Set in Python (3)

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*Memo:

• My post explains a set (1).
• My post explains a set (2).
• My post explains a set (4).

A set can be iterated with a for statement as shown below:

<1D set>:

for x in {10, 20, 30, 40, 50}:
    print(x)
# 40
# 10
# 50
# 20
# 30

<2D set>:

for x in {frozenset({10, 20, 30, 40}), frozenset({50, 60, 70, 80})}:
    for y in x:
        print(y)
# 40
# 10
# 20
# 30
# 80
# 50
# 60
# 70

<3D set>:

for x in {frozenset({frozenset({10, 20}), frozenset({30, 40})}),
          frozenset({frozenset({50, 60}), frozenset({70, 80})})}:
    for y in x:
        for z in y:
            print(z)
# 40
# 30
# 10
# 20
# 80
# 70
# 50
# 60

A set can be unpacked with an assignment and for statement, function and * but not with ** as shown below:

v1, v2, v3 = {0, 1, 2}

print(v1, v2, v3)
# 0 1 2

v1, *v2, v3 = {0, 1, 2, 3, 4, 5}

print(v1, v2, v3)  # 0 [1, 2, 3, 4] 5
print(v1, *v2, v3) # 0 1 2 3 4 5

for v1, v2, v3 in {frozenset({0, 1, 2}), frozenset({3, 4, 5})}:
    print(v1, v2, v3)
# 3 4 5
# 0 1 2

for v1, *v2, v3 in {frozenset({0, 1, 2, 3, 4, 5}),
                    frozenset({6, 7, 8, 9, 10, 11})}:
    print(v1, v2, v3)
    print(v1, *v2, v3)
# 6 [7, 8, 9, 10] 11
# 6 7 8 9 10 11
# 0 [1, 2, 3, 4] 5
# 0 1 2 3 4 5

print(*{0, 1}, 2, *{3, 4, *{5}})
# 0 1 2 3 4 5

print({*{0, 1}, 2, *{3, 4, *{5}}})
# {0, 1, 2, 3, 4, 5}

def func(p1='a', p2='b', p3='c', p4='d', p5='e', p6='f'):
    print(p1, p2, p3, p4, p5, p6)

func()
# a b c d e f

func(*{0, 1, 2, 3}, *{4, 5})
# 0 1 2 3 4 5

def func(p1='a', p2='b', *args):
    print(p1, p2, args)
    print(p1, p2, *args)
    print(p1, p2, ['A', 'B', *args, 'C', 'D'])

func()
# a b ()
# a b Nothing
# a b ['A', 'B', 'C', 'D']

func(*{0, 1, 2, 3}, *{4, 5})
# 0 1 (2, 3, 4, 5)
# 0 1 2 3 4 5
# 0 1 ['A', 'B', 2, 3, 4, 5, 'C', 'D']

set() can create a set with or without an iterable as shown below:

*Memo:

• The 1st argument is iterable(Optional-Default:()-Type:Iterable):
  • Don't use iterable=.

# Empty set
print(set())
print(set(()))
# set()

print(set([0, 1, 2, 3, 4]))                      # list
print(set((0, 1, 2, 3, 4)))                      # tuple
print(set(iter([0, 1, 2, 3, 4])))                # iterator
print(set({0, 1, 2, 3, 4}))                      # set
print(set(frozenset([0, 1, 2, 3, 4])))           # frozenset
print(set(range(5)))                             # range
# {0, 1, 2, 3, 4}

print(set({'name': 'John', 'age': 36}))          # dict
print(set({'name': 'John', 'age': 36}.keys()))   # dict.keys()
# {'age', 'name'}

print(set({'name': 'John', 'age': 36}.values())) # dict.values()
# {'John', 36}

print(set({'name': 'John', 'age': 36}.items()))  # dict.items()
# {('age', 36), ('name', 'John')}

print(set('Hello'))                              # str
# {'H', 'e', 'l', 'o'}

print(set(b'Hello'))                             # bytes
print(set(bytearray(b'Hello')))                  # bytearray
# {72, 108, 101, 111}

A set comprehension can create a set as shown below:

<1D set>:

sample = {0, 1, 2, 3, 4, 5, 6, 7}

A = {x**2 for x in sample}

print(A)
# {0, 1, 4, 36, 9, 16, 49, 25}

<2D set>:

sample = {frozenset({0, 1, 2, 3}), frozenset({4, 5, 6, 7})}

A = {frozenset(y**2 for y in x) for x in sample}

print(A)
# {frozenset({16, 25, 36, 49}), frozenset({0, 1, 4, 9})}

<3D set>:

sample = {frozenset({frozenset({0, 1}), frozenset({2, 3})}),
          frozenset({frozenset({4, 5}), frozenset({6, 7})})}

A = {frozenset(frozenset(z**2 for z in y) for y in x) for x in sample}

print(A)
# {frozenset({frozenset({16, 25}), frozenset({49, 36})}),
#  frozenset({frozenset({9, 4}), frozenset({0, 1})})}

Be careful, a big set gets MemoryError as shown below:

A = range(1000000000)

print(set(A))
# MemoryError

A = {x for x in range(1000000000)}
# MemoryError