10 Things You Didn’t Know You Could Do in Python3

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Python is the third most commonly-used programming language. It has introduced many new features, simplifying and enhancing the development process. Yet, many developers remain unaware of the full potential that Python 3 has to offer.

This article will uncover ten lesser-known and underutilized capabilities in Python (v3.5 to v3.11). These hidden gems can improve your coding efficiency and productivity. So, without further ado, let’s dive into these fascinating Python 3 features.

1. Walrus Operator

It’s a new syntax introduced in Python 3.11 that assigns values to variables as part of a larger expression.

Old way

a = "This is a sample string text"
if len(a) > 10:
    print("Length of string a = ", len(a))
a = "This is a sample string text"

if len(a) > 10:
    print("Length of string a = ", len(a))
a = "This is a sample string text"

if len(a) > 10:
    print("Length of string a = ", len(a))

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New way

a = "This is a sample string text"
if (len_a := len(a)) > 10: # Note the walrus operator will compute value of len(a) and assign it to variable len_a
    print("Length of string a = ", len_a)
a = "This is a sample string text"

if (len_a := len(a)) > 10: # Note the walrus operator will compute value of len(a) and assign it to variable len_a
    print("Length of string a = ", len_a)
a = "This is a sample string text"

if (len_a := len(a)) > 10: # Note the walrus operator will compute value of len(a) and assign it to variable len_a
    print("Length of string a = ", len_a)

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2. Structural Pattern Matching

You might remember reading that Python doesn’t support switch statements because if-else can achieve the same result. You are in for a treat. Python3.10 introduced something similar.

Old way

def http_error(status):
    if status == 400:
        return "Bad request"
    elif status == 404:
        return "Not found"
    elif status == 418:
        return "I'm a teapot"
    else:
        return "Something's wrong with the internet"
def http_error(status):
    if status == 400:
        return "Bad request"
    elif status == 404:
        return "Not found"
    elif status == 418:
        return "I'm a teapot"
    else:
        return "Something's wrong with the internet"
def http_error(status):
    if status == 400:
        return "Bad request"
    elif status == 404:
        return "Not found"
    elif status == 418:
        return "I'm a teapot"
    else:
        return "Something's wrong with the internet"

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New way

def http_error(status):
    match status:
        case 400:
            return "Bad request"
        case 404:
            return "Not found"
        case 418:
            return "I'm a teapot"
        case _: # This is a wildcard operator
            return "Something's wrong with the internet"
def http_error(status):
    match status:
        case 400:
            return "Bad request"
        case 404:
            return "Not found"
        case 418:
            return "I'm a teapot"
        case _: # This is a wildcard operator
            return "Something's wrong with the internet"
def http_error(status):
    match status:
        case 400:
            return "Bad request"
        case 404:
            return "Not found"
        case 418:
            return "I'm a teapot"
        case _: # This is a wildcard operator
            return "Something's wrong with the internet"

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3. Merging Dictionaries

Python3.9 introduced a new way of merging or updating dictionaries. It complements the existing dict.update and {**d1, **d2} methods of merging dictionaries.

Old way

x = {"key1": "value1 from x", "key2": "value2 from x"}
y = {"key2": "value2 from y", "key3": "value3 from y"}
print({ **x,** y})
print({ **y,** x}) # Note here keys of y would be given preference over keys of x
x = {"key1": "value1 from x", "key2": "value2 from x"}
y = {"key2": "value2 from y", "key3": "value3 from y"}

print({ **x,** y})
print({ **y,** x}) # Note here keys of y would be given preference over keys of x
x = {"key1": "value1 from x", "key2": "value2 from x"}
y = {"key2": "value2 from y", "key3": "value3 from y"}

print({ **x,** y})
print({ **y,** x}) # Note here keys of y would be given preference over keys of x

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New way

x = {"key1": "value1 from x", "key2": "value2 from x"}
y = {"key2": "value2 from y", "key3": "value3 from y"}
# Note the usage of OR (|) operator
print(x | y)
prin(y | x) # Note here keys of y would be given preference over keys of x
x = {"key1": "value1 from x", "key2": "value2 from x"}
y = {"key2": "value2 from y", "key3": "value3 from y"}

# Note the usage of OR (|) operator
print(x | y)
prin(y | x) # Note here keys of y would be given preference over keys of x
x = {"key1": "value1 from x", "key2": "value2 from x"}
y = {"key2": "value2 from y", "key3": "value3 from y"}

# Note the usage of OR (|) operator
print(x | y)
prin(y | x) # Note here keys of y would be given preference over keys of x

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4. Removing Prefix or Suffix

Python3.9 introduced dedicated methods to get rid of prefixes or suffixes in strings.

Old way

x = "prefixstring"
y = "stringsuffix"
print(x.split("prefix")[-1])
print(y.split("suffix")[0])
x = "prefixstring"
y = "stringsuffix"

print(x.split("prefix")[-1])
print(y.split("suffix")[0])
x = "prefixstring"
y = "stringsuffix"

print(x.split("prefix")[-1])
print(y.split("suffix")[0])

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New way

x = "prefixstring"
y = "stringsuffix"
print(x.removeprefix("prefix"))
print(y.removesuffix("suffix"))
x = "prefixstring"
y = "stringsuffix"

print(x.removeprefix("prefix"))
print(y.removesuffix("suffix"))
x = "prefixstring"
y = "stringsuffix"

print(x.removeprefix("prefix"))
print(y.removesuffix("suffix"))

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5. Positional Only Parameters

Python provides to define positional and keyword arguments for a function. But you can pass them interchangeably. Python3.8 introduced a way to enforce that you cannot pass positional arguments as keyword arguments.

Old way

def fun(pos_arg1, pos_arg2, key_arg_1 = None):
    print("positional arguments: ", pos_arg1, pos_arg2)
    print("Keyword arguments: ", key_arg_1)
# It will work
fun(1, 2, 3) # Passing keyword argument as positional argument
# It will also work
fun(pos_arg1=1, pos_arg2=2, key_arg_1=3) # Passing positional argument as keyword argument
def fun(pos_arg1, pos_arg2, key_arg_1 = None):
    print("positional arguments: ", pos_arg1, pos_arg2)
    print("Keyword arguments: ", key_arg_1)

# It will work
fun(1, 2, 3) # Passing keyword argument as positional argument

# It will also work
fun(pos_arg1=1, pos_arg2=2, key_arg_1=3) # Passing positional argument as keyword argument
def fun(pos_arg1, pos_arg2, key_arg_1 = None):
    print("positional arguments: ", pos_arg1, pos_arg2)
    print("Keyword arguments: ", key_arg_1)

# It will work
fun(1, 2, 3) # Passing keyword argument as positional argument

# It will also work
fun(pos_arg1=1, pos_arg2=2, key_arg_1=3) # Passing positional argument as keyword argument

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New way

def fun(pos_arg1, pos_arg2, /, key_arg_1 = None):
    print("positional arguments: ", pos_arg1, pos_arg2)
    print("Keyword arguments: ", key_arg_1)
# It will work
fun(1, 2, 3) # Passing keyword argument as positional argument
# It won't work
fun(1, pos_arg2=2, key_arg_1=3) # Passing one positional argument as keyword argument
fun(pos_arg1=1, pos_arg2=2, key_arg_1=3) # Passing both positional arguments as keyword argument
def fun(pos_arg1, pos_arg2, /, key_arg_1 = None):
    print("positional arguments: ", pos_arg1, pos_arg2)
    print("Keyword arguments: ", key_arg_1)

# It will work
fun(1, 2, 3) # Passing keyword argument as positional argument

# It won't work
fun(1, pos_arg2=2, key_arg_1=3) # Passing one positional argument as keyword argument
fun(pos_arg1=1, pos_arg2=2, key_arg_1=3) # Passing both positional arguments as keyword argument
def fun(pos_arg1, pos_arg2, /, key_arg_1 = None):
    print("positional arguments: ", pos_arg1, pos_arg2)
    print("Keyword arguments: ", key_arg_1)

# It will work
fun(1, 2, 3) # Passing keyword argument as positional argument

# It won't work
fun(1, pos_arg2=2, key_arg_1=3) # Passing one positional argument as keyword argument
fun(pos_arg1=1, pos_arg2=2, key_arg_1=3) # Passing both positional arguments as keyword argument

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6. Time with nanoseconds Precision

Did you ever need nanosecond precision in getting time to compare code performances? Python3.7 introduced new methods in the time library.

Old way

import time
start = time.time()
end = time.time()
print(end - start)
# Provides sub-second precision, though that precision varies by platform
# >> 2.7179718017578125e-05 Notice the precision is in e-05
import time

start = time.time()
end = time.time()

print(end - start)
# Provides sub-second precision, though that precision varies by platform
# >> 2.7179718017578125e-05 Notice the precision is in e-05
import time

start = time.time()
end = time.time()

print(end - start)
# Provides sub-second precision, though that precision varies by platform
# >> 2.7179718017578125e-05 Notice the precision is in e-05

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New way

import time
start = time.time_ns()
end = time.time_ns()
print(end - start)
# Provides nanosecond precision
# >> 47000 Notice the figure is in nanoseconds
import time

start = time.time_ns()
end = time.time_ns()

print(end - start)
# Provides nanosecond precision
# >> 47000 Notice the figure is in nanoseconds
import time

start = time.time_ns()
end = time.time_ns()

print(end - start)
# Provides nanosecond precision
# >> 47000 Notice the figure is in nanoseconds

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7. f-strings

Python3.6 introduced f-strings to provide an easy way of formatting strings.

Old way

a = 1
print("Value of a = {}".format(a))
a = 1

print("Value of a = {}".format(a))
a = 1

print("Value of a = {}".format(a))

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New way

a = 1
print(f"Value of a = {a}")
a = 1

print(f"Value of a = {a}")
a = 1

print(f"Value of a = {a}")

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8. Underscores in Numeric Literals

Python 3.6 introduced allowing adding underscores in numeric literals for better readability.

Old way

a = 1000000000000000 # try counting the number of 0's
print(type(a))
# >> <class 'int'>
a = 1000000000000000 # try counting the number of 0's

print(type(a))
# >> <class 'int'>
a = 1000000000000000 # try counting the number of 0's

print(type(a))
# >> <class 'int'>

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New way

a = 1_000_000_000_000_000
print(type(a))
# >> <class 'int'>
a = 1_000_000_000_000_000

print(type(a))
# >> <class 'int'>
a = 1_000_000_000_000_000

print(type(a))
# >> <class 'int'>

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9. Matrix Multiplication Operator

Python3.5 introduced a dedicated @ infix operator for matrix multiplication.

Old way

import numpy
x = numpy.ones(3)
m = numpy.eye(3)
print(x.dot(m))
import numpy

x = numpy.ones(3)
m = numpy.eye(3)

print(x.dot(m))
import numpy

x = numpy.ones(3)
m = numpy.eye(3)

print(x.dot(m))

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New way

import numpy # NumPy 1.10 has support for the new operator:
x = numpy.ones(3)
m = numpy.eye(3)
print(x @ m) # @ is the new matrix matrix-multiplication operator
import numpy # NumPy 1.10 has support for the new operator:

x = numpy.ones(3)
m = numpy.eye(3)

print(x @ m) # @ is the new matrix matrix-multiplication operator
import numpy # NumPy 1.10 has support for the new operator:

x = numpy.ones(3)
m = numpy.eye(3)

print(x @ m) # @ is the new matrix matrix-multiplication operator

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10. Approximate Equality

Python3.5 introduced dedicated methods to tell whether two values are approximately equal or “close” to each other.

Old way

a = 5.0
b = 4.99998
print(abs(a - b) <= 1e-5)
a = 5.0
b = 4.99998

print(abs(a - b) <= 1e-5)
a = 5.0
b = 4.99998

print(abs(a - b) <= 1e-5)

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New way

import math
a = 5.0
b = 4.99998
print(math.isclose(a, b, rel_tol=1e-5))
import math

a = 5.0
b = 4.99998

print(math.isclose(a, b, rel_tol=1e-5))
import math

a = 5.0
b = 4.99998

print(math.isclose(a, b, rel_tol=1e-5))

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Resources

1. Python3.11 Change-log
2. Python3.10 Change-log
3. Python3.9 Change-log
4. Python3.8 Change-log
5. Python3.7 Change-log
6. Python3.6 Change-log
7. Python3.5 Change-log

原文链接：10 Things You Didn’t Know You Could Do in Python3