Assignment expressions
Use new syntax (the “walrus operator”, :=) to assign values to variables as part of an expression ...
def say_hello():
print("Hello")
if (greeting := say_hello() is not None):
print(f"{greeting}, World!")
# We had been required to declare and assign value to a variable first.
greeting = say_hello()
print(f"{greeting}, World!")Positional-only parameters
Use new syntax (/) to indicate that some function parameters must be specified positionally (i.e., cannot be used as keyword arguments) ...
def sum(a, b , c=None, /):
result = a+b
if c is not None:
result += c
return result
>>> sum(1, 2) # valid
>>> sum(1, 2, 3) # valid
>>> sum(a=1, b=2) # invalid
>>> sum(1, 2, c=3) # invalidf-strings now support = for quick and easy debugging
f'{expr=}' expands to the text of the expression, an equal sign, then the repr of the evaluated expression ...
price = 6250
tax = int(6250 * 0.2)
print (f"Total price is {price + tax=} dollars.")
# We had not been able to use = in f-strings
total = price + tax
print (f"Total price is {total} dollars.")functools.lru_cache()
It can now be used as a decorator rather than as a function returning a decorator ...
from functools import lru_cache
@lru_cache(maxsize=None)
def fib(n):
if n < 2:
return n
return fib(n-1) + fib(n-2)
>>> [fib(n) for n in range(16)]
[0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610]
>>> fib.cache_info()
CacheInfo(hits=28, misses=16, maxsize=None, currsize=16)It is not necessary to write a memoization function (below) anymore.
def memoize(func):
cache = dict()
def memoized_func(*args):
if args in cache:
return cache[args]
result = func(*args)
cache[args] = result
return result
return memoized_funcYou can read more about memoization in Python here.
math.prod()
Calculate the product of all the elements in the input iterable. The default start value for the product is
1. When the iterable is empty, return the start value.
from math import prod
>>> prod(range(1,5)) # 24Why didn't this exist already