Learning Python – Part 3

You can become a serverless blackbelt. Enrol to my 4-week online workshop Production-Ready Serverless and gain hands-on experience building something from scratch using serverless technologies. At the end of the workshop, you should have a broader view of the challenges you will face as your serverless architecture matures and expands. You should also have a firm grasp on when serverless is a good fit for your system as well as common pitfalls you need to avoid. Sign up now and get 15% discount with the code yanprs15!


A while back I decided to try and learn Python for the hell of it as it seems like an interesting language and has some of the most concise and user-friendly syntax. Having spent some time going through a number of different learning sources and materials (like the official site python.org which has a very helpful tutorial section) I have put together a set of notes I made as I was learning and hopefully they can be useful to you as a quick list of how-to code snippets.

All the code snapshots I’m showing here are taken from the IDLE Python shell.


A set is an unordered collection with no duplicate elements. To create a set:


notice how the duplicate was removed?


You can also use a string as a sequence of char objects and turn it into a set:



Now, let’s use this two simple sets to illustrate some basic set operations:


Set difference:


Set union:


Set intersect:


Exclusive (in one or the other but not both):




Dictionaries are key value pairs indexed by keys, which can be any immutable type. To create an empty dictionary:



You access the elements in a dictionary using square brackets [], you can find out all the keys and values in a dictionary using the keys and values methods:



You can also use the del statement to delete a key value pair:



You can create a dictionary using the dict() method and pass in a sequence of tuples:


if the keys are all strings, you can even do this:



To loop through dictionaries, the key and corresponding value can be retrieved at the same time using the iteritems() method:




Use a while loops to generate the Finobacci sequence:



For loops:



Mutable sequences like lists should not be modified at the same time as looping through it, and instead should be done on a copy:


what would happen if we don’t use a copy here? This code will get stuck in an infinite loop:



The else and break statement:

Loops in Python can have an else clause which is executed when the loop terminates through exhaustion of the list (for for loops) or when the loop condition becomes false (for while loops), but it won’t execute if the loop is terminated with the break statement:



The continue statement:



The pass statement:

It does nothing, often used to create a minimal class..




Use the def keyword to define a function:


Note that the first string is a docstring that can be used by some tools to generate documentations.


Arguments are passed using call by reference, as the argument is always an object reference not the value of the object.

Every function has a return value, if nothing is returned then a special None value is returned. Writing of the None value is usually suppressed by the interpreter, but you can see it using print:



Use the return keyword to return values from a function:



Default argument values:



The default values are evaluated once and once only, at the point of function definition:


however, it works differently with mutable objects such as lists, dictionaries etc.


notice how the second function call didn’t use the default empty list? That’s because the object referenced by the variable l is mutable and its state was mutated by the first add_item call.


You can also call the function using keyword arguments if they appear AFTER the regular parameters have been passed in:


note that keyword arguments cannot be provided twice.


You can define an arbitrary argument list which takes in a tuple:



Similarly, you can take in a dictionary:



Interestingly, the reserve of the above is true too! You can take a tuple and unpacking it with the * operator:



Or take a dictionary and unpacking it with the ** operator:





Liked this article? Support me on Patreon and get direct help from me via a private Slack channel or 1-2-1 mentoring.
Subscribe to my newsletter

Hi, I’m Yan. I’m an AWS Serverless Hero and I help companies go faster for less by adopting serverless technologies successfully.

Are you struggling with serverless or need guidance on best practices? Do you want someone to review your architecture and help you avoid costly mistakes down the line? Whatever the case, I’m here to help.

Hire me.

Skill up your serverless game with this hands-on workshop.

My 4-week Production-Ready Serverless online workshop is back!

This course takes you through building a production-ready serverless web application from testing, deployment, security, all the way through to observability. The motivation for this course is to give you hands-on experience building something with serverless technologies while giving you a broader view of the challenges you will face as the architecture matures and expands.

We will start at the basics and give you a firm introduction to Lambda and all the relevant concepts and service features (including the latest announcements in 2020). And then gradually ramping up and cover a wide array of topics such as API security, testing strategies, CI/CD, secret management, and operational best practices for monitoring and troubleshooting.

If you enrol now you can also get 15% OFF with the promo code “yanprs15”.

Enrol now and SAVE 15%.

Check out my new podcast Real-World Serverless where I talk with engineers who are building amazing things with serverless technologies and discuss the real-world use cases and challenges they face. If you’re interested in what people are actually doing with serverless and what it’s really like to be working with serverless day-to-day, then this is the podcast for you.

Check out my new course, Learn you some Lambda best practice for great good! In this course, you will learn best practices for working with AWS Lambda in terms of performance, cost, security, scalability, resilience and observability. We will also cover latest features from re:Invent 2019 such as Provisioned Concurrency and Lambda Destinations. Enrol now and start learning!

Check out my video course, Complete Guide to AWS Step Functions. In this course, we’ll cover everything you need to know to use AWS Step Functions service effectively. There is something for everyone from beginners to more advanced users looking for design patterns and best practices. Enrol now and start learning!