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NumPy: Beginner's Guide - Third Edition
Ivan Idris
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eBook - ePub
NumPy: Beginner's Guide - Third Edition
Ivan Idris
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About This Book
- Analyze, benchmark, and profile your Node.js application to find slow spots, and push it to the limit by eliminating performance bottlenecks
- Learn the basis of performance analysis using Node.js
- Explore the high performance capabilities of Node.js, along with best practices
Who This Book Is For
This book is for Node.js developers who want a more in-depth knowledge of the platform to improve the performance of their applications. Whether you have a base Node.js background or you are an expert who knows the garbage collector and wants to leverage it to make applications more robust, the examples in this book will benefit you.
What You Will Learn
- Develop applications using well-defined and well-tested development patterns
- Explore memory management and garbage collection to improve performance
- Monitor memory changes and analyze heap snapshots
- Profile CPU and improve your code to avoid patterns that force intensive processor usage
- Understand the importance of data and when you should cache information
- Educate yourself to always test your code and benchmark when needed
- Extend your application's scope and know what other elements can influence performance
In Detail
Node.js is a tool written in C that allows you to use JavaScript on the server-side. High performance on a platform such as Node.js is to take advantage of every aspect of your hardware, helping memory management act at its best. Spot the memory leaks and solve them fast with Node.js by monitoring and stopping them before they become an issue.
Starting with performance analysis concepts and their importance in helping Node.js developers eliminate performance bottlenecks, this book will take you through development patterns to avoid performance penalties. You will learn the importance of garbage collection and its behavior, and discover how to profile your processor, allowing better performance and scalability.
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Informazioni
NumPy Beginner's Guide Third Edition
Table of Contents
NumPy Beginner's Guide Third Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Support files, eBooks, discount offers, and more
Why subscribe?
Free access for Packt account holders
Preface
What is NumPy?
History
Why use NumPy?
Limitations of NumPy
What this book covers
What you need for this book
Who this book is for
Sections
Time for action – heading
What just happened?
Pop quiz – heading
Have a go hero – heading
Conventions
Reader feedback
Customer support
Downloading the example code
Downloading the color images of this book
Errata
Piracy
Questions
1. NumPy Quick Start
Python
Time for action – installing Python on different operating systems
What just happened?
The Python help system
Time for action – using the Python help system
What just happened?
Basic arithmetic and variable assignment
Time for action – using Python as a calculator
What just happened?
Time for action – assigning values to variables
What just happened?
The print() function
Time for action – printing with the print() function
What just happened?
Code comments
Time for action – commenting code
The if statement
Time for action – deciding with the if statement
What just happened?
The for loop
Time for action – repeating instructions with loops
What just happened?
Python functions
Time for action – defining functions
What just happened?
Python modules
Time for action – importing modules
What just happened?
NumPy on Windows
Time for action – installing NumPy, matplotlib, SciPy, and IPython on Windows
What just happened?
NumPy on Linux
Time for action – installing NumPy, matplotlib, SciPy, and IPython on Linux
NumPy on Mac OS X
Time for action – installing NumPy, SciPy, matplotlib, and IPython with MacPorts or Fink
What just happened?
Building from source
Arrays
Time for action – adding vectors
What just happened?
Pop quiz – Functioning of the arange() function
Have a go hero – continue the analysis
IPython – an interactive shell
Online resources and help
Summary
2. Beginning with NumPy Fundamentals
NumPy array object
Time for action – creating a multidimensional array
What just happened?
Pop quiz – the shape of ndarray
Have a go hero – create a three-by-three array
Selecting elements
NumPy numerical types
Data type objects
Character codes
The dtype constructors
The dtype attributes
Time for action – creating a record data type
What just happened?
One-dimensional slicing and indexing
Time for action – slicing and indexing multidimensional arrays
What just happened?
Time for action – manipulating array shapes
What just happened?
Stacking
Time for action – stacking arrays
What just happened?
Splitting
Time for action – splitting arrays
What just happened?
Array attributes
Time for action – converting arrays
What just happened?
Summary
3. Getting Familiar with Commonly Used Functions
File I/O
Time for action – reading and writing files
What just happened?
Comma-seperated value files
Time for action – loading from CSV files
Volume Weighted Average Price
Time for action – calculating Volume Weighted Average Price
What just happened?
The mean() function
Time-weighted average price
Pop quiz – computing the weighted average
Have a go hero – calculating other averages
Value range
Time for action – finding highest and lowest values
What just happened?
Statistics
Time for action – performing simple statistics
What just happened?
Stock returns
Time for action – analyzing stock returns
What just happened?
Dates
Time for action – dealing with dates
What just happened?
Have a go hero – looking at VWAP and TWAP
Time for action – using the datetime64 data type
What just happened?
Weekly summary
Time for action – summarizing data
What just happened?
Have a go hero – improving the code
Average True Range
Time for action – calculating the Average True Range
What just happened?
Have a go hero – taking the minimum() function for a spin
Simple Moving Average
Time for action – computing the Simple Moving Average
What just happened?
Exponential Moving Average
Time for action – cal...