Python is an ideal language for solving problems, especially in Linux
and Unix networks. With this pragmatic book, administrators can review
various tasks that often occur in the management of these systems, and
learn how Python can provide a more efficient and less painful way to
handle them. Each chapter in Python for Unix and Linux System
Administration presents a particular administrative issue, such as
concurrency or data backup, and presents Python solutions through
hands-on examples. Once you finish this book, you’ll be able to develop
your own set of command-line utilities with Python to tackle a wide
range of problems. Discover how this language can help you:
- Read text files and extract information
- Run tasks concurrently using the threading and forking options
- Get information from one process to another using network facilities
- Create clickable GUIs to handle large and complex utilities
- Monitor large clusters of machines by interacting with SNMP
programmatically
- Master the IPython Interactive Python shell to replace or augment
Bash, Korn, or Z-Shell
- Integrate Cloud Computing into your infrastructure, and learn to
write a Google App Engine Application
- Solve unique data backup challenges with customized scripts
- Interact with MySQL, SQLite, Oracle, Postgres, Django ORM, and
SQLAlchemy With this book, you’ll learn how to package and deploy your
Python applications and libraries, and write code that runs equally well
on multiple Unix platforms. You’ll also learn about several
Python-related technologies that will make your life much easier.

We are visual animals. But before we can see the world in its true splendor, our brains, just like our computers, have to sort and organize raw data, and then transform that data to produce new images of the world. Beginning Python Visualization: Crafting Visual Transformation Scripts talks about turning many types of small data sources into useful visual data. And you will learn Python as part of the bargain.

What you’ll learn

• Write ten lines of code and present visual information instead of data soup.
• Set up an open source environment ready for data visualization.
• Forget Excel: use Python.
• Learn numerical and textual processing.
• Draw graphs and plots based on textual and numerical data.
• Learn how to deal with images.

This book offers a highly accessible introduction to Natural Language Processing, the field that underpins a variety of language technologies, ranging from predictive text and email filtering to automatic summarization and translation. With Natural Language Processing with Python, you’ll learn how to write Python programs to work with large collections of unstructured text. You’ll access richly-annotated datasets using a comprehensive range of linguistic data structures. And you’ll understand the main algorithms for analyzing the content and structure of written communication. Packed with examples and exercises, Natural Language Processing with Python will help you:

Extract information from unstructured text, to guess the topic or identify “named entities” Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence