Code structure

Last updated on 2024-12-09 | Edit this page

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Overview

Questions

How to structure a code in a scalable and reusable way?

Objectives

Learn to use functions and classes
Understand how to organise your code in modules and packages

Introduction

When you’re writing code, making it consistent and well-structured is just as essential as ensuring it produces the correct result. You should think about how you structure your code as you write it, as this will make it easier to read and maintain in the future both by yourself and others.

It’s important to follow the design principles of the programming language you are using. Python is known as an object-oriented programming language, which means Python code is structured around creating, using, and interacting with code objects. There are many different types of objects in Python, such as basic integers or text strings, lists or dictionaries which contain multiple objects, and functions that operate on objects. It’s also encouraged to create your own classes of objects, to make your code more modular and reusable.

When your code grows in size and complexity, it’s a good idea to split it into multiple files, known as modules, and organise these modules into packages. This makes your code easier to manage and maintain, and allows you to reuse code across multiple projects.

Functions

Functions are a way to group code together that performs a specific task. There are many built-in functions in Python, such as print() to output values or len() to get the length of a list. But you can also create your own functions, to perform tasks that you need to do multiple times.

Functions are defined using the def keyword, followed by the function name and a set of parentheses containing any parameters the function takes. The function body is then indented and contains the code that the function will execute. The return keyword is used to specify what the function should output.

Below is a very basic function that simply takes two parameters and returns their sum. Once you have defined a function, you can call it by using its name and passing in the required parameters as arguments to the function. In this case the parameters a and b are set to 2 and 6 respectively, and the result of the function is stored in the result variable:

PYTHON

def add(a, b):
    return a + b

result = add(3, 5)
print(result)

OUTPUT

Whitespace

If you’re used to other programming languages like C or R, you might be surprised to see that Python does not use curly braces {} to define blocks like functions. Instead, Python uses indentation to define blocks of code, either with spaces or tabs (known as whitespace).

It’s important to be consistent with your indentation, as mixing different numbers of spaces or tabs can cause errors. Most code editors will automatically indent and convert tabs to spaces when writing Python.

This is obviously a very simple example, but functions can be much more complex and can take multiple parameters, return multiple values, or raise errors if something goes wrong.

Any function acts as a reusable block of code that can be called multiple times within your program. Building your code out of small, modular functions makes it easier to read and maintain, by not having to repeat the same code multiple times you save space and only need to edit the code in one place when making changes. It’s also easier and more reliable to test the output of individual functions to make sure they work correctly, rather than having to run the entire program. There will be a future session on Testing and Continuous Integration which will cover this in more detail.

Scope

When you define a variable inside a function, it is only accessible within that function. This is known as the scope of the variable. If you try to access a variable that is defined inside a function from outside the function, you will get an error:

PYTHON

def my_function():
    x = 10
    return x

result = my_function()
print(x)

OUTPUT

NameError: name 'x' is not defined

Anything defined outside of a function is said to be in the global scope, and can be accessed from anywhere in the program (including within functions). However, it’s generally considered good practice to avoid using global variables, as they can make your code harder to understand and debug.

Challenge 1

What will be the output of this code?

PYTHON

x = 5
y = 10

def my_function(z):
    x = 20
    return x + y + z
result = my_function(3)

print('x:', x)
print('y:', y)
print('Result:', result)
print('z:', z)

Show me the solution

OUTPUT

x: 5
y: 10
Result: 33
NameError: name 'z' is not defined

The x variable inside the function is a different variable to the x variable outside, so changing it inside the function does not affect the global x variable.

The y variable is accessible inside the function because it is defined in the global scope.

The result variable is the sum of the function’s x variable, the global y variable and the argument z.

The z variable is not defined outside the function, so trying to print it in the main body of the script will raise an error.

Classes

Classes are a way to group functions and data together into a single object. Classes act as a blueprint for creating objects, which are then called instances of the class.

Similar to functions, classes are defined using the class keyword, followed by the class name. The class body is then indented and contains any properties or methods (i.e. functions) that the class has.

Below is a very simple class for a Rectangle object, which has properties for its width and height, as well as a method to calculate its area:

PYTHON

class Rectangle:
   width = 5
   height = 3

    def get_area(self):
        return self.width * self.height

The `self` parameter

Methods in a class always define self as the first parameter, which is used as a reference to the instance of the class that the method is being called on. In this case the get_area method uses the width and height properties of the Rectangle instance. You can actually call this parameter anything you like, but self is the convention in Python.

You can then create an instance of this class by calling the class name as if it were a function, and you can access its properties and methods using the . operator:

PYTHON

my_rectangle = Rectangle()
print('This rectangle has a width of', my_rectangle.width, 'and a height of', my_rectangle.height)
print('Its area is', my_rectangle.get_area())

OUTPUT

This rectangle has a width of 5 and a height of 3
Its area is 15

In this case the class is not very reusable, as the width and height are fixed. You can pass arguments when creating an instance of the class by defining a special __init__() method. The __init__() method at is called whenever a new instance of the class is created, and it can take values to set the initial state of the object. In the example below, the Rectangle class takes width and height parameters and stores them as properties of the self object (i.e. the instance of the class that is being created):

PYTHON

class Rectangle:
    def __init__(self, width, height):
        self.width = width
        self.height = height

    def get_area(self):
        return self.width * self.height

my_rectangle = Rectangle(10, 20)
print('This rectangle has a width of', my_rectangle.width, 'and a height of', my_rectangle.height)
print('Its area is', my_rectangle.get_area())

OUTPUT

This rectangle has a width of 10 and a height of 20
Its area is 200

“Dunder” methods

In Python, methods that start and end with double underscores are called “dunder” (short for “double underscore”) or “magic” methods. These methods are special and have specific built-in meanings, such as __init__() being called when an instance of a class is initialised. We’ll see more examples of “dunders” later in this section.

Classes are a powerful way to structure your code, as they allow you to group related functions and data together in a way that is reusable and easy to understand.

Challenge 2

In the code below, we have multiple lists representing items in a grocery store. Each fruit has a name, price, and the number in stock.

PYTHON

fruits = ['apple', 'banana', 'orange']
fruit_prices = [1.00, 0.50, 0.75]
fruit_count = [10, 20, 15]

Create a class called Stock that has properties called name, price, count, and two methods: display() that prints out the name and unit price of the fruit, and get_total_value() that returns the total value of the stock.

Then create a new list of Stock objects, and call the display() method on each object.

Show me the solution

PYTHON

class Stock:
    def __init__(self, name, price, count):
        self.name = name
        self.price = price
        self.count = count

    def display(self):
        print(f'Each {self.name} costs £{self.price}')

    def get_total_value(self):
        return self.price * self.count


fruits = [
    Stock('apple', 1.00, 10),
    Stock('banana', 0.50, 20),
    Stock('orange', 0.75, 15)
]
for fruit in fruits:
    fruit.display()

OUTPUT

Each apple costs £1.0
Each banana costs £0.5
Each orange costs £0.75

Challenge 3

Now, create a Shop class that has a property called stock that is a list of Stock objects. The Shop class should have a method called display_stock() that calls the display() method on each item in the stock list, and a method called get_total_stock_value() that returns the total value of all items in the stock list.

Then create a new Shop object with the fruits list as the input, and call the display_stock() and get_total_stock_value() methods.

Show me the solution

PYTHON

class Shop:
    def __init__(self, stock):
        self.stock = stock

    def display_stock(self):
        for item in self.stock:
            item.display()

    def get_total_stock_value(self):
        total = 0
        for item in self.stock:
            total += item.get_total_value()
        return total

shop = Shop(fruits)
shop.display_stock()
print('Total stock value:', shop.get_total_stock_value())

OUTPUT

Each apple costs £1.0
Each banana costs £0.5
Each orange costs £0.75
Total stock value: 31.25

Naming conventions

Note that in each of these examples, the variables, properties and class names are written as nouns (e.g. result, Rectangle, width or Shop), while the functions and class methods are lowercase verbs or short phrases (e.g. add(), get_area() or display_stock()). This is a common convention in Python, and following it can help you write more readable code and understand the difference between objects and functions more easily.

We will see more examples of coding conventions like this in later sections.

Scripts and Modules

A Python script is a file containing Python code that can be executed by the Python interpreter. You can run a script by calling the Python interpreter with the script file as an argument, like this:

BASH

python my_script.py

When you’re writing a large program, it’s a good idea to split your code into multiple files to make it easier to manage, and to make it easier to reuse code in other projects. Each file containing Python code is called a module, and you can import modules into scripts and other modules to use the functions and classes they contain.

For example, you could create a file called calculator.py that contains the add() function we defined earlier, as well as other functions for subtraction, multiplication, and division.

PYTHON

"""calculator.py"""

def add(a, b):
    return a + b

def subtract(a, b):
    return a - b

def multiply(a, b):
    return a * b

def divide(a, b):
    return a / b

Now, in another script or module, you can import the calculator module and use its functions by using the import keyword:

PYTHON

"""script.py"""
import calculator

result = calculator.add(5, 3)
print(result)

OUTPUT

You can also import specific functions or classes from a module, rather than importing the whole module. This can be useful if you only need one or two functions, as it saves some time and can make your code more readable:

PYTHON

from calculator import add

result = add(5, 3)

Python comes with a lot of built-in modules that you can import and use in your code, collectively known as the Standard Library. These work in the same way, for instance if you wanted trigonometric functions you can do from math import sin, cos, tan and then use those functions in your code.

Running a module as a script

In some cases, you might want a mixture of code that executes when the module is run as a script as well as functions and classes that can be imported into other modules. Too keep the two separate, you can use another special “dunder” method called __name__. This is a built-in variable that is set to '__main__' when the module is run as a script, and is set to the module name when the module is imported into another module.

As such, if you include a check for if __name__ == '__main__': in your module, you can define code that only runs when the module is run as a script:

PYTHON

"""calculator.py"""
def add(a, b):
    return a + b

if __name__ == '__main__':
    result = add(5, 3)
    print('Test result:', result)

BASH

$ python calculator.py
Test result: 8

If you didn’t include the if __name__ == '__main__': check, then every time you tried to import the add() function from the calculator module, the test code would run as well and print out the result.

Packages

Once you have a collection of modules that you want to reuse across multiple projects, you can organise them into a package. A package is a directory containing multiple modules, along with a special __init__.py file that tells Python that the directory is a package (this is yet another example of a “dunder” being used as a special marker in Python, in this case being used to signify that a directory is importable).

For example, you could create a package called my_package that contains the calculator module we defined earlier, as well as a new module called geometry that contains functions for working with shapes. When organising these modules into a package, the directory structure would look like this:

my_package/
    __init__.py
    calculator.py
    geometry.py

The __init__.py file can be empty, but it can also contain code that runs when the package is imported.

You can then import the modules from the package in the same way as before, but you need to include the package name either as a prefix or by using the from keyword:

PYTHON

import my_package.calculator
my_package.calculator.add(5, 3)

OR

from my_package import calculator
calculator.add(5, 3)

OR

from my_package.calculator import add
add(5, 3)

If your package grows large enough, you can also create sub-packages within your package by creating subdirectories with their own __init__.py files. This allows you to organise your code into a hierarchical structure that makes it easier to manage and understand.

Challenge 4

A researcher has all of their code for a project in a single Python file, and they want to split it into multiple modules within a package. Here is a list of the functions and classes they have defined in their script:

load_data(): a function that reads data from a file
clean_data(): a function that removes any missing values from the data
plot_data(): a function that plots the data
Data: a class that holds the data, returned by load_data()
Model: a class that represents a machine learning model created from the data
test_data(): a function that tests the data class is working correctly
test_model(): a function that tests the model class is working correctly
run_experiment(): a function that runs the entire experiment, taking a data file as an input

There is also a test file called test_data.csv that contains some example data, and is used by the test_data() and test_model() functions.

How would you organise this code into a package?

Show me the solution

Here is an example of how you could organise the code into a package:

research_project/
    __init__.py
    data/
        __init__.py
        data.py
    model/
        __init__.py
        model.py
    plot/
        __init__.py
        plot.py
    scripts/
        __init__.py
        run_experiment.py
    tests/
        __init__.py
        test_data.csv
        test_data.py
        test_model.py

The data module would contain the load_data() and clean_data() functions and the Data class.
The model module would contain the Model class definition.
The plot module would contain the plot_data() function.
The scripts module would contain the run_experiment() function in a standalone script.
The tests module would contain the test_data() and test_model() functions, as well as the test_data.csv file.

For instance, if you wanted to load and plot the data in a different script, you could import the data and plot modules like this:

PYTHON

from research_project.data import load_data
from research_project.plot import plot_data

data = load_data('data.csv')
plot_data(cleaned_data)

Although it seems like a lot of files for a small amount of code, this structure makes it easier to manage and maintain the project over time, and will make it easier to reuse the code in other projects in the future.

Once you have your package organised, you can share it with others by using a code hosting platform like GitHub, or uploading it to the Python Package Index (PyPI, https://pypi.org/). If you do this there are some additional files you should include to make your package more user-friendly, such as a README file that explains what the package does and how to use it, and a LICENSE file that specifies the terms under which the code can be used. There is another session on Packaging which will go into more detail on how to create and share Python packages.

Final exercise : Rewriting a Python Script

In this final exercise, you will rewrite a Python script that is poorly structured and difficult to read, with a large amount of repeated code.

Challenge 5

You can find the script here: student_scores.py.

This Python script is designed to read in a data file containing student names and scores (all generated randomly!), although here we just include the data as a text string in the script to save having to download a separate file.

After checking there are no errors with the input, the script then goes through each student, calculates their total score across the three exams and prints out a summary of the data. It then calculates the average score for each assignment, and prints out the student with the highest total score in the class.

You can download it and run it on your local computer using python test_script.py. The output should look like this:

OUTPUT

studentid  firstname  surname    score1  score2  score3  total
39816      Fiona      Ellis      15      18      16      49
40859      Philip     Holdcroft  12      17      15      44
71625      Kathleen   Ingram     20      19      19      58
91462      David      Nicholson  14      16      18      48
97297      Mark       Walch      18      20      17      55
Average score1: 15.80
Average score2: 18.00
Average score3: 18.00
Student with highest total: Kathleen Ingram (58.00)

Your task is to rewrite this script using functions and classes to make it more modular and reusable. You can also move code out of the script into separate files and modules if you think it will make the code easier to manage.

Make sure when you’re done that the output of the script is the same as the original.

Code structure

Overview

Questions

Objectives

Introduction

Functions

PYTHON

OUTPUT

Whitespace

Scope

PYTHON

OUTPUT

Challenge 1

PYTHON

Show me the solution

OUTPUT

Classes

PYTHON

The self parameter

PYTHON

OUTPUT

PYTHON

OUTPUT

“Dunder” methods

Challenge 2

PYTHON

Show me the solution

PYTHON

OUTPUT

Challenge 3

Show me the solution

PYTHON

OUTPUT

Naming conventions

Scripts and Modules

BASH

PYTHON

PYTHON

OUTPUT

PYTHON

Running a module as a script

PYTHON

BASH

Packages

PYTHON

Challenge 4

Show me the solution

PYTHON

Final exercise : Rewriting a Python Script

Challenge 5

OUTPUT

The `self` parameter