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Bioinformatics with Python Cookbook

You're reading from   Bioinformatics with Python Cookbook Use modern Python libraries and applications to solve real-world computational biology problems

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Product type Paperback
Published in Sep 2022
Publisher Packt
ISBN-13 9781803236421
Length 360 pages
Edition 3rd Edition
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Author (1):
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Tiago Antao Tiago Antao
Author Profile Icon Tiago Antao
Tiago Antao
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Toc

Table of Contents (15) Chapters Close

Preface 1. Chapter 1: Python and the Surrounding Software Ecology 2. Chapter 2: Getting to Know NumPy, pandas, Arrow, and Matplotlib FREE CHAPTER 3. Chapter 3: Next-Generation Sequencing 4. Chapter 4: Advanced NGS Data Processing 5. Chapter 5: Working with Genomes 6. Chapter 6: Population Genetics 7. Chapter 7: Phylogenetics 8. Chapter 8: Using the Protein Data Bank 9. Chapter 9: Bioinformatics Pipelines 10. Chapter 10: Machine Learning for Bioinformatics 11. Chapter 11: Parallel Processing with Dask and Zarr 12. Chapter 12: Functional Programming for Bioinformatics 13. Index 14. Other Books You May Enjoy

A showcase of Python’s functools module

Python has three built-in modules that greatly help when writing code in a functional dialect: functools, operator, and itertools. In this recipe, we are going to briefly discuss the functools module. For example, the fundamental reduce function (where part of the name of MapReduce comes from) is only available if you import functools.

While a detailed exploration of these modules would be too long for a single recipe, we are going to showcase some functionality by improving some of the code of the previous recipes with the functionality from functools and showcase some illustrative examples of the utility of the module.

Getting ready

Our code is available in Chapter12/Builtin.py. We will make references to previous recipes.

How to do it...

Let’s look at several illustrative examples:

  1. Remember that our recursive implementation of a factorial function in the previous recipe was not very efficient? Let’...
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