
 |      S. Out of bounds indices are clipped in a manner consistent with the
 |      handling of normal slices.
 |  Data descriptors defined here:
 |  start
 |  step
 |  stop

#命名列表切割方式
a = [0, 1, 2, 3, 4, 5]
ind = slice(-3, None)
print(a[ind]) 
for i in ind.indices(6):
    print(i)  
print(a[3:6:1])
#由上脚本可知indices其实就是对slice的一种解释，其实把slice(-3, None)变成slice(3,6,1)结果也是一样的

output:

[3, 4, 5]
3
6
1
[3, 4, 5]

2. built-in functions:
2.1 built-in function iter 
iter(...)
    iter(iterable) -> iterator
    iter(callable, sentinel) -> iterator
    
    Get an iterator from an object.  In the first form, the argument must
    supply its own iterator, or be a sequence.
    In the second form, the callable is called until it returns the sentinel.

for i in iter(range(5)):
    print(i, end = ' ')

output:

0 1 2 3 4

2.2 built-in function min
min(...)
    min(iterable, *[, default=obj, key=func]) -> value
    min(arg1, arg2, *args, *[, key=func]) -> value
    
    With a single iterable argument, return its smallest item. The
    default keyword-only argument specifies an object to return if
    the provided iterable is empty.
    With two or more arguments, return the smallest argument.

# for the tow methods, we give the examples, as follows:
# Data reduction across fields of a data structure
portfolio = [
   {'name':'GOOG', 'shares': 50},
   {'name':'YHOO', 'shares': 75},
   {'name':'AOL', 'shares': 20},
   {'name':'SCOX', 'shares': 65}
]
print(min(p['shares'] for p in portfolio))
print(min(portfolio, key = lambda x: x['shares']))

output:

20
{'name': 'AOL', 'shares': 20}

2.3 Help on built-in function eval
eval(...)
    eval(source[, globals[, locals]]) -> value
    
    Evaluate the source in the context of globals and locals.
    The source may be a string representing a Python expression
    or a code object as returned by compile().
    The globals must be a dictionary and locals can be any mapping,
    defaulting to the current globals and locals.
    If only globals is given, locals defaults to it.
eval()函数十分强大，官方demo解释为：将字符串str当成有效的表达式来求值并返回计算结果。so，结合math当成一个计算器很好用。
其他用法，可以把list,tuple,dict和string相互转化。见下例子：

>>> a = "[[1,2], [3,4], [5,6], [7,8], [9,0]]"
>>> print(type(eval(a)))
<class 'list'>

另一个例子：

# Compute area with console input
import math
# Prompt the user to enter a radius
radius = eval(input("Enter a value for radius:"))
# compute area
area = pow(radius, 2) * math.pi
# Display results
print("The area for the circle of radius", radius, "is", area)