Rajesh JoshiHistory ⏳
I was looking into the code base of a library few years back ⌚, and I saw something strange 🤯. It goes like -
@try
def fetch(url: str):
resp = request.get(url)
return resp.json()
So the definition of fetch function is clear enough, but what the hack is this @try 🤯 just before the function definition?
That was a Decorator 🤔
Decorators are very powerful and useful tool in Python as it allows programmers to modify the behaviour of a function. Decorators allow us to wrap another function in order to extend the behaviour of the wrapped function.
Example 1: Functions as an object 🤔
def upper_text(text):
return text.upper()
print(upper_text('Hello'))
func = upper_text
print(func('Hello'))
HELLO
HELLO
Example 2: Function as an argument 🤔
def upper_text(text):
return text.upper()
def lower_text(text):
return text.lower()
def func(func):
# storing the function in a variable
msg = func("Hello")
print(msg)
func(upper_text)
func(lower_text)
HELLO
hello
Example 3: Returning function 🤔
def create_adder(x):
def adder(y):
return x + y
return adder
add_15 = create_adder(15)
print(add_15(10))
25
Example 4: Decorator 🚀
# importing libraries
import time
import math
# decorator to calculate duration
# taken by any function.
def calculate_time(func):
# added arguments inside the inner1,
# if function takes any arguments,
# can be added like this.
def inner1(*args, **kwargs):
# storing time before function execution
begin = time.time()
func(*args, **kwargs)
# storing time after function execution
end = time.time()
print("Total time taken in : ", func.__name__, end - begin)
return inner1
# this can be added to any function present,
# in this case to calculate a factorial
@calculate_time
def factorial(num):
# sleep 2 seconds because it takes very less time
# so that you can see the actual difference
time.sleep(2)
print(math.factorial(num))
# calling the function.
factorial(10)
3628800
Total time taken in : factorial 2.0061802864074707
Back to History 😃
So, what was that?
@try
def fetch(url: str):
resp = request.get(url)
return resp.json()
The definition of try was like this -
def try(func):
def exe(*args, **kwargs):
try:
return func(*args, **kwargs)
except Exception as e:
return {
"message": "Error while processing the request",
"details": str(e)
}
return exe
Hit Like ❤️ and share your thoughts in the comments 💬
Thank you
cheers
