Learning Scrapy

Author: Dimitrios Kouzis-Loukas
Publisher: Packt Publishing Ltd
ISBN: 9781784390914
Release Date: 2016-01-30
Genre: Computers

Learn the art of efficient web scraping and crawling with Python About This Book Extract data from any source to perform real time analytics. Full of techniques and examples to help you crawl websites and extract data within hours. A hands-on guide to web scraping and crawling with real-life problems and solutions Who This Book Is For If you are a software developer, data scientist, NLP or machine-learning enthusiast or just need to migrate your company's wiki from a legacy platform, then this book is for you. It is perfect for someone , who needs instant access to large amounts of semi-structured data effortlessly. What You Will Learn Understand HTML pages and write XPath to extract the data you need Write Scrapy spiders with simple Python and do web crawls Push your data into any database, search engine or analytics system Configure your spider to download files, images and use proxies Create efficient pipelines that shape data in precisely the form you want Use Twisted Asynchronous API to process hundreds of items concurrently Make your crawler super-fast by learning how to tune Scrapy's performance Perform large scale distributed crawls with scrapyd and scrapinghub In Detail This book covers the long awaited Scrapy v 1.0 that empowers you to extract useful data from virtually any source with very little effort. It starts off by explaining the fundamentals of Scrapy framework, followed by a thorough description of how to extract data from any source, clean it up, shape it as per your requirement using Python and 3rd party APIs. Next you will be familiarised with the process of storing the scrapped data in databases as well as search engines and performing real time analytics on them with Spark Streaming. By the end of this book, you will perfect the art of scarping data for your applications with ease Style and approach It is a hands on guide, with first few chapters written as a tutorial, aiming to motivate you and get you started quickly. As the book progresses, more advanced features are explained with real world examples that can be reffered while developing your own web applications.

Learning Scrapy

Author: Dimitris Kouzis - Loukas
Publisher:
ISBN: 1784399787
Release Date: 2016-01-29
Genre: Computers

Learn the art of efficient web scraping and crawling with PythonAbout This Book• Extract data from any source to perform real time analytics.• Full of techniques and examples to help you crawl websites and extract data within hours.• A hands-on guide to web scraping and crawling with real-life problems and solutionsWho This Book Is ForIf you are a software developer, data scientist, NLP or machine-learning enthusiast or just need to migrate your company's wiki from a legacy platform, then this book is for you. It is perfect for someone , who needs instant access to large amounts of semi-structured data effortlessly.What You Will Learn• Understand HTML pages and write XPath to extract the data you need• Write Scrapy spiders with simple Python and do web crawls• Push your data into any database, search engine or analytics system• Configure your spider to download files, images and use proxies• Create efficient pipelines that shape data in precisely the form you want• Use Twisted Asynchronous API to process hundreds of items concurrently• Make your crawler super-fast by learning how to tune Scrapy's performance• Perform large scale distributed crawls with scrapyd and scrapinghubIn DetailThis book covers the long awaited Scrapy v 1.0 that empowers you to extract useful data from virtually any source with very little effort. It starts off by explaining the fundamentals of Scrapy framework, followed by a thorough description of how to extract data from any source, clean it up, shape it as per your requirement using Python and 3rd party APIs. Next you will be familiarised with the process of storing the scrapped data in databases as well as search engines and performing real time analytics on them with Spark Streaming. By the end of this book, you will perfect the art of scarping data for your applications with easeStyle and approachIt is a hands on guide, with first few chapters written as a tutorial, aiming to motivate you and get you started quickly. As the book progresses, more advanced features are explained with real world examples that can be reffered while developing your own web applications.

Machine Learning for the Web

Author: Andrea Isoni
Publisher: Packt Publishing Ltd
ISBN: 9781785888724
Release Date: 2016-07-29
Genre: Computers

Explore the web and make smarter predictions using Python About This Book Targets two big and prominent markets where sophisticated web apps are of need and importance. Practical examples of building machine learning web application, which are easy to follow and replicate. A comprehensive tutorial on Python libraries and frameworks to get you up and started. Who This Book Is For The book is aimed at upcoming and new data scientists who have little experience with machine learning or users who are interested in and are working on developing smart (predictive) web applications. Knowledge of Django would be beneficial. The reader is expected to have a background in Python programming and good knowledge of statistics. What You Will Learn Get familiar with the fundamental concepts and some of the jargons used in the machine learning community Use tools and techniques to mine data from websites Grasp the core concepts of Django framework Get to know the most useful clustering and classification techniques and implement them in Python Acquire all the necessary knowledge to build a web application with Django Successfully build and deploy a movie recommendation system application using the Django framework in Python In Detail Python is a general purpose and also a comparatively easy to learn programming language. Hence it is the language of choice for data scientists to prototype, visualize, and run data analyses on small and medium-sized data sets. This is a unique book that helps bridge the gap between machine learning and web development. It focuses on the difficulties of implementing predictive analytics in web applications. We focus on the Python language, frameworks, tools, and libraries, showing you how to build a machine learning system. You will explore the core machine learning concepts and then develop and deploy the data into a web application using the Django framework. You will also learn to carry out web, document, and server mining tasks, and build recommendation engines. Later, you will explore Python's impressive Django framework and will find out how to build a modern simple web app with machine learning features. Style and approach Instead of being overwhelmed with multiple concepts at once, this book provides a step-by-step approach that will guide you through one topic at a time. An intuitive step-by step guide that will focus on one key topic at a time. Building upon the acquired knowledge in each chapter, we will connect the fundamental theory and practical tips by illustrative visualizations and hands-on code examples.

Web Scraping with Python

Author: Ryan Mitchell
Publisher: "O'Reilly Media, Inc."
ISBN: 9781491910252
Release Date: 2015-06-15
Genre: Computers

Learn web scraping and crawling techniques to access unlimited data from any web source in any format. With this practical guide, you’ll learn how to use Python scripts and web APIs to gather and process data from thousands—or even millions—of web pages at once. Ideal for programmers, security professionals, and web administrators familiar with Python, this book not only teaches basic web scraping mechanics, but also delves into more advanced topics, such as analyzing raw data or using scrapers for frontend website testing. Code samples are available to help you understand the concepts in practice. Learn how to parse complicated HTML pages Traverse multiple pages and sites Get a general overview of APIs and how they work Learn several methods for storing the data you scrape Download, read, and extract data from documents Use tools and techniques to clean badly formatted data Read and write natural languages Crawl through forms and logins Understand how to scrape JavaScript Learn image processing and text recognition

Data Visualization with Python and JavaScript

Author: Kyran Dale
Publisher: "O'Reilly Media, Inc."
ISBN: 9781491920541
Release Date: 2016-06-30
Genre: Computers

Learn how to turn raw data into rich, interactive web visualizations with the powerful combination of Python and JavaScript. With this hands-on guide, author Kyran Dale teaches you how build a basic dataviz toolchain with best-of-breed Python and JavaScript libraries—including Scrapy, Matplotlib, Pandas, Flask, and D3—for crafting engaging, browser-based visualizations. As a working example, throughout the book Dale walks you through transforming Wikipedia’s table-based list of Nobel Prize winners into an interactive visualization. You’ll examine steps along the entire toolchain, from scraping, cleaning, exploring, and delivering data to building the visualization with JavaScript’s D3 library. If you’re ready to create your own web-based data visualizations—and know either Python or JavaScript— this is the book for you. Learn how to manipulate data with Python Understand the commonalities between Python and JavaScript Extract information from websites by using Python’s web-scraping tools, BeautifulSoup and Scrapy Clean and explore data with Python’s Pandas, Matplotlib, and Numpy libraries Serve data and create RESTful web APIs with Python’s Flask framework Create engaging, interactive web visualizations with JavaScript’s D3 library

Learning Penetration Testing with Python

Author: Christopher Duffy
Publisher: Packt Publishing
ISBN: 1785282328
Release Date: 2015-09-30
Genre: Computers

Utilize Python scripting to execute effective and efficient penetration testsAbout This Book• Understand how and where Python scripts meet the need for penetration testing• Familiarise yourself with the process of highlighting a specific methodology to exploit an environment to fetch critical data• Develop your Python and penetration testing skills with real-world examplesWho This Book Is ForIf you are a security professional or researcher, with knowledge of different operating systems and a conceptual idea of penetration testing, and you would like to grow your knowledge in Python, then this book is ideal for you.What You Will Learn• Familiarise yourself with the generation of Metasploit resource files• Use the Metasploit Remote Procedure Call (MSFRPC) to automate exploit generation and execution• Use Python's Scrapy, network, socket, office, Nmap libraries, and custom modules• Parse Microsoft Office spreadsheets and eXtensible Markup Language (XML) data files• Write buffer overflows and reverse Metasploit modules to expand capabilities• Exploit Remote File Inclusion (RFI) to gain administrative access to systems with Python and other scripting languages• Crack an organization's Internet perimeter• Chain exploits to gain deeper access to an organization's resources• Interact with web services with PythonIn DetailPython is a powerful new-age scripting platform that allows you to build exploits, evaluate services, automate, and link solutions with ease. Python is a multi-paradigm programming language well suited to both object-oriented application development as well as functional design patterns. Because of the power and flexibility offered by it, Python has become one of the most popular languages used for penetration testing.This book highlights how you can evaluate an organization methodically and realistically. Specific tradecraft and techniques are covered that show you exactly when and where industry tools can and should be used and when Python fits a need that proprietary and open source solutions do not.Initial methodology, and Python fundamentals are established and then built on. Specific examples are created with vulnerable system images, which are available to the community to test scripts, techniques, and exploits. This book walks you through real-world penetration testing challenges and how Python can help.From start to finish, the book takes you through how to create Python scripts that meet relative needs that can be adapted to particular situations. As chapters progress, the script examples explain new concepts to enhance your foundational knowledge, culminating with you being able to build multi-threaded security tools, link security tools together, automate reports, create custom exploits, and expand Metasploit modules.Style and approachThis book is a practical guide that will help you become better penetration testers and/or Python security tool developers. Each chapter builds on concepts and tradecraft using detailed examples in test environments that you can simulate.

Web Scraping with Python

Author: Richard Lawson
Publisher: Packt Publishing Ltd
ISBN: 9781782164371
Release Date: 2015-10-28
Genre: Computers

Successfully scrape data from any website with the power of Python About This Book A hands-on guide to web scraping with real-life problems and solutions Techniques to download and extract data from complex websites Create a number of different web scrapers to extract information Who This Book Is For This book is aimed at developers who want to use web scraping for legitimate purposes. Prior programming experience with Python would be useful but not essential. Anyone with general knowledge of programming languages should be able to pick up the book and understand the principals involved. What You Will Learn Extract data from web pages with simple Python programming Build a threaded crawler to process web pages in parallel Follow links to crawl a website Download cache to reduce bandwidth Use multiple threads and processes to scrape faster Learn how to parse JavaScript-dependent websites Interact with forms and sessions Solve CAPTCHAs on protected web pages Discover how to track the state of a crawl In Detail The Internet contains the most useful set of data ever assembled, largely publicly accessible for free. However, this data is not easily reusable. It is embedded within the structure and style of websites and needs to be carefully extracted to be useful. Web scraping is becoming increasingly useful as a means to easily gather and make sense of the plethora of information available online. Using a simple language like Python, you can crawl the information out of complex websites using simple programming. This book is the ultimate guide to using Python to scrape data from websites. In the early chapters it covers how to extract data from static web pages and how to use caching to manage the load on servers. After the basics we'll get our hands dirty with building a more sophisticated crawler with threads and more advanced topics. Learn step-by-step how to use Ajax URLs, employ the Firebug extension for monitoring, and indirectly scrape data. Discover more scraping nitty-gritties such as using the browser renderer, managing cookies, how to submit forms to extract data from complex websites protected by CAPTCHA, and so on. The book wraps up with how to create high-level scrapers with Scrapy libraries and implement what has been learned to real websites. Style and approach This book is a hands-on guide with real-life examples and solutions starting simple and then progressively becoming more complex. Each chapter in this book introduces a problem and then provides one or more possible solutions.

Data Wrangling with Python

Author: Jacqueline Kazil
Publisher: "O'Reilly Media, Inc."
ISBN: 9781491948774
Release Date: 2016-02-04
Genre: Computers

How do you take your data analysis skills beyond Excel to the next level? By learning just enough Python to get stuff done. This hands-on guide shows non-programmers like you how to process information that’s initially too messy or difficult to access. You don't need to know a thing about the Python programming language to get started. Through various step-by-step exercises, you’ll learn how to acquire, clean, analyze, and present data efficiently. You’ll also discover how to automate your data process, schedule file- editing and clean-up tasks, process larger datasets, and create compelling stories with data you obtain. Quickly learn basic Python syntax, data types, and language concepts Work with both machine-readable and human-consumable data Scrape websites and APIs to find a bounty of useful information Clean and format data to eliminate duplicates and errors in your datasets Learn when to standardize data and when to test and script data cleanup Explore and analyze your datasets with new Python libraries and techniques Use Python solutions to automate your entire data-wrangling process

Data Science from Scratch

Author: Joel Grus
Publisher: "O'Reilly Media, Inc."
ISBN: 9781491904404
Release Date: 2015-04-14
Genre: BUSINESS & ECONOMICS

Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

NLTK Essentials

Author: Nitin Hardeniya
Publisher: Packt Publishing Ltd
ISBN: 9781784398507
Release Date: 2015-07-27
Genre: Computers

Natural Language Processing (NLP) is the field of artificial intelligence and computational linguistics that deals with the interactions between computers and human languages. With the instances of human-computer interaction increasing, it's becoming imperative for computers to comprehend all major natural languages. Natural Language Toolkit (NLTK) is one such powerful and robust tool. You start with an introduction to get the gist of how to build systems around NLP. We then move on to explore data science-related tasks, following which you will learn how to create a customized tokenizer and parser from scratch. Throughout, we delve into the essential concepts of NLP while gaining practical insights into various open source tools and libraries available in Python for NLP. You will then learn how to analyze social media sites to discover trending topics and perform sentiment analysis. Finally, you will see tools which will help you deal with large scale text. By the end of this book, you will be confident about NLP and data science concepts and know how to apply them in your day-to-day work.

Learning Python

Author: Mark Lutz
Publisher: "O'Reilly Media, Inc."
ISBN: 9781449355692
Release Date: 2013-06-12
Genre: Computers

Get a comprehensive, in-depth introduction to the core Python language with this hands-on book. Based on author Mark Lutz’s popular training course, this updated fifth edition will help you quickly write efficient, high-quality code with Python. It’s an ideal way to begin, whether you’re new to programming or a professional developer versed in other languages. Complete with quizzes, exercises, and helpful illustrations, this easy-to-follow, self-paced tutorial gets you started with both Python 2.7 and 3.3— the latest releases in the 3.X and 2.X lines—plus all other releases in common use today. You’ll also learn some advanced language features that recently have become more common in Python code. Explore Python’s major built-in object types such as numbers, lists, and dictionaries Create and process objects with Python statements, and learn Python’s general syntax model Use functions to avoid code redundancy and package code for reuse Organize statements, functions, and other tools into larger components with modules Dive into classes: Python’s object-oriented programming tool for structuring code Write large programs with Python’s exception-handling model and development tools Learn advanced Python tools, including decorators, descriptors, metaclasses, and Unicode processing

Learning Data Mining with Python

Author: Robert Layton
Publisher: Packt Publishing Ltd
ISBN: 9781784391201
Release Date: 2015-07-29
Genre: Computers

The next step in the information age is to gain insights from the deluge of data coming our way. Data mining provides a way of finding this insight, and Python is one of the most popular languages for data mining, providing both power and flexibility in analysis. This book teaches you to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis. Next, we move on to more complex data types including text, images, and graphs. In every chapter, we create models that solve real-world problems. There is a rich and varied set of libraries available in Python for data mining. This book covers a large number, including the IPython Notebook, pandas, scikit-learn and NLTK. Each chapter of this book introduces you to new algorithms and techniques. By the end of the book, you will gain a large insight into using Python for data mining, with a good knowledge and understanding of the algorithms and implementations.

Python Cookbook

Author: David Beazley
Publisher: "O'Reilly Media, Inc."
ISBN: 9781449357351
Release Date: 2013-05-10
Genre: Computers

If you need help writing programs in Python 3, or want to update older Python 2 code, this book is just the ticket. Packed with practical recipes written and tested with Python 3.3, this unique cookbook is for experienced Python programmers who want to focus on modern tools and idioms. Inside, you’ll find complete recipes for more than a dozen topics, covering the core Python language as well as tasks common to a wide variety of application domains. Each recipe contains code samples you can use in your projects right away, along with a discussion about how and why the solution works. Topics include: Data Structures and Algorithms Strings and Text Numbers, Dates, and Times Iterators and Generators Files and I/O Data Encoding and Processing Functions Classes and Objects Metaprogramming Modules and Packages Network and Web Programming Concurrency Utility Scripting and System Administration Testing, Debugging, and Exceptions C Extensions

Instant Web Scraping with Java

Author: Ryan Mitchell
Publisher: Packt Publishing Ltd
ISBN: 9781849696890
Release Date: 2013-01-01
Genre: Computers

This book is full of short, concise recipes to learn a variety of useful web scraping techniques using Java. You will start with a simple basic recipe of setting up your Java environment and gradually learn some more advanced recipes such as using complex Scrapers.Instant Web Scraping with Java is aimed at developers who, while not necessarily familiar with Java, are at least ready to dive into the complexities of this language with simple, step-by-step instructions leading the way. It is assumed that you have at least an intermediate knowledge of HTML, some knowledge of MySQL, and access to an Internet-connected computer while doing most of the exercises (after all, scraping the Web is difficult if your code can't get online!)

Getting Started with Beautiful Soup

Author: Vineeth G. Nair
Publisher: Packt Publishing Ltd
ISBN: 9781783289561
Release Date: 2014-01-24
Genre: Computers

This book is a practical, hands-on guide that takes you through the techniques of web scraping using Beautiful Soup. Getting Started with Beautiful Soup is great for anybody who is interested in website scraping and extracting information. However, a basic knowledge of Python, HTML tags, and CSS is required for better understanding.