1.1 collection

It is an iterable, unordered data structure that cannot contain repeated elements. The elements of the collection are immutable, such as: int, float, string, tuple, etc. The variable content cannot be the elements of the collection, such as: list, dict, set, etc.

Collections can be divided into:

• Mutable collection (set)
• Immutable collections (frozenset)

1.2 Mutable collections

1.2.1 Create collection

>>> a = {1,3,2,4}
>>> a
{1, 2, 3, 4}

It is represented by big {}, note: the dictionary is also represented by {}, but it stores key-value pairs.

>>> a = set()  # create an empty collection, if a={} is an empty dictionary
>>> a
set()

Use the set function to create a collection, which is followed by a sequence:

>>> a = set("hello")
>>> a
{'e', 'o', 'h', 'l'}

1.2.2 Modifying mutable collections

• Add element: add(elem)

  Note: Duplicate elements cannot be added because collection elements are not repeated.

>>> a = set()
>>> a = {1,2,3,4}
>>> a.add(5)
>>> a
{1, 2, 3, 4, 5}
>>> a.add(4)
>>> a
{1, 2, 3, 4, 5}

• Delete elements: remove(elem); discard(elem)

  The difference between the two elements is that an exception is thrown before deleting an element that does not exist, and the latter will not.

>>> a = {1,2,3,4}
>>> a.remove(1)
>>> a
{2, 3, 4}
>>> a.discard(4)
>>> a
{2, 3}
>>> a.remove(4)  # 4 does not exist, an exception is thrown
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
KeyError: 4

• Delete any element, the return value is the deleted element: pop()

>>> a = {1,3,2,4}
>>> a.pop()
1

• Empty collection: clear()

>>> a = {1,2,3,4}
>>> a.clear()
>>> a
set()

1.2.3 Other methods

• Copy a collection: copy()

>>> a = {1,2,3,4}
>>> b = a.copy()
>>> b
{1, 2, 3, 4}

• The empty intersection of two collections returns true: isdisjoint()

>>> a = {1,2,3,4}
>>> b = {1,2}
>>> a.isdisjoint(b)  # Intersect returns False
False

• is a subset returns true: issubset()

>>> a = {1,2,3,4}
>>> b = {1,2,3,4,5}
>>> a.issubset(b)
True
>>> b.issubset(a)
False

• is a superset returns true: issuperset()

>>> a = {1,2,3,4,5}
>>> b = {1,2}
>>> c = {1,2,6}
>>> a.issuperset(b)
True
>>> a.issuperset(c)
False

• Merge collection to collection A: update()

>>> a = {1,2,3,4}
>>> a.update({3,4,5,6})
>>> a
{1, 2, 3, 4, 5, 6}

1.2.4 Operations on Sets

operator	illustrate
&	Intersection: Get elements that exist in both sets
|	Union: Two collection elements are merged together, and duplicates are removed.
-	Difference set: A set that belongs to set A but does not belong to set B
^	Symmetric difference set: only belongs to set A and set B, that is, what is left after removing the intersection.
==	equal
!=	not equal
in	inside
not in	not in

• Intersection: intersection; intersection_update

>>> a = {1,2,3,4}
>>> b = {1,2}
>>> a & b
{1, 2}
>>> a.intersection(b)
{1, 2}

# intersection_update will modify the collection A, while the former generates a new collection
>>> a = {1,2,3,4}
>>> b = {3,4,5,6}
>>> a.intersection_update(b)
>>> a
{3, 4}

• Union: union

>>> a = {1,2,3,4}
>>> b = {5,6}
>>> a | b
{1, 2, 3, 4, 5, 6}
>>> a.union(b)
{1, 2, 3, 4, 5, 6}

• Difference set: difference; difference_update()

>>> a = {1,2,3,4}
>>> b = {1,2}
>>> a - b
{3, 4}
>>> a.difference()
{1, 2, 3, 4}
>>> b - a  # Conversely subtract, there is no element after removal.
set()

# difference_update will modify collection A
>>> a = {1,2,3,4}
>>> b = {3,4,5,6}
>>> a - b
{1, 2}
>>> a  # no change
{1, 2, 3, 4}
>>> a.difference_update(b)
>>> a  # changed
{1, 2}

• Symmetric difference: symmetric_difference(); symmetric_difference_update()

>>> a = {1,2,3,4}
>>> b = {3,4,5,6}
>>> a ^ b
{1, 2, 5, 6}
>>> a.symmetric_difference(b)
{1, 2, 5, 6}

# symmetric_difference_update modifies set A

1.2.5 Universal functions

function	illustrate
enumerate()	Number the elements and return an enumerate object
len()	length
max()	maximum value
min()	minimum value
sorted()	Sort, generate a new list
sum()	to sum

>>> a = {'a','b','c','hello'}
>>> a
{'a', 'b', 'hello', 'c'}
>>> for i in enumerate(a):
...     print(i)
...
(0, 'a')
(1, 'b')
(2, 'hello')
(3, 'c')

1.3 Immutable collection frozenset

Known as a frozen collection, it cannot be changed, but it can be accessed and set operations.

Immutable collections can be used as keys in dictionaries and as elements in collections.

# create
>>> a = frozenset(["Zhang San","Li Si","hello",1,2,3])
>>> a
frozenset({1, 2, 3, 'hello', 'Zhang San', 'Li Si'})
>>> type(a)
<class 'frozenset'>

1.4 Set comprehensions

Same as list comprehension

# [item for item in iterable]
# [item for item in iterable if condition]

>>> a = {i for i in range(10)}
>>> a
{0, 1, 2, 3, 4, 5, 6, 7, 8, 9}