内置序列概览
-
容器序列(container sequences):
list,tuple,collections.deque- 存放对象的引用
-
扁平序列(flat sequences):
str,bytes,array.array- 在自己的内存空间存储内容值
-
CPython 对象头包含实现相关的元数据（其他 Python 实现不必使用相同布局）
- float:
ob_refcnt,ob_type,ob_fval
- float:
-
可变序列(Mutable sequences):
list, bytearray, array.array, collections.deque -
不可变序列(Immutable sequences):
tuple, str, bytes
列表推导式/生成器表达式
- List Comprehensions(listcomps) and Generator Expressions(genexps)
In Python code, line breaks are ignored inside pairs of [], {}, or (). So you can build multiline lists, listcomps, tuples, dictionaries, etc., without using the \ line continuation escape, which doesn’t work if you accidentally type a space after it.
- “Walrus operator”
:=：在推导式中，赋值表达式的目标绑定到外层作用域；循环变量仍属于推导式内部作用域。下面的last能在推导式外访问，c则不能。
>>> x = 'ABC'
>>> codes = [ord(x) for x in x]
>>> x
'ABC'
>>> codes
[65, 66, 67]
>>> codes = [last := ord(c) for c in x]
>>> last
67
>>> c
File "<stdin>", line 1, in <module>
NameError: name 'c' is not defined- some useful tips For :=a
# INVALID
x := 0
# Valid alternative
(x := 0)
# INVALID
x = y := 0
# Valid alternative
x = (y := 0)
# Valid
len(lines := f.readlines())
# Valid
foo(x := 3, cat='vector')
# INVALID
foo(cat=category := 'vector')
# Valid alternative
foo(cat=(category := 'vector'))- Differences between assignment expressions and assignment statements
- Multiple targets are not directly supported:
x = y = z = 0 # Equivalent: (z := (y := (x := 0)))
- Single assignment targets other than a single `NAME` are not supported:
# No equivalent
a[i] = x
self.rest = []
- Priority around commas is different:
x = 1, 2 # Sets x to (1, 2)
(x := 1, 2) # Sets x to 1
- Iterable packing and unpacking (both regular or extended forms) are not supported:
# Equivalent needs extra parentheses
loc = x, y # Use (loc := (x, y))
info = name, phone, *rest # Use (info := (name, phone, *rest))
# No equivalent
px, py, pz = position
name, phone, email, *other_info = contact
- Inline type annotations are not supported:
# Closest equivalent is "p: Optional[int]" as a separate declaration
p: Optional[int] = None
- Augmented assignment is not supported:
total += tax # Equivalent: (total := total + tax)- 列表推导式与map/filter比较，有时候可读性更强，性能方面相差不大
>>> symbols = '$¢£¥€¤'
>>> beyond_ascii = [ord(s) for s in symbols if ord(s) > 127]
>>> beyond_ascii
[162, 163, 165, 8364, 164]
>>> beyond_ascii = list(filter(lambda c: c > 127, map(ord, symbols)))
>>> beyond_ascii
[162, 163, 165, 8364, 164]- 生成器表达式通过迭代器逐个产生项，而不是构建一个列表提供给其他构造函数
line_list = [' line 1\n', 'line 2 \n', ' \n', '']
# Generator expression -- returns iterator
stripped_iter = (line.strip() for line in line_list)
# List comprehension -- returns list
stripped_list = [line.strip() for line in line_list]- array
array.typecodes：可用类型码随 Python 版本变化，在当前解释器中查询- the type of objects stored in them is constrained
元组
- Tuples hold records: each item in the tuple holds the data for one field, and the position of the item gives its meaning.
- print with operator ’%’ can unpack tuple
- Tuples as Immutable Lists:
- When you see a tuple in code, you know its length will never change.
- A tuple uses less memory than a list of the same length, and it allows Python to do some optimizations.
hash能判断对象是否可哈希，但不能一般性地证明其内容不会变化。元组可哈希要求各元素可哈希；自定义可变对象也可能可哈希。下面这个函数实际检查的是可哈希性。
def is_hashable(o):
try:
hash(o)
except TypeError:
return False
return True
tf = (10, 'alpha', (1, 2)) # Contains no mutable items
tm = (10, 'alpha', [1, 2]) # Contains a mutable item (list)
is_hashable(tf) # True
is_hashable(tm) # False序列和可迭代对象拆包
- parallel assignment
>>> lax_coordinates = (33.9425, -118.408056)
>>> latitude, longitude = lax_coordinates # unpacking
>>> latitude
33.9425
>>> divmod(20, 8)
(2, 4)
>>> t = (20, 8)
>>> divmod(*t)
(2, 4)
>>> quotient, remainder = divmod(*t)
>>> quotient, remainder
(2, 4)
>>> import os
>>> _, filename = os.path.split('/home/luciano/.ssh/id_rsa.pub')
>>> filename
'id_rsa.pub'- 在序列拆包赋值中，一个目标列表可以有一个星号目标，位置不必在最后；它收集剩余项。
- 函数定义中的
*args与调用时的*iterable是相关但不同的语法，分别遵循函数参数和调用规则。
- 函数定义中的
>>> a, b, *rest = range(5)
>>> a, b, rest
(0, 1, [2, 3, 4])
>>> a, *b, rest = range(4)
>>> a, b, rest
(0, [1, 2], 3)
>>> a, b, *rest = range(2)
>>> a, b, rest
(0, 1, [])
>>> *a, = range(5)
>>> a
[0, 1, 2, 3, 4]
>>> *range(4), 4
(0, 1, 2, 3, 4)A Small Puzzle
Example 2-16. A riddle
>>> t = (1, 2, [30, 40])
>>> t[2] += [50, 60]What happens next? Choose the best answer:
- A. t becomes (1, 2, [30, 40, 50, 60]).
- B. TypeError is raised with the message ‘tuple’ object does not support item assignment.
- C. Neither.
- D. Both A and B.
答案是 D：列表先原地扩展，随后对元组元素赋值时报错。以下反汇编是旧版 CPython 输出；具体指令随版本变化。
>>> import dis
>>> dis.dis('s[a] += b')
1 0 LOAD_NAME 0 (s)
2 LOAD_NAME 1 (a)
4 DUP_TOP_TWO
6 BINARY_SUBSCR # Put the value of s[a] on TOS (Top Of Stack)
8 LOAD_NAME 2 (b)
10 INPLACE_ADD # Perform add
12 ROT_THREE
14 STORE_SUBSCR # Assign
16 LOAD_CONST 0 (None)
18 RETURN_VALUEList.sort与内置函数sorted
- List.sort method sorts a list in place without making a copy(use Timsort)
- The built-in function sorted creates a new list and returns it
- Accept both
reverseandkey(function)
When a List Is Not the Answer
- If a list only contains numbers, an array.array is a more efficient replacement. Arrays support all mutable sequence operations (including
.pop,.insert, and.extend), as well as additional methods for fast loading and saving, such as.frombytesand.tofile. - The built-in memoryview class is a shared-memory sequence type that lets you handle slices of arrays without copying bytes.
>>> from array import array
>>> octets = array('B', range(6))
>>> m1 = memoryview(octets)
>>> m1.tolist()
[0, 1, 2, 3, 4, 5]
>>> m2 = m1.cast('B', [2, 3])
>>> m2.tolist()
[[0, 1, 2], [3, 4, 5]]
>>> m3 = m1.cast('B', [3, 2])
>>> m3.tolist()
[[0, 1], [2, 3], [4, 5]]
>>> m2[1,1] = 22
>>> m3[1,1] = 33
>>> octets
array('B', [0, 1, 2, 33, 22, 5])- NumPy implements multidimensional, homogeneous arrays and matrix types that hold not only numbers but also user-defined records, and provides efficient element-wise operations.
- Deques and Other Queues