Effective Python Development for Biologists: Tools and techniques for building biological programs by Dr Martin Jones
English | 2016 | ISBN: 153910303X | 296 Pages | PDF | 1.9 MB
Python is rapidly becoming the standard language for many talks in scientific research, and is particularly popular in biology and bioinformatics. One of the great strengths of Python is the ecosystem of tools and libraries that have grown up around it.
Python is rapidly becoming the standard language for many talks in scientific research, and is particularly popular in biology and bioinformatics. One of the great strengths of Python is the ecosystem of tools and libraries that have grown up around it.
This book introduces the novice biologist programmer to tools and techniques that make developing Python code easier and faster and will help you to write more reliable, performant programs. Written by a biologist, it focusses on solving the problems that students and researchers encounter every day:
- How do I make my program run faster?
- How can I be sure that my results are correct?
- How do I share this program with my colleagues?
- How can I speed up the process of writing my code?
Chapters include:
- Environments for development - learn how you can take advantage of different tools for actually writing code, including those designed specifically for scientific work.
- Organising and sharing code - learn how Python's module and packaging system works, how to effectively reuse code across multiple projects, and how to share your programs with colleagues and the wider world.
- Testing - learn how automated testing can make your code more reliable, how to catch bugs before they impact your work, and how to edit code with confidence.
- Performance - learn how to make your code run quickly even on large datasets, how to understand the scaling behaviour of your code, and explore the trade offs involved in designing code.
- User interfaces - learn how to make your code more user friendly, how to design effective interfaces, and how to automate record-keeping with Python's logging system.
