


How to Efficiently Iterate Over Overlapping Pairs (and Triples) in Python Lists?
How to Iterate Overlapping Value Pairs from a List
When working with lists in Python, it's often necessary to iterate over values in pairs. A common approach is to use a construct such as:
for current, next in zip(the_list, the_list[1:]): # Do something
While this code works, there is a more idiomatic and efficient solution using the pairwise function from the itertools module. Here's a revised Python 3.8 implementation:
import itertools def pairwise(iterable): "s -> (s0, s1), (s1, s2), (s2, s3), ..." a, b = itertools.tee(iterable) next(b, None) return zip(a, b)
For Python 2, use itertools.izip instead of zip (since zip in Python 2 creates a list instead of a lazy iterator).
The pairwise function works by creating two parallel iterators, a and b, pointing to the same first element. b is then advanced one step ahead using next. The izip function combines the elements from the two iterators to form overlapping pairs.
This approach can also be generalized to handle larger "windows" of values. For example, to iterate over triples of values, use the following function:
def threes(iterator): "s -> (s0, s1, s2), (s1, s2, s3), (s2, s3, 4), ..." a, b, c = itertools.tee(iterator, 3) next(b, None) next(c, None) next(c, None) return zip(a, b, c)
Caveat: It's important to note that if one of the iterators advances further than the others due to the use of next, the implementation will hold the consumed elements in memory until all iterators have consumed them.
The above is the detailed content of How to Efficiently Iterate Over Overlapping Pairs (and Triples) in Python Lists?. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics











Python is suitable for data science, web development and automation tasks, while C is suitable for system programming, game development and embedded systems. Python is known for its simplicity and powerful ecosystem, while C is known for its high performance and underlying control capabilities.

You can learn basic programming concepts and skills of Python within 2 hours. 1. Learn variables and data types, 2. Master control flow (conditional statements and loops), 3. Understand the definition and use of functions, 4. Quickly get started with Python programming through simple examples and code snippets.

Python excels in gaming and GUI development. 1) Game development uses Pygame, providing drawing, audio and other functions, which are suitable for creating 2D games. 2) GUI development can choose Tkinter or PyQt. Tkinter is simple and easy to use, PyQt has rich functions and is suitable for professional development.

You can learn the basics of Python within two hours. 1. Learn variables and data types, 2. Master control structures such as if statements and loops, 3. Understand the definition and use of functions. These will help you start writing simple Python programs.

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.

To maximize the efficiency of learning Python in a limited time, you can use Python's datetime, time, and schedule modules. 1. The datetime module is used to record and plan learning time. 2. The time module helps to set study and rest time. 3. The schedule module automatically arranges weekly learning tasks.

Python is widely used in the fields of web development, data science, machine learning, automation and scripting. 1) In web development, Django and Flask frameworks simplify the development process. 2) In the fields of data science and machine learning, NumPy, Pandas, Scikit-learn and TensorFlow libraries provide strong support. 3) In terms of automation and scripting, Python is suitable for tasks such as automated testing and system management.

Python excels in automation, scripting, and task management. 1) Automation: File backup is realized through standard libraries such as os and shutil. 2) Script writing: Use the psutil library to monitor system resources. 3) Task management: Use the schedule library to schedule tasks. Python's ease of use and rich library support makes it the preferred tool in these areas.
