The original URL: https://github.com/satwikkansal/wtfpython

Datatype

All problems about datatype.

Shallow-copy and Deep-copy

When it comes to deep copy and shallow copy, the differences can be compared based on data types, copy principles, and copy functions. Here is a table in Markdown format that summarizes the differences between deep copy and shallow copy:

This table provides an overview of the differences between deep copy and shallow copy based on different data types, copy principles, and the use of copy functions. Please note that the mentioned copy functions refer to the copy module provided by the Python standard library.

Following is code about this feature:

import copy

nested_array = [1, 2, 7, [4, 9, 6]]

shallow_copy = copy.copy(nested_array)

deep_copy = copy.deepcopy(nested_array)

# Original array: [1, 2, 7, [4, 9, 6]] 2456116559808
print("Original array:", nested_array, id(nested_array), "\n")
# Shallow copy before modifying: [1, 2, 7, [4, 9, 6]] 140724048356296
print("Shallow copy before modifying:", shallow_copy, id(shallow_copy[3]), "\n")
nested_array[3].append(512)
# Shallow copy after modifying: [1, 2, 7, [4, 9, 6, 512]] 140724048356296 
print("Shallow copy after modifying:", shallow_copy, id(shallow_copy[3]), "\n")
# original array: [1, 2, 7, [4, 9, 6]] 2456116539264 
print("Original array:", deep_copy, id(deep_copy), "\n")
nested_array[3][2] = 1024
# Original array after modifying by deep copying: [1, 2, 7, [4, 9, 1024, 512]] 2456116559808
print("Original array after modifying by deep copying:", nested_array, id(nested_array), "\n")
# original array after deep copying: [1, 2, 7, [4, 9, 6]] 2456116539264 
print("Original array after deep copying:", deep_copy, id(deep_copy), "\n")

unconspicuous shallow copying

>>> row = [""] * 3
>>> board = [row] * 3
>>> board
[['', '', ''], ['', '', ''], ['', '', '']]
>>> board[0][0]
''
>>> board[0][0] = "X"
>>> board
[['X', '', ''], ['X', '', ''], ['X', '', '']]

To avoid this problem, we can initialize a grid, and instantly modify the value of [0][0].

board = [[""] * 3 for _  in range(3)]
board[0][0] = "X"
print(board)

small integer caching

Original: Pylong_Fromlong

Quote: The reason of small integer caching

The range of caching is from -5 to 256. And the meaning of is mean to varaibles which possessed the same memory address. So, for those caching integer number, they are assigned memory address in advance. When we use assignment statement to assign number for variables, those variables will get the same memory address for the same value.

a, b = 256, 256
for i in range(250, 260):
    if a is not b:
        break
    a += 1
    b += 1
print("start point: ", a, "end point:", b)  # a = b = 257

dict or set

uniqueness of the key's logic

Althogh there are three object, such as number, complex, and float number, those objects have the same logic value.

>>> collections = dict()
>>> temporary = 5 + 0j
>>> collections[5] = "Dog"
>>> collections[5]
'Dog'
>>> collections[5.0] = "Pear"
>>> collections[5.0]
'Pear'
>>> collections[temporary] = "King"
>>> collections[temporary]
'King'
>>> collections[5]
'King'
>>> collections[5.0]
'King'
>>> collections[temporary]
'King'

Operator

all about operator in python.

walrus operator

version: Python 3.8

PEP No: 572

Function

try-except

• The return value is determined by the last return sentence.
• The finally sentence will be definitely be executed.
• The interactive interface gives the output, but the IDE maybe gives output.

def simple():
    try:
        # return 10086
        return "from try"
    finally:
        # return 1024
        return "from finally"


def asceticism():
    for _ in range(3):
        try:
            continue
        finally:
            print(10000)


def complex():
    try:
        for i in range(3):
            try:
                1 / i
            except ZeroDivisionError:
                raise ZeroDivisionError("Invalid value")
            finally:
                print("Normal", i)
                break
    except ZeroDivisionError as e:
        print("Zero devision error occured", e)

reassign value

array = [1, 2, 5]
g = (x for x in array if array.count(x) > 0)
array = [9, 2, 4]
print(list(g))