videvs: Python

The Simple Way to Make Technology See

Author:: Anthony Oliver, Katherine Scott, Kurt Demaagd, Nathan Oostendorp
ISBN-10:: 9781449320362
Year:: 2012
Pages:: 254
Language:: English
File size:: 11 MB
File format:: ePub
Category:: web-development Python

Book Description:

Learn how to build your own computer vision (CV) applications quickly and easily with SimpleCV, an open source framework written in Python. Through examples of real-world applications, this hands-on guide introduces you to basic CV techniques for collecting, processing, and analyzing streaming digital images. You’ll then learn how to apply these methods with SimpleCV, using sample Python code. All you need to get started is a Windows, Mac, or Linux system, and a willingness to put CV to work in a variety of ways. Programming experience is optional.

Capture images from several sources, including webcams, smartphones, and Kinect
Filter image input so your application processes only necessary information
Manipulate images by performing basic arithmetic on pixel values
Use feature detection techniques to focus on interesting parts of an image
Work with several features in a single image, using the NumPy and SciPy Python libraries
Learn about optical flow to identify objects that change between two image frames
Use SimpleCV’s command line and code editor to run examples and test techniques

A Guide for Python Programmers

Author:: Kurt W. Smith
ISBN-10:: 1491901551
Year:: 2015
Pages:: 254
Language:: English
File size:: 4.3 MB
File format:: PDF
Category:: web-development Python datebases Datebases

Book Description:

Build software that combines Python’s expressivity with the performance and control of C (and C++). It’s possible with Cython, the compiler and hybrid programming language used by foundational packages such as NumPy, and prominent in projects including Pandas, h5py, and scikits-learn. In this practical guide, you’ll learn how to use Cython to improve Python’s performance—up to 3000x— and to wrap C and C++ libraries in Python with ease.

Author Kurt Smith takes you through Cython’s capabilities, with sample code and in-depth practice exercises. If you’re just starting with Cython, or want to go deeper, you’ll learn how this language is an essential part of any performance-oriented Python programmer’s arsenal.

Use Cython’s static typing to speed up Python code
Gain hands-on experience using Cython features to boost your numeric-heavy Python
Create new types with Cython—and see how fast object-oriented programming in Python can be
Effectively organize Cython code into separate modules and packages without sacrificing performance
Use Cython to give Pythonic interfaces to C and C++ libraries
Optimize code with Cython’s runtime and compile-time profiling tools
Use Cython’s prange function to parallelize loops transparently with OpenMP

Modern Computing in Simple Packages

Author:: Bill Lubanovic
ISBN-10:: 1449359361
Year:: 2015
Pages:: 484
Language:: English
File size:: 8.2 MB
File format:: PDF
Category:: web-development Python

Book Description:

Easy to understand and fun to read, Introducing Python is ideal for beginning programmers as well as those new to the language. Author Bill Lubanovic takes you from the basics to more involved and varied topics, mixing tutorials with cookbook-style code recipes to explain concepts in Python 3. End-of-chapter exercises help you practice what you’ve learned.

You’ll gain a strong foundation in the language, including best practices for testing, debugging, code reuse, and other development tips. This book also shows you how to use Python for applications in business, science, and the arts, using various Python tools and open source packages.

Learn simple data types, and basic math and text operations
Use data-wrangling techniques with Python’s built-in data structures
Explore Python code structure, including the use of functions
Write large programs in Python, with modules and packages
Dive into objects, classes, and other object-oriented features
Examine storage from flat files to relational databases and NoSQL
Use Python to build web clients, servers, APIs, and services
Manage system tasks such as programs, processes, and threads
Understand the basics of concurrency and network programming

For Facial Recognition, Object Detection, and Pattern Recognition Using Python

Author:: Himanshu Singh
ISBN-10:: 1484241487
Year:: 2019
Pages:: 169
Language:: English
File size:: 4.8 MB
File format:: PDF, ePub
Category:: web-development Python

Book Description:

Gain insights into image-processing methodologies and algorithms, using machine learning and neural networks in Python. This book begins with the environment setup, understanding basic image-processing terminology, and exploring Python concepts that will be useful for implementing the algorithms discussed in the book. You will then cover all the core image processing algorithms in detail before moving onto the biggest computer vision library: OpenCV. You’ll see the OpenCV algorithms and how to use them for image processing.

The next section looks at advanced machine learning and deep learning methods for image processing and classification. You’ll work with concepts such as pulse coupled neural networks, AdaBoost, XG boost, and convolutional neural networks for image-specific applications. Later you’ll explore how models are made in real time and then deployed using various DevOps tools.

All the concepts in Practical Machine Learning and Image Processing are explained using real-life scenarios. After reading this book you will be able to apply image processing techniques and make machine learning models for customized application.

What You Will Learn

Discover image-processing algorithms and their applications using Python
Explore image processing using the OpenCV library
Use TensorFlow, scikit-learn, NumPy, and other libraries
Work with machine learning and deep learning algorithms for image processing
Apply image-processing techniques to five real-time projects

Who This Book Is For

Data scientists and software developers interested in image processing and computer vision.

Over 80 taskbased recipes to store, organize, manipulate, and analyze spatial data in a PostGIS database

Author:: Bborie Park, Paolo Corti, Stephen Vincent Mather, Thomas J. Kraft
ISBN-10:: 9781849518666
Year:: 2014
Pages:: 484
Language:: English
File size:: 46 MB
File format:: PDF
Category:: web-development Python datebases Datebases

Book Description:

PostGIS is a spatial database that integrates advanced storage and analysis of vector and raster data, and is remarkably flexible and powerful. PostGIS provides support for geographic objects to the PostgreSQL object-relational database and is currently the most popular open source spatial databases. If you want to explore the complete range of PostGIS techniques and expose the related extensions, this book is a must-have.

This book is a deep-dive into the full range of PostGIS topics, with practical applications of the concepts and code. It is a comprehensive guide on PostGIS tools and concepts which are required to manage, manipulate, and analyse spatial data in PostGIS. This book is packed with systematic instructions of hands-on examples and in-depth explanations. Even for experienced users, this book will serve as a great source of reference by providing new ways of working with PostGIS through the book’s easy-to-follow approach.

This hands-on guide looks at key spatial data manipulation tasks, explaining not only how each task is performed, but also why. It provides practical guidance allowing you to safely take advantage of the advanced technology in PostGIS in order to simplify your spatial database administration tasks.

This practical book will help you take advantage of basic and advanced vector, raster, and routing approaches. You will learn to use the concepts of data maintenance, optimization, and performance, which will help you to integrate these into a large ecosystem of desktop and web tools.

With this comprehensive guide, you will be armed with all the tools and instructions you need to both manage the spatial database system and make better decisions as your project’s requirements evolve.

Unlocking Text Data with Machine Learning and Deep Learning using Python

Author:: Adarsha Shivananda, Akshay Kulkarni
ISBN-10:: 1484242661
Year:: 2019
Pages:: 234
Language:: English
File size:: 3.8 MB
File format:: PDF, ePub
Category:: web-development Python

Book Description:

Implement natural language processing applications with Python using a problem-solution approach. This book has numerous coding exercises that will help you to quickly deploy natural language processing techniques, such as text classification, parts of speech identification, topic modeling, text summarization, text generation, entity extraction, and sentiment analysis.

Natural Language Processing Recipes starts by offering solutions for cleaning and preprocessing text data and ways to analyze it with advanced algorithms. You’ll see practical applications of the semantic as well as syntactic analysis of text, as well as complex natural language processing approaches that involve text normalization, advanced preprocessing, POS tagging, and sentiment analysis. You will also learn various applications of machine learning and deep learning in natural language processing.

By using the recipes in this book, you will have a toolbox of solutions to apply to your own projects in the real world, making your development time quicker and more efficient.

What You Will Learn

Apply NLP techniques using Python libraries such as NLTK, TextBlob, spaCy, Stanford CoreNLP, and many more
Implement the concepts of information retrieval, text summarization, sentiment analysis, and other advanced natural language processing techniques.
Identify machine learning and deep learning techniques for natural language processing and natural language generation problems

Who This Book Is For

Data scientists who want to refresh and learn various concepts of natural language processing through coding exercises.

A Problem-Solution Approach

Author:: Pradeepta Mishra
ISBN-10:: 1484242572
Year:: 2019
Pages:: 184
Language:: English
File size:: 15 MB
File format:: PDF, ePub
Category:: web-development Python

Book Description:

Get up to speed with the deep learning concepts of Pytorch using a problem-solution approach. Starting with an introduction to PyTorch, you’ll get familiarized with tensors, a type of data structure used to calculate arithmetic operations and also learn how they operate. You will then take a look at probability distributions using PyTorch and get acquainted with its concepts. Further you will dive into transformations and graph computations with PyTorch. Along the way you will take a look at common issues faced with neural network implementation and tensor differentiation, and get the best solutions for them.

Moving on to algorithms; you will learn how PyTorch works with supervised and unsupervised algorithms. You will see how convolutional neural networks, deep neural networks, and recurrent neural networks work using PyTorch. In conclusion you will get acquainted with natural language processing and text processing using PyTorch.

What You Will Learn

Master tensor operations for dynamic graph-based calculations using PyTorch
Create PyTorch transformations and graph computations for neural networks
Carry out supervised and unsupervised learning using PyTorch
Work with deep learning algorithms such as CNN and RNN
Build LSTM models in PyTorch
Use PyTorch for text processing

Who This Book Is For

Readers wanting to dive straight into programming PyTorch.

Cases Studies from Healthcare, Retail, and Finance

Author:: Puneet Mathur
ISBN-10:: 1484237862
Year:: 2018
Pages:: 400
Language:: English
File size:: 7 MB
File format:: PDF, ePub
Category:: Python

Book Description:

Gain practical skills in machine learning for finance, healthcare, and retail. This book uses a hands-on approach by providing case studies from each of these domains: you’ll see examples that demonstrate how to use machine learning as a tool for business enhancement. As a domain expert, you will not only discover how machine learning is used in finance, healthcare, and retail, but also work through practical case studies where machine learning has been implemented.

Machine Learning Applications Using Python is divided into three sections, one for each of the domains (healthcare, finance, and retail). Each section starts with an overview of machine learning and key technological advancements in that domain. You’ll then learn more by using case studies on how organizations are changing the game in their chosen markets. This book has practical case studies with Python code and domain-specific innovative ideas for monetizing machine learning.

What You Will Learn

Discover applied machine learning processes and principles
Implement machine learning in areas of healthcare, finance, and retail
Avoid the pitfalls of implementing applied machine learning
Build Python machine learning examples in the three subject areas

Who This Book Is For

Data scientists and machine learning professionals.

Event-Driven and Asynchronous Programming with Python

Author:: Brian Warner, Cory Benfield, Dustin Mitchell, Kevin Samuel, Mark Williams, Moshe Zadka, Pierre Tardy
ISBN-10:: 1484237412
Year:: 2019
Pages:: 382
Language:: English
File size:: 4.7 MB
File format:: PDF, ePub
Category:: Python

Book Description:

Explore Twisted, the Python-based event-driven networking engine, and review several of its most popular application projects. It is written by community leaders who have contributed to many of the projects covered, and share their hard-won insights and experience.

Expert Twisted starts with an introduction to event-driven programming, explaining it in the context of what makes Twisted unique. It shows how Twisted’s design emphasizes testability as a solution to common challenges of reliability, debugging, and start-to-finish causality that are inherent in event-driven programming. It also explains asynchronous programming, and the importance of functions, deferreds, and coroutines. It then uses two popular applications, treq and klein, to demonstrate calling and writing Web APIs with Twisted.

The second part of the book dives into Twisted projects, in each case explaining how the project fits into the Twisted ecosystem and what it does, and offers several examples to bring readers up to speed, with pointers to additional resources for more depth. Examples include using Twisted with Docker, as a WSGI container, for file sharing, and more.

What You’ll Learn

Integrate Twisted and asyncio using adapters
Automate software build, test, and release processes with Buildbot
Create clients and servers with Autobahn
Transfer files with Magic Wormhole
Distribute cloud-based file storage with Tahoe LAFS
Understand HTTP/2 with Python and Twisted
Support for asynchronous tasks using Django Channels

Who This Book Is For

Readers should have some Python experience and understand the essentials of containers and protocols, but need not be familiar with Twisted or the associated projects covered in the book.

A Concise Guide with Examples

Author:: Moritz Lenz
ISBN-10:: 1484242807
Year:: 2019
Pages:: 194
Language:: English
File size:: 2.7 MB
File format:: PDF, ePub
Category:: Python

Book Description:

Gain the techniques and tools that enable a smooth and efficient software development process in this quick and practical guide on Python continuous integration (CI) and continuous delivery (CD). Based on example applications, this book introduces various kinds of testing and shows you how to set up automated systems that run these tests, and install applications in different environments in controlled ways. Python Continuous Integration and Delivery tackles the technical problems related to software development that are typically glossed over in pure programming texts.

After reading this book, you’ll see that in today’s fast-moving world, no software project can afford to go through development, then an integration phase of unpredictable length and complexity, and finally be shipped to the customer — just to find out that the resulting application didn’t quite fill their need. Instead, you’ll discover that practicing continuous integration and continuous delivery reduces the risks by keeping changes small and automating otherwise painful processes.

What You Will Learn

Carry out various kinds of testing, including unit testing and continuous integration testing, of your Python code using Jenkins
Build packages and manage repositories
Incorporate Ansible and Go for automated packaging and other deployments
Manage more complex and robust deployments

Who This Book Is For

Python programmers and operating staff that work with Python applications.

Author:: Naomi Ceder
ISBN-10:: 1617294039
Year:: 2018
Pages:: 472
Language:: English
File size:: 9.8 MB
File format:: PDF
Category:: Python

Book Description:

This third revision of Manning’s popular The Quick Python Book offers a clear, crisp updated introduction to the elegant Python programming language and its famously easy-to-read syntax. Written for programmers new to Python, this latest edition includes new exercises throughout. It covers features common to other languages concisely, while introducing Python’s comprehensive standard functions library and unique features in detail.

Foreword by Nicholas Tollervey, Python Software Foundation.

Author:: Valentina Porcu
ISBN-10:: 1484241126
Year:: 2019
Pages:: 260
Language:: English
File size:: 4.5 MB
File format:: PDF, ePub
Category:: Python

Book Description:

Learn how to use Python and its structures, how to install Python, and which tools are best suited for data analyst work. This book provides you with a handy reference and tutorial on topics ranging from basic Python concepts through to data mining, manipulating and importing datasets, and data analysis.

Python for Data Mining Quick Syntax Reference covers each concept concisely, with many illustrative examples. You’ll be introduced to several data mining packages, with examples of how to use each of them.

The first part covers core Python including objects, lists, functions, modules, and error handling. The second part covers Python’s most important data mining packages: NumPy and SciPy for mathematical functions and random data generation, pandas for dataframe management and data import, Matplotlib for drawing charts, and scikitlearn for machine learning.

What You’ll Learn

Install Python and choose a development environment
Understand the basic concepts of object-oriented programming
Import, open, and edit files
Review the differences between Python 2.x and 3.x

Who This Book Is For

Programmers new to Python’s data mining packages or with experience in other languages, who want a quick guide to Pythonic tools and techniques.

Author:: Francois Chollet
ISBN-10:: 9781617294433
Year:: 2017
Pages:: 384
Language:: English
File size:: 10.9 MB
File format:: PDF, ePub
Category:: Python

Book Description:

Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples.

Using Natural Language Processing and Machine Learning

Author:: Sumit Raj
ISBN-10:: 1484240952
Year:: 2019
Pages:: 192
Language:: English
File size:: 5.2 MB
File format:: PDF, ePub
Category:: Python

Book Description:

Build your own chatbot using Python and open source tools. This book begins with an introduction to chatbots where you will gain vital information on their architecture. You will then dive straight into natural language processing with the natural language toolkit (NLTK) for building a custom language processing platform for your chatbot. With this foundation, you will take a look at different natural language processing techniques so that you can choose the right one for you.

The next stage is to learn to build a chatbot using the API.ai platform and define its intents and entities. During this example, you will learn to enable communication with your bot and also take a look at key points of its integration and deployment.

The final chapter of Building Chatbots with Python teaches you how to build, train, and deploy your very own chatbot. Using open source libraries and machine learning techniques you will learn to predict conditions for your bot and develop a conversational agent as a web application. Finally you will deploy your chatbot on your own server with AWS.

What You Will Learn

Gain the basics of natural language processing using Python
Collect data and train your data for the chatbot
Build your chatbot from scratch as a web app
Integrate your chatbots with Facebook, Slack, and Telegram
Deploy chatbots on your own server

Who This Book Is For

Intermediate Python developers who have no idea about chatbots. Developers with basic Python programming knowledge can also take advantage of the book.

With Natural Language Processing and Recommender Systems

Author:: Pramod Singh
ISBN-10:: 1484241304
Year:: 2019
Pages:: 223
Language:: English
File size:: 7.1 MB
File format:: PDF, ePub
Category:: Python

Book Description:

Build machine learning models, natural language processing applications, and recommender systems with PySpark to solve various business challenges. This book starts with the fundamentals of Spark and its evolution and then covers the entire spectrum of traditional machine learning algorithms along with natural language processing and recommender systems using PySpark.

Machine Learning with PySpark shows you how to build supervised machine learning models such as linear regression, logistic regression, decision trees, and random forest. You’ll also see unsupervised machine learning models such as K-means and hierarchical clustering. A major portion of the book focuses on feature engineering to create useful features with PySpark to train the machine learning models. The natural language processing section covers text processing, text mining, and embedding for classification.

After reading this book, you will understand how to use PySpark’s machine learning library to build and train various machine learning models. Additionally you’ll become comfortable with related PySpark components, such as data ingestion, data processing, and data analysis, that you can use to develop data-driven intelligent applications.

What You Will Learn

Build a spectrum of supervised and unsupervised machine learning algorithms
Implement machine learning algorithms with Spark MLlib libraries
Develop a recommender system with Spark MLlib libraries
Handle issues related to feature engineering, class balance, bias and variance, and cross validation for building an optimal fit model

Who This Book Is For

Data science and machine learning professionals.

Analyze Data to Create Visualizations for BI Systems

Author:: Dr. Ossama Embarak
ISBN-10:: 1484241088
Year:: 2018
Pages:: 374
Language:: English
File size:: 12.1 MB
File format:: PDF, ePub
Category:: Python

Book Description:

Look at Python from a data science point of view and learn proven techniques for data visualization as used in making critical business decisions. Starting with an introduction to data science with Python, you will take a closer look at the Python environment and get acquainted with editors such as Jupyter Notebook and Spyder. After going through a primer on Python programming, you will grasp fundamental Python programming techniques used in data science. Moving on to data visualization, you will see how it caters to modern business needs and forms a key factor in decision-making. You will also take a look at some popular data visualization libraries in Python.

Shifting focus to data structures, you will learn the various aspects of data structures from a data science perspective. You will then work with file I/O and regular expressions in Python, followed by gathering and cleaning data. Moving on to exploring and analyzing data, you will look at advanced data structures in Python. Then, you will take a deep dive into data visualization techniques, going through a number of plotting systems in Python.

In conclusion, you will complete a detailed case study, where you’ll get a chance to revisit the concepts you’ve covered so far.

What You Will Learn

Use Python programming techniques for data science
Master data collections in Python
Create engaging visualizations for BI systems
Deploy effective strategies for gathering and cleaning data
Integrate the Seaborn and Matplotlib plotting systems

Who This Book Is For

Developers with basic Python programming knowledge looking to adopt key strategies for data analysis and visualizations using Python.

Understanding and Using the Descriptor Protocol

Author:: Jacob Zimmerman
ISBN-10:: 1484237269
Year:: 2018
Pages:: 97
Language:: English
File size:: 1.3 MB
File format:: PDF, ePub
Category:: Python

Book Description:

Create descriptors and see ideas and examples of how to use descriptors effectively. In this short book, you’ll explore descriptors in general, with a deep explanation of what descriptors are, how they work, and how they’re used. Once you understand the simplicity of the descriptor protocol, the author delves into using and creating descriptors in practice, with plenty of tips, patterns, and real-world guidance. Because descriptors are inherently flexible, you’ll work with multiple examples illustrating how to best take advantage of them.

This second edition includes additions throughout, including new material covering the set_name_() descriptors, new and improved flowcharts to explain the inner workings of descriptors, and a completely new chapter to address instance-level attributes, the easiest way to create descriptors correctly the first time.

Although brief, Python Descriptors is a comprehensive guide to creating Python descriptors, including a pip install-able library called descriptor_tools, which was written alongside this book and is an open source library on GitHub. After reading this book, you will have a solid understanding of how descriptors work and the techniques to avoid the big gotchas associated with working with them.

What You Will Learn

Discover descriptor protocols
Master attribute access and how it applies to descriptors
Build your own descriptors
Use descriptors to store attributes
Create read-only descriptors
Explore the descriptor classes
Apply the other uses of descriptors

Who This Book Is For

Experienced Python coders, programmers, and developers.

Using pandas, Requests, and Recurrent

Author:: Max Humber
ISBN-10:: 9781484238011
Year:: 2018
Pages:: 117
Language:: English
File size:: 3.8 MB
File format:: PDF, ePub
Category:: Python

Book Description:

Deal with data, build up financial formulas in code from scratch, and evaluate and think about money in your day-to-day life. This book is about Python and personal finance and how you can effectively mix the two together.

In Personal Finance with Python you will learn Python and finance at the same time by creating a profit calculator, a currency converter, an amortization schedule, a budget, a portfolio rebalancer, and a purchase forecaster. Many of the examples use pandas, the main data manipulation tool in Python. Each chapter is hands-on, self-contained, and motivated by fun and interesting examples.

Although this book assumes a minimal familiarity with programming and the Python language, if you don’t have any, don’t worry. Everything is built up piece-by-piece and the first chapters are conducted at a relaxed pace. You’ll need Python 3.6 (or above) and all of the setup details are included.

What You’ll Learn

Work with data in pandas
Calculate Net Present Value and Internal Rate Return
Query a third-party API with Requests
Manage secrets
Build efficient loops
Parse English sentences with Recurrent
Work with the YAML file format
Fetch stock quotes and use Prophet to forecast the future

Who This Book Is For

Anyone interested in Python, personal finance, and/or both! This book is geared towards those who want to manage their money more effectively and to those who just want to learn or improve their Python.

With Pandas, NumPy, and Matplotlib

Author:: Fabio Nelli
ISBN-10:: 1484239121
Year:: 2018
Pages:: 569
Language:: English
File size:: 13.9 MB
File format:: PDF, ePub
Category:: Python

Book Description:

Explore the latest Python tools and techniques to help you tackle the world of data acquisition and analysis. You’ll review scientific computing with NumPy, visualization with matplotlib, and machine learning with scikit-learn.

This revision is fully updated with new content on social media data analysis, image analysis with OpenCV, and deep learning libraries. Each chapter includes multiple examples demonstrating how to work with each library. At its heart lies the coverage of pandas, for high-performance, easy-to-use data structures and tools for data manipulation

Author Fabio Nelli expertly demonstrates using Python for data processing, management, and information retrieval. Later chapters apply what you’ve learned to handwriting recognition and extending graphical capabilities with the JavaScript D3 library. Whether you are dealing with sales data, investment data, medical data, web page usage, or other data sets, Python Data Analytics, Second Edition is an invaluable reference with its examples of storing, accessing, and analyzing data.

What You’ll Learn

Understand the core concepts of data analysis and the Python ecosystem
Go in depth with pandas for reading, writing, and processing data
Use tools and techniques for data visualization and image analysis
Examine popular deep learning libraries Keras, Theano,TensorFlow, and PyTorch

Who This Book Is For

Experienced Python developers who need to learn about Pythonic tools for data analysis

Using BeautifulSoup and Scrapy

Author:: Gábor László Hajba
ISBN-10:: 1484239245
Year:: 2018
Pages:: 223
Language:: English
File size:: 4.7 MB
File format:: PDF, ePub
Category:: Python

Book Description:

Closely examine website scraping and data processing: the technique of extracting data from websites in a format suitable for further analysis. You’ll review which tools to use, and compare their features and efficiency. Focusing on BeautifulSoup4 and Scrapy, this concise, focused book highlights common problems and suggests solutions that readers can implement on their own.

Website Scraping with Python starts by introducing and installing the scraping tools and explaining the features of the full application that readers will build throughout the book. You’ll see how to use BeautifulSoup4 and Scrapy individually or together to achieve the desired results. Because many sites use JavaScript, you’ll also employ Selenium with a browser emulator to render these sites and make them ready for scraping.

By the end of this book, you’ll have a complete scraping application to use and rewrite to suit your needs. As a bonus, the author shows you options of how to deploy your spiders into the Cloud to leverage your computer from long-running scraping tasks.

What You’ll Learn

Install and implement scraping tools individually and together
Run spiders to crawl websites for data from the cloud
Work with emulators and drivers to extract data from scripted sites

Who This Book Is For

Readers with some previous Python and software development experience, and an interest in website scraping.