130+ Interview Questions
(and answers) on Concurrent Futures
Challenge Your Knowledge of the ThreadPoolExecutor and ProcessPoolExecutor classes in Python
Discover pointed interview questions (and answers) allowing you to learn the concurrent.futures API.
Also invaluable for preparing for a job interview and evaluating candidates.
How well do you know
Python Concurrent Futures?
The concurrent.futures module provides the ability to launch parallel and concurrent tasks in Python using thread and process-based concurrency.
Importantly, the ThreadPoolExecutor and ProcessPoolExecutor offer the same modern interface with asynchronous tasks, Future objects, and the ability to wait on groups of tasks.
The problem is that few developers know about it, let alone, how to use it well.
The concurrent.futures module with the ThreadPoolExecutor and ProcessPoolExecutor classes offers the best way to execute ad hoc tasks concurrently in Python.
- Do you know how to handle task results in the order tasks finish?
- Do you know how to wait for the first task to fail?
- Do you know how many workers are created by default?
Discover 130+ interview questions on Python concurrent.futures.
- Study the questions and answers and improve your skill.
- Test yourself to see what you really know, and what you don’t.
- Select questions to interview developers on a new role.
Prepare for an interview or test your Python concurrent.futures skills today.
- 130+ questions to prepare you and test your knowledge of the API.
- 17 sections covering all aspects of the API, including functions and classes.
- 65 pages for on-screen reading open next to your editor.
- 2 formats (PDF and EPUB) for screen, tablet, and kindle reading.
- zip download that contains both formats of the ebook.
This book provides a large number of questions on what, how, and when to use the Python concurrent.futures API.
Choose Your Package:
All prices are in USD.
What topics are covered?
The questions are divided into 17 major topics, they are:
- Global Interpreter Lock
- Threads vs Processes
- Blocking Calls
- Executor Shutdown
- Submit Tasks
- Map Tasks
- Future Objects
- Future Result
- Future Status
- Done Callback Functions
- As Completed
Each topic has a preamble summarizing the types of questions to expect for the topic and why they are important.
Each question is listed in a heading format so that you can read it and think about it for self-study. This is followed by the answer.
Sometimes the answers will provide additional clarifying information and sample code.
Those questions that require a code example will provide a full code listing in the answer that may be used as a guide.
Who is this book for?
Let’s make sure you’re in the right place.
Specifically, this book is for:
- Developers that want to learn the concurrent.futures API with pointed questions.
- Developers that want to test their knowledge of the concurrent.futures API.
- Engineering managers that want to evaluate candidates for a job that requires Python concurrent.futures.
Get your copy now:
100% Money-Back Guarantee
(no questions asked)
I want you to actually learn asyncio so well that you can confidently use it on current and future projects.
I designed my book to read just like I’m sitting beside you, showing you how.
I want you to be happy. I want you to win!
I stand behind all of my materials. I know they get results and I’m proud of them.
Nevertheless, if you decide that my books are not a good fit for you, I’ll understand.
I offer a 100% money-back guarantee, no questions asked.
To get a refund, contact me with your purchase name and email address.
Frequently Asked Questions
This section covers some frequently asked questions.
If you have any questions. Contact me directly. Any time about anything. I will do my best to help.
What version of python do you need?
All code examples use Python 3.
Python 3.9+ to be exact.
Python 2.7 is not supported because it reached its “end of life” in 2020.
What format is the book?
You can read the book on your screen, next to your editor.
You can also read the book on your tablet, away from your workstation.
The ebook is provided in 2 formats:
- PDF (.pdf): perfect for reading on the screen or tablet.
- EPUB (.epub): perfect for reading on a tablet with a Kindle or iBooks app.
Many developers like to read technical books on their tablet or iPad.
How can you get more help?
The sections in this book were designed to be easy to read and follow.
Nevertheless, sometimes we need a little extra help.
A list of further reading resources is provided at the end of each section. These can be helpful if you are interested in learning more about the topic covered, such as fine-grained details of the standard library and API functions used.
If you ever have questions about the lessons or code in this book, you can contact me any time and I will do my best to help. My contact details are provided at the end of the book.
How many pages is the book?
The PDF is 65 US letter-sized pages.
Can you print the book?
Although, I think it’s better to work through it on the screen.
- You can search, skip, and jump around really fast.
- You can copy and paste code examples.
- You can compare code output directly.
Is there digital rights management?
The ebooks have no DRM.
Do you get free updates?
Each time I release an updated version, I will send you an email with a link so that you can download the latest version for free.
You can also email me any time and I will send you the latest version.
Can you buy the book elsewhere?
Can you read a sample?
You can read a book sample via google books “preview or via the amazon “look inside” feature:
About the Author
Hi, I’m Jason Brownlee, Ph.D.
I’m a Python developer, husband, and father to two boys.
I want to share something with you.
I am obsessed with Python concurrency, but I wasn’t always this way.
My background is in Artificial Intelligence and I have a few fancy degrees and past job titles to prove it.
You can see my LinkedIn profile here:
- Jason Brownlee LinkedIn Profile
(follow me if you like)
Well, AI and machine learning has been hot for the last decade. I have spent that time as a Python machine learning developer:
- Working on a range of predictive modeling projects.
- Writing more than 1,000+ tutorials.
- Authoring over 20+ books.
There’s one thing about machine learning in Python, your code must be fast.
Modeling code is already generally fast, built on top of C and Fortran code libraries.
But you know how it is on real projects…
You always have to glue bits together, wrap the fast code and run it many times, and so on.
Making code run fast requires Python concurrency and I have spent most of the last decade using all the different types of Python concurrency available.
Including threading, multiprocessing, asyncio, and the suite of popular libraries.
I know my way around Python concurrency and I am deeply frustrated at the bad wrap it has.
This is why I started SuperFastPython.com where you can find hundreds of free tutorials on Python concurrency.
And this is why I wrote this book.
Praise for Super Fast Python
Python developers write to me all the time and let me know how helpful my tutorials and books have been.
Below are some select examples posted to LinkedIn.
What Are You Waiting For?
Stop reading outdated StackOverflow answers.
Learn Python concurrency correctly, step-by-step.
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