Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletter Hub
Free Learning
Arrow right icon
timer SALE ENDS IN
0 Days
:
00 Hours
:
00 Minutes
:
00 Seconds
Python High Performance, Second Edition
Python High Performance, Second Edition

Python High Performance, Second Edition: Build high-performing, concurrent, and distributed applications , Second Edition

Arrow left icon
Profile Icon Dr. Gabriele Lanaro
Arrow right icon
$19.99 per month
Full star icon Full star icon Full star icon Full star icon Empty star icon 4 (2 Ratings)
Paperback May 2017 270 pages 2nd Edition
eBook
$24.99 $35.99
Paperback
$43.99
Subscription
Free Trial
Renews at $19.99p/m
Arrow left icon
Profile Icon Dr. Gabriele Lanaro
Arrow right icon
$19.99 per month
Full star icon Full star icon Full star icon Full star icon Empty star icon 4 (2 Ratings)
Paperback May 2017 270 pages 2nd Edition
eBook
$24.99 $35.99
Paperback
$43.99
Subscription
Free Trial
Renews at $19.99p/m
eBook
$24.99 $35.99
Paperback
$43.99
Subscription
Free Trial
Renews at $19.99p/m

What do you get with a Packt Subscription?

Free for first 7 days. $19.99 p/m after that. Cancel any time!
Product feature icon Unlimited ad-free access to the largest independent learning library in tech. Access this title and thousands more!
Product feature icon 50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.
Product feature icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Product feature icon Thousands of reference materials covering every tech concept you need to stay up to date.
Subscribe now
View plans & pricing
Table of content icon View table of contents Preview book icon Preview Book

Python High Performance, Second Edition

Pure Python Optimizations

As mentioned in the last chapter, one of the most effective ways of improving the performance of applications is through the use of better algorithms and data structures. The Python standard library provides a large variety of ready-to-use algorithms and data structures that can be directly incorporated in your applications. With the tools learned from this chapter, you will be able to use the right algorithm for the task and achieve massive speed gains.

Even though many algorithms have been around for quite a while, they are especially relevant in today's world as we continuously produce, consume, and analyze ever increasing amounts of data. Buying a larger server or microoptimizing can work for some time, but achieving better scaling through algorithmic improvement can solve the problem once and for all.

In this chapter, we will understand how to achieve better scaling using standard...

Useful algorithms and data structures

Algorithmic improvements are especially effective in increasing performance because they typically allow the application to scale better with increasingly large inputs.

Algorithm running times can be classified according to their computational complexity, a characterization of the resources required to perform a task. Such classification is expressed through the Big-O notation, an upper bound on the operations required to execute the task, which usually depends on the input size.

For example, incrementing each element of a list can be implemented using a for loop, as follows:

    input = list(range(10))
for i, _ in enumerate(input):
input[i] += 1

If the operation does not depend on the size of the input (for example, accessing the first element of a list), the algorithm is said to take constant, or O(1), time. This means that, no matter how much data we have, the...

Caching and memoization

Caching is a great technique used to improve the performance of a wide range of applications. The idea behind caching is to store expensive results in a temporary location, called cache, that can be located in memory, on-disk, or in a remote location.

Web applications make extensive use of caching. In a web application, it often happens that users request a certain page at the same time. In this case, instead of recomputing the page for each user, the web application can compute it once and serve the user the already rendered page. Ideally, caching also needs a mechanism for invalidation so that if the page needs to be updated, we can recompute it before serving it again. Intelligent caching allows web applications to handle increasing number of users with less resources. Caching can also be done preemptively, such as the later sections of the video get buffered when watching a video online...

Comprehensions and generators

In this section, we will explore a few simple strategies to speed up Python loops using comprehension and generators. In Python, comprehension and generator expressions are fairly optimized operations and should be preferred in place of explicit for-loops. Another reason to use this construct is readability; even if the speedup over a standard loop is modest, the comprehension and generator syntax is more compact and (most of the times) more intuitive.

In the following example, we can see that both the list comprehension and generator expressions are faster than an explicit loop when combined with the sum function:

    def loop(): 
res = []
for i in range(100000):
res.append(i * i)
return sum(res)

def comprehension():
return sum([i * i for i in range(100000)])

def generator():
return sum(i * i for i in range(100000))

%timeit...

Summary

Algorithmic optimization can improve how your application scales as we process increasingly large data. In this chapter, we demonstrated use-cases and running times of the most common data structures available in Python, such as lists, deques, dictionaries, heaps, and tries. We also covered caching, a technique that can be used to trade some space, in memory or on-disk, in exchange for increased responsiveness of an application. We also demonstrated how to get modest speed gains by replacing for-loops with fast constructs, such as list comprehensions and generator expressions.

In the subsequent chapters, we will learn how to improve performance further using numerical libraries such as numpy, and how to write extension modules in a lower-level language with the help of Cython.

Left arrow icon Right arrow icon
Download code icon Download Code

Key benefits

  • Identify the bottlenecks in your applications and solve them using the best profiling techniques
  • Write efficient numerical code in NumPy, Cython, and Pandas
  • Adapt your programs to run on multiple processors and machines with parallel programming

Description

Python is a versatile language that has found applications in many industries. The clean syntax, rich standard library, and vast selection of third-party libraries make Python a wildly popular language. Python High Performance is a practical guide that shows how to leverage the power of both native and third-party Python libraries to build robust applications. The book explains how to use various profilers to find performance bottlenecks and apply the correct algorithm to fix them. The reader will learn how to effectively use NumPy and Cython to speed up numerical code. The book explains concepts of concurrent programming and how to implement robust and responsive applications using Reactive programming. Readers will learn how to write code for parallel architectures using Tensorflow and Theano, and use a cluster of computers for large-scale computations using technologies such as Dask and PySpark. By the end of the book, readers will have learned to achieve performance and scale from their Python applications.

Who is this book for?

The book is aimed at Python developers who want to improve the performance of their application. Basic knowledge of Python is expected

What you will learn

  • Write efficient numerical code with the NumPy and Pandas libraries
  • Use Cython and Numba to achieve native performance
  • Find bottlenecks in your Python code using profilers
  • Write asynchronous code using Asyncio and RxPy
  • Use Tensorflow and Theano for automatic parallelism in Python
  • Set up and run distributed algorithms on a cluster using Dask and PySpark

Product Details

Country selected
Publication date, Length, Edition, Language, ISBN-13
Publication date : May 24, 2017
Length: 270 pages
Edition : 2nd
Language : English
ISBN-13 : 9781787282896
Category :
Languages :
Tools :

What do you get with a Packt Subscription?

Free for first 7 days. $19.99 p/m after that. Cancel any time!
Product feature icon Unlimited ad-free access to the largest independent learning library in tech. Access this title and thousands more!
Product feature icon 50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.
Product feature icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Product feature icon Thousands of reference materials covering every tech concept you need to stay up to date.
Subscribe now
View plans & pricing

Product Details

Publication date : May 24, 2017
Length: 270 pages
Edition : 2nd
Language : English
ISBN-13 : 9781787282896
Category :
Languages :
Tools :

Packt Subscriptions

See our plans and pricing
Modal Close icon
$19.99 billed monthly
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Simple pricing, no contract
$199.99 billed annually
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just $5 each
Feature tick icon Exclusive print discounts
$279.99 billed in 18 months
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just $5 each
Feature tick icon Exclusive print discounts

Frequently bought together


Stars icon
Total $ 136.97
Python High Performance, Second Edition
$43.99
Python Data Structures and Algorithms
$48.99
Daniel Arbuckle???s Mastering Python
$43.99
Total $ 136.97 Stars icon

Table of Contents

9 Chapters
Benchmarking and Profiling Chevron down icon Chevron up icon
Pure Python Optimizations Chevron down icon Chevron up icon
Fast Array Operations with NumPy and Pandas Chevron down icon Chevron up icon
C Performance with Cython Chevron down icon Chevron up icon
Exploring Compilers Chevron down icon Chevron up icon
Implementing Concurrency Chevron down icon Chevron up icon
Parallel Processing Chevron down icon Chevron up icon
Distributed Processing Chevron down icon Chevron up icon
Designing for High Performance Chevron down icon Chevron up icon

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
(2 Ratings)
5 star 50%
4 star 0%
3 star 50%
2 star 0%
1 star 0%
Dimitri Shvorob Feb 23, 2018
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Thinking how to rate this book has been a bit of a roller-coaster:Up: "Is this really a Packt book? It's very well written, I like it!"Down: "Hold on - there is another "High-performance Python" book, published by O'Reilly in 2014? The TOCs sure have more than a few similarities. Is this one a copycat?"Up: "No, it isn't. I see how this book is different, and see what it brings to the table. Oh, and first edition of this book came out in 2013, so this is actually the earliest book on the subject, it seems".In the end, a very positive evaluation. Yes, "High-performance Python" by by Gorelick and Ozsvald is an obvious competitor, and a strong one - a more advanced book than Lanaro's, I would guess. On the other hand, as a newbie to the world of high-performance Python, I know that I find Lanaro's explanation much easier to follow. This is the book I am actually going to use to learn the subject. Many thanks, Gabriele, five stars from me.
Amazon Verified review Amazon
Parijat Sengupta May 19, 2023
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3
A neat compilation of online guides/tutorials. Convoluted explanations that are typical of short articles posted on multiple forums. The worst chapter is perhaps the one on implementing concurrency (chapter 6). A redeeming feature is a good explanatory section on the indexing patterns of Numpy. There isn’t much to expect from Packt books in general, as they seem to be put together in haste with quality control an obvious casualty - this title lives up to that billing.
Amazon Verified review Amazon
Get free access to Packt library with over 7500+ books and video courses for 7 days!
Start Free Trial

FAQs

What is included in a Packt subscription? Chevron down icon Chevron up icon

A subscription provides you with full access to view all Packt and licnesed content online, this includes exclusive access to Early Access titles. Depending on the tier chosen you can also earn credits and discounts to use for owning content

How can I cancel my subscription? Chevron down icon Chevron up icon

To cancel your subscription with us simply go to the account page - found in the top right of the page or at https://subscription.packtpub.com/my-account/subscription - From here you will see the ‘cancel subscription’ button in the grey box with your subscription information in.

What are credits? Chevron down icon Chevron up icon

Credits can be earned from reading 40 section of any title within the payment cycle - a month starting from the day of subscription payment. You also earn a Credit every month if you subscribe to our annual or 18 month plans. Credits can be used to buy books DRM free, the same way that you would pay for a book. Your credits can be found in the subscription homepage - subscription.packtpub.com - clicking on ‘the my’ library dropdown and selecting ‘credits’.

What happens if an Early Access Course is cancelled? Chevron down icon Chevron up icon

Projects are rarely cancelled, but sometimes it's unavoidable. If an Early Access course is cancelled or excessively delayed, you can exchange your purchase for another course. For further details, please contact us here.

Where can I send feedback about an Early Access title? Chevron down icon Chevron up icon

If you have any feedback about the product you're reading, or Early Access in general, then please fill out a contact form here and we'll make sure the feedback gets to the right team. 

Can I download the code files for Early Access titles? Chevron down icon Chevron up icon

We try to ensure that all books in Early Access have code available to use, download, and fork on GitHub. This helps us be more agile in the development of the book, and helps keep the often changing code base of new versions and new technologies as up to date as possible. Unfortunately, however, there will be rare cases when it is not possible for us to have downloadable code samples available until publication.

When we publish the book, the code files will also be available to download from the Packt website.

How accurate is the publication date? Chevron down icon Chevron up icon

The publication date is as accurate as we can be at any point in the project. Unfortunately, delays can happen. Often those delays are out of our control, such as changes to the technology code base or delays in the tech release. We do our best to give you an accurate estimate of the publication date at any given time, and as more chapters are delivered, the more accurate the delivery date will become.

How will I know when new chapters are ready? Chevron down icon Chevron up icon

We'll let you know every time there has been an update to a course that you've bought in Early Access. You'll get an email to let you know there has been a new chapter, or a change to a previous chapter. The new chapters are automatically added to your account, so you can also check back there any time you're ready and download or read them online.

I am a Packt subscriber, do I get Early Access? Chevron down icon Chevron up icon

Yes, all Early Access content is fully available through your subscription. You will need to have a paid for or active trial subscription in order to access all titles.

How is Early Access delivered? Chevron down icon Chevron up icon

Early Access is currently only available as a PDF or through our online reader. As we make changes or add new chapters, the files in your Packt account will be updated so you can download them again or view them online immediately.

How do I buy Early Access content? Chevron down icon Chevron up icon

Early Access is a way of us getting our content to you quicker, but the method of buying the Early Access course is still the same. Just find the course you want to buy, go through the check-out steps, and you’ll get a confirmation email from us with information and a link to the relevant Early Access courses.

What is Early Access? Chevron down icon Chevron up icon

Keeping up to date with the latest technology is difficult; new versions, new frameworks, new techniques. This feature gives you a head-start to our content, as it's being created. With Early Access you'll receive each chapter as it's written, and get regular updates throughout the product's development, as well as the final course as soon as it's ready.We created Early Access as a means of giving you the information you need, as soon as it's available. As we go through the process of developing a course, 99% of it can be ready but we can't publish until that last 1% falls in to place. Early Access helps to unlock the potential of our content early, to help you start your learning when you need it most. You not only get access to every chapter as it's delivered, edited, and updated, but you'll also get the finalized, DRM-free product to download in any format you want when it's published. As a member of Packt, you'll also be eligible for our exclusive offers, including a free course every day, and discounts on new and popular titles.