Python Concurrent File I/O

Concurrent File I/O in Python

Faster File I/O With Threads, Processes, and AsyncIO

File I/O can be faster in Python when using concurrency.

• Discover how to write files 3x faster with processes
• Discover how to read files 3x faster with processes and threads
• Discover how to unzip files 4x faster with processes and threads

File I/O stands for File Input/Output, referring to the process of reading data from and writing data to files on a storage device like a hard drive.

Studying how to bring concurrency to file I/O is critical for Python developers.

File I/O operations are inherently slower compared to working with data in RAM, often becoming a significant bottleneck in many programs. By understanding concurrency and incorporating it into your file I/O tasks, you can unlock the full potential of modern computer hardware, making your applications more efficient and capable of handling large workloads.

The problem is, there is no silver bullet. Each program and each task is different and unique. We cannot know which approach to Python concurrency will give good or even the best performance.

Therefore in addition to learning how to perform file I/O operations concurrently, Python developers must learn how to benchmark a suite of different approaches to implementing file I/O operations concurrently.

Introducing: "Concurrent File I/O in Python". A new book designed to teach you how to bring concurrency to your file I/O tasks in Python, super fast!

You will get rapid-paced tutorials showing you how to bring concurrency to the most common file I/O tasks.

Including:

• How to perform file I/O operation in the background.
• How to concurrently read files from disk and write files to disk.
• How to concurrently delete files from disk.
• How to concurrently copy, move, and rename files on disk.
• How to efficiently append files on disk.
• How to concurrently zip files and unzip files on disk.

Don't worry if you are new to file I/O or concurrency, you will also get primers on the background required to get the most out of this book, including:

• The importance of concurrency for high-performance file I/O.
• How to perform common file I/O operations in Python.
• How to use Python concurrency APIs including threading, multiprocessing, and asyncio.
• How to perform file I/O with coroutines in asyncio using the aiofiles library.
• How to use programming patterns for concurrent file I/O.

Each tutorial is carefully designed to teach one critical aspect of how to bring concurrency to file I/O tasks.

Table of Contents

• Introduction
• Tutorial 01: Importance of Concurrency for File I/O.
• Tutorial 02: Tour of Python File I/O.
• Tutorial 03: Tour of Python Concurrency.
• Tutorial 04: Tour of AIOFiles for AsyncIO.
• Tutorial 05: File I/O Concurrency Patterns.
• Tutorial 06: How to Run File I/O in the Background.
• Tutorial 07: How to Write Files Concurrently.
• Tutorial 08: How to Read Files Concurrently.
• Tutorial 09: How to Delete Files Concurrently.
• Tutorial 10: How to Copy Files Concurrently.
• Tutorial 11: How to Move Files Concurrently.
• Tutorial 12: How to Rename Files Concurrently.
• Tutorial 13: How to Append Files Concurrently.
• Tutorial 14: How to Zip Files Concurrently.
• Tutorial 15: How to Unzip Files Concurrently.
• Conclusions

Stop copy-pasting code from StackOverflow answers.

Learn Python concurrency correctly, step-by-step.

Learn more about this book here:

• https://superfastpython.com/concurrent-file-io-in-python/

How to Buy

1. Click the "I want this!" button (in the upper right)
2. Choose Credit Card or PayPal and complete the order form then click the "Pay" button.
3. You will be redirected to a webpage where you can download your bundle immediately (you will also get an email with the download link, just in case you need it).

About the Author

Jason Brownlee, Ph.D. helps Python developers bring modern concurrency methods to their projects with hands-on tutorials.

Jason loves Python Concurrency. It's all he does. It’s his main thing.

Jason has:

• Read all the books on Python concurrency.
• Used all of the Python concurrency APIs in the standard library.
• Written 500+ tutorials and 12+ books on Python concurrency.

Learn more at SuperFastPython.com

Jason is a software engineer and research scientist with a background in artificial intelligence and high-performance computing. He has authored more than 20 technical books on machine learning and has built, operated, and exited online businesses.

See his linkedin profile here:

• Jason Brownlee on LinkedIn (follow him!)

Any Questions?

Hi, Jason here, do you have any questions?

Contact me directly at any time about this product or Python concurrency generally. I'm here to help as best I can.

You can send an email directly to my inbox via:

• Jason@SuperFastPython.com