Python refresher — Part 2

Ndamulelo Nemakhavhani

Jan 16, 2019·2 min read

1. Generators

• Function that returns an iterator — i.e. An item that we can iterate over one value at a time
• A generator can preserves all variables and states when a yield is encountered. Thereafter, when a next call is encountered the function carries on the execution from where it left off.

def days_of_the_week():
    n = 1
    yield n    n += 1
    yield n    n += 1
    yield n>>> print( days_of_the_week() )  # 1>>> print( days_of_the_week() )  # 2>>> print( days_of_the_week() )  # 3

2. List comprehensions

• List comprehensions are formed by creating a new list by applying some logic to all items in the original list.
• For example, to square all entries in a list:

>>>  a = [3, 4, 5]
>>> b = [x ** x for x in a ]
    # b = [9, 16, 25]

3. Optional arguments

• It is possible to write functions with an arbitrary number of arguments

def sum( a, b, *optional):
    if len(optional) != 0:
        return sum(a, b) + sum(optional)
    else:
        return (a + b)>>> sum(3,1)  # 4
>>> sum(3,1,4,5)  # 13

• Consequentially, a & b are called required arguments, whereas optional is a list of optional arguments.
• The optional arguments can also be represented as a hash-map if **optional is used instead of *optional.

4. Regular expressions

• Regular expressions can be leveraged to uncover complex patterns from strings.
• Python comes with a built in re module that can be used for this purpose

import re>>> string = "hakuna matata"
>>> re.match( r'(.*)\n (.*?) .*', string, noflags)
    # no match

• Ref: https://.tutorialspoint.com/python/python_reg_expressions.html

5. Partial functions

• Partial functions are commonly used in tasks where you need to pre-populate some arguments in a function such as in the example below:

def _send_email(to, subject, body):  
    send_mail(subject,
              body, 
             settings.EMAIL_HOST_USER,   )   email_admin      = partial(_send_email, to="admin@example.com") email_general_it = partial(_send_email, to="it@example.com") email_marketing  = partial(_send_email, to="marketing@example.com") email_sales      = partial(_send_email, to="sales@example.com")

• This way, you only need to provide the remaining two arguments when calling the generated higher order functions.
• Ref: https://chriskiehl.com/article/Cleaner-coding-through-partially-applied-functions

6. Closures

• A closure is just a function that contains a nested function that uses one or more of the enclosing function’s variables.

def make_multiplier_of(n):
    def multiplier(x):
        return x * n
    return multiplier# Multiplier of 3
times3 = make_multiplier_of(3)# Output: 27
print(times3(9))

• Ref: https://www.programiz.com/python-programming/closure

7. Decorators

• A decorator simply modifies a function and return a new function
• This essentially means to augment a core function with additional functionality.