Python Development

Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Its high-level built in data structures, combined with dynamic typing and dynamic binding, make it very attractive for Rapid Application Development, as well as for use as a scripting or glue language to connect existing components together. Python’s simple, easy to learn syntax emphasizes readability and therefore reduces the cost of program maintenance. Python supports modules and packages, which encourages program modularity and code reuse. The Python interpreter and the extensive standard library are available in source or binary form without charge for all major platforms, and can be freely distributed.

Often, programmers fall in love with Python because of the increased productivity it provides. Since there is no compilation step, the edit-test-debug cycle is incredibly fast. Debugging Python programs is easy: a bug or bad input will never cause a segmentation fault. Instead, when the interpreter discovers an error, it raises an exception. When the program doesn’t catch the exception, the interpreter prints a stack trace. A source level debugger allows inspection of local and global variables, evaluation of arbitrary expressions, setting breakpoints, stepping through the code a line at a time, and so on. The debugger is written in Python itself, testifying to Python’s introspective power. On the other hand, often the quickest way to debug a program is to add a few print statements to the source: the fast edit-test-debug cycle makes this simple approach very effective.

The first thing you will learn in Python is how to create variables. They are fundamental to everything we do in programming. Fortunately, they’re also really easy, which makes them a great place to start. Variables are essentially little boxes in your programs that can store data. You can give the variables names, store data inside them, and get that data back later when you need it. This data can be simple like numbers and text, or it can be complex, like entire webpages and spreadsheets. One of the simplest types of data is numerical data. Numbers are important for many things in programming. Whether you are keeping track of the number of users on your website, processing payments, or computing important statistics as part of data analysis, numbers are everywhere.

So, here are the topics I recommend you learn this week:

  • How to store numbers in variables and access the values stored in them.
  • How to use variables to perform mathematical operations on numbers (+, -, *, /, %, //).
  • How to print the value of a variable to the screen using Python’s print() function.
These fundamental building blocks will form the foundation of everything there is to come; I hope you’re excited!
Strings, in coding terms, are simply pieces of text. Strings are used to represent usernames, email addresses, messages, URLs, names of cities in a dataset, and other kinds of textual information.

You can print strings, stick them together, cut certain pieces out of them, replace certain pieces with other pieces, and so much more.

This week, I suggest you learn how to create strings in Python, and the various manipulations you can do with them.

Start by learning:
  • How to ask the user a question and save their input in a variable.
  • How to add two strings together.
  • How to convert a string to all uppercase/lowercase/title case.
  • How to strip off whitespace from a string.
  • How to replace a certain character in a string with another.
In this week, you will use your knowledge of variables, numbers, and strings, to learn how to make your Python programs think!

Logic and conditional flow allow you to control how your programs run. They allow you to decide whether certain pieces of code will run or not based upon whether a certain condition is true or false.

While it may sound complicated, it really isn’t. In fact, we have already used logic together when we gave our students a grade based on their score.

Logic is one of my favorite topics in programming. Being able to create a program that can decide what to do based on certain conditions opens a whole new world of possibilities.

When learning logic, focus on the following topics:

  • If statements (if, elif, else)
  • Comparison operators (>, <, ==, !=, >=, <=)
  • The Boolean data type (True, False)
  • Conditional operators (and, or, not)

Try to put these topics together to build a little program. For example, try building a program that will ask a user for their age, and then decide whether they can watch a certain movie or not.

Logic goes hand in hand with a very powerful concept called the while loop. So, for this week I want you to try to master while loops too.

The link between the two is that a condition is evaluated to be True or False, and then something happens based on that evaluation. In the case of logic, the action happens once. In the case of a while loop, the action happens continually, as long as the condition is True.

For this week, try to learn the following additional topic:

  • While loops
This is a very exciting week and will essentially give you programming superpowers — have fun!
Up until now, you have been using variables that contain a single piece of data: one number or one string.

Data structures allow you to put multiple pieces of data together into one variable. Think of storing a whole bunch of numbers, a whole bunch of strings, or even a mixture of both!

There are two main data structures in Python: lists and dictionaries. There are others, of course, but dictionaries and lists are probably the two most common ones.

Lists allow you to store data in a certain order, like so:

my_numbers_list = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]

A dictionary allows you to store data and store it under certain “keys”. In the example below, “name”, “class”, and “score” are keys, and each has associated values.

student_dictionary = { ‘name’: ‘Sarah’, ‘class’: ‘The Python Bible’, ‘score’: 100 }

For–loops link well with data structures like how while loops link well with logic. They allow you to repeat an action for every item in a data structure.

In this way, for-loops allow you to write a single piece of code and repeat its action (or set of actions) potentially thousands of times.

This week, try to master the following concepts:

  • How to add items to a list
  • Extracting elements from a list
  • Replacing elements in a list
  • Dictionaries
  • Adding entries to a dictionary
  • Extracting values from a dictionary based on their key
  • Replacing values in a dictionary using keys
  • Using a for loop to iterate over a list
  • Using a for loop to iterate over a dictionary
In past weeks, you will have already learned how to use many functions. Perhaps you used a function to make a string all uppercase, or perhaps you used a function that will add an item to a list.

But this week, you will learn how to create your very own functions! Oooh, how exciting!!

A function is a piece of code that will perform a certain action (function) based on the inputs you give it, and maybe even return some output.

For example, when we use the print() function, we give the print() function a certain piece of text to print to the screen.

The print() function will take the input you give it, perform some rather complicated actions behind the scenes, and then make text magically appear on the screen.

Similarly, your functions will take inputs, do something, and give results.

This is very useful for making your code easier to read and for breaking your code up into manageable, well-defined chunks. These are invaluable skills to have as your projects become larger and more sophisticated.

So, for this week, try to learn the following topics:

  • How to define a function
  • How to give inputs to a function
  • The difference between an argument and a parameter
  • How to set default parameters
  • How to return a value from a function
You are doing great and have come such a long way! But if I know you, you want to take your Python skills to the next level.

It’s time for you to learn Object-Oriented Programming.

As the word “oriented” hints in its name, Object-oriented programming is really just a new way—a new orientation, if you will—of approaching programming.

Instead of thinking of a program as a list of commands that you execute in sequence like in sequential programming, object-oriented programming is all about creating and using objects.

So, what are objects? Well, objects can be anything. We use objects to model concepts that are useful to our programs. We can model users; we can model buttons; anything you can think of can be an object and modeled in your code.

Python itself is intended to be used in an Object-Oriented way. The reason for this is that by creating objects and modeling their behavior, we can build really sophisticated and powerful programs in a relatively straightforward way (once you get the hang of it, at least).

So, the topics I suggest you learn in this final week are:

  • The difference between objects + classes, and how they relate
  • How to create classes and objects
  • How constructors work in Python classes
  • How to define an object’s states using class variables and instance variables
  • How to define an object’s behaviors using methods
  • Introduction to Python and Django
  • Setting up the development environment (Python, Django, and a text editor/IDE)
  • Creating a new Django project
  • Understanding the project structure
  • Creating and configuring a virtual environment
  • Running the development server
  • Creating and configuring a Django app
  • Creating and configuring database models
  • Understanding Django’s MTV (Model-Template-View) architecture
  • Implementing views and URL patterns
  • Creating and rendering Django templates
  • Working with static files (CSS, JavaScript, images)
  • Django forms and form handling
  • Implementing user registration and authentication
  • Managing user sessions and cookies
  • Working with Django’s built-in admin interface
  • Customizing the admin interface
  • Django ORM (Object-Relational Mapping) and database queries
  • Querying and filtering data
  • Implementing pagination and sorting
  • Implementing CRUD (Create, Read, Update, Delete) operations
  • Working with Django’s built-in authentication system
  • Implementing user roles and permissions
  • Handling file uploads
  • Implementing search functionality
  • Working with Django middleware
  • Understanding and implementing Django’s security features
  • Implementing RESTful APIs with Django Rest Framework
  • Deploying a Django application to a hosting provider
  • Implementing caching to improve performance
  • Using Django’s testing framework for unit tests
  • Working with third-party Django packages and libraries
  • Implementing internationalization and localization
  • Handling errors and exceptions in Django
  • Performance optimization techniques for Django
  • Best practices for Django development