4 Python Concepts That You Need To Know

Python is a great language to learn for its ease of use and its powerful application in big data. When first learning python, there are 4 powerful concepts that can be hard to understand depending on your prior programming experience. Today, we explain these concepts in detail to help you write cleaner code.

In python, a function is simply a pointer to a piece of code. Therefore, a function can call other functions, be a parameter, and can be assigned to a variable. While this may be hard to grasp at first, it is critical to understand especially when having to work on large codebases that have been worked on by multiple developers. Understanding how python handles each line of code, will enable you to easily read and dissect code.

Python lambdas are anonymous or unnamed functions. These functions are created on-the-fly when called and are deleted after execution. The body of a lambda must be an expression and follow the syntax outlined below.

lambda parameters: expression

Lambdas are a great way to create small anonymous functions that are needed only where they are located. Lambda are mainly used as an argument of other functions or along with built-in functions like filter.

List comprehension provides a shortcut to creating list in python. As you can see below, list comprehension allows you to consolidate a for loop and its logic into one line of code. Depending on the complexity, this can decrease code readability.

results = []
for name in directory:
results.append(name.upper())

# Above for loop written as list comprehension
results = [ name.upper() for name in directory ]

Other than a slight difference in syntax, the main difference between generators and comprehensions is that generators return a pointer to the values of the list instead of the list itself. Conserving the amount of memory used. In the example below, the syntactical difference between comprehensions and generators can be seen. List comprehension uses square brackets, whereas generators use parenthesis. By adding a print statement after your list comprehension and generator, it will be easier to see what the output is for each.

results = (name.upper() for name in directory)

In python a switch or case statement does not exist. Which leads developers to use elseif statements in situations where a switch or case statement would be used in other languages. At times this will suffice, but there are times where using a dictionary will provide the same functionality in a cleaner fashion. For instance, if we have four elseif statements that call a different function depending on the case. Instead of having multiple elseif statements, we can create a dictionary with each case being a key and each function needed assigned as the value to its respective key. This conversion can be seen below.

test_input = '1'

# Traditional elif statement
if test_input == '1':
print('one')
elif test_input == '2':
print('two')

# Elif statement converted into dictionary
case_dict = {
'1': 'one',
'2': 'two'
}

test_output = case_dict[test_input]
print(test_output)