2018最佳人工智能数据采集(爬虫)工具书下载

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Python网络数据采集

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Python网络数据采集 - 2016.pdf

本书采用简洁强大的Python语言,介绍了网络数据采集,并为采集新式网络中的各种数据类型提供了全面的指导。第 1部分重点介绍网络数据采集的基本原理:如何用Python从网络服务器请求信息,如何对服务器的响应进行基本处理,以及如何以自动化手段与网站进行交互。第 二部分介绍如何用网络爬虫测试网站,自动化处理,以及如何通过更多的方式接入网络。

Web Scraping with Python 2nd - 2018.pdf

https://github.com/REMitchell/python-scraping 2000左右星

讨论钉钉免费群21745728 qq群144081101 567351477

精通Python爬虫框架Scrapy - 2018.pdf

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Scrapy是使用Python开发的一个快速、高层次的屏幕抓取和Web抓取框架,用于抓Web站点并从页面中提取结构化的数据。《精通Python爬虫框架Scrapy》以Scrapy 1.0版本为基础,讲解了Scrapy的基础知识,以及如何使用Python和三方API提取、整理数据,以满足自己的需求。

本书共11章,其内容涵盖了Scrapy基础知识,理解HTML和XPath,安装Scrapy并爬取一个网站,使用爬虫填充数据库并输出到移动应用中,爬虫的强大功能,将爬虫部署到Scrapinghub云服务器,Scrapy的配置与管理,Scrapy编程,管道秘诀,理解Scrapy性能,使用Scrapyd与实时分析进行分布式爬取。本书附录还提供了各种软件的安装与故障排除等内容。
本书适合软件开发人员、数据科学家,以及对自然语言处理和机器学习感兴趣的人阅读。

  • 源码 github星级 300左右

Learning Scrapy -2016.pdf 另有中文电子版本 因为版权已经在CSDN等网站下架,可以在qq群144081101等找到。

精通Scrapy网络爬虫

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本书深入系统地介绍了Python流行框架Scrapy的相关技术及使用技巧。全书共14章,从逻辑上可分为基础篇和高级篇两部分,基础篇重点介绍Scrapy的核心元素,如spider、selector、item、link等;高级篇讲解爬虫的高级话题,如登录认证、文件下载、执行JavaScript、动态网页爬取、使用HTTP代理、分布式爬虫的编写等,并配合项目案例讲解,包括供练习使用的网站,以及知乎、豆瓣、360爬虫案例等。 本书案例丰富,注重实践,代码注释详尽,适合有一定Python语言基础,想学习编写复杂网络爬虫的读者使用。

python3爬虫基础

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在线教程

https://github.com/MorvanZhou/easy-scraping-tutorial 200 左右星

First web scraper

教程:https://first-web-scraper.readthedocs.io/en/latest/

https://github.com/ireapps/first-web-scraper/blob/master/docs/index.rst 200 左右星

Practical Web Scraping for Data Science -Best Practices and Examples with Python - 2018.pdf

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https://github.com/Apress/practical-web-scraping-for-data-science 星级 低于100

This book provides a complete and modern guide to web scraping, using Python as the programming language, without glossing over important details or best practices. Written with a data science audience in mind, the book explores both scraping and the larger context of web technologies in which it operates, to ensure full understanding. The authors recommend web scraping as a powerful tool for any data scientist’s arsenal, as many data science projects start by obtaining an appropriate data set.

Starting with a brief overview on scraping and real-life use cases, the authors explore the core concepts of HTTP, HTML, and CSS to provide a solid foundation. Along with a quick Python primer, they cover Selenium for JavaScript-heavy sites, and web crawling in detail. The book finishes with a recap of best practices and a collection of examples that bring together everything you've learned and illustrate various data science use cases.

用Python写网络爬虫 第2版

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《用Python写网络爬虫(第 2版》讲解了如何使用Python来编写网络爬虫程序,内容包括网络爬虫简介,从页面中抓取数据的3种方法,提取缓存中的数据,使用多个线程和进程进行并发抓取,抓取动态页面中的内容,与表单进行交互,处理页面中的验证码问题,以及使用Scarpy和Portia进行数据抓取,并在最后介绍了使用本书讲解的数据抓取技术对几个真实的网站进行抓取的实例,旨在帮助读者活学活用书中介绍的技术。

《用Python写网络爬虫(第 2版》适合有一定Python编程经验而且对爬虫技术感兴趣的读者阅读。

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Python Web Scraping 2nd Edition - 2017.pdf

第一版中文 用Python写网络爬虫.pdf

https://github.com/kjam/wswp < 100星

Python Web Scraping Cookbook - 2018.pdf

下载

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Python Web Scraping Cookbook is a solution-focused book that will teach you techniques to develop high-performance Scrapers, and deal with cookies, hidden form fields, Ajax-based sites and proxies. You'll explore a number of real-world scenarios where every part of the development or product life cycle will be fully covered. You will not only develop the skills to design reliable, high-performing data flows, but also deploy your codebase to Amazon Web Services (AWS). If you are involved in software engineering, product development, or data mining or in building data-driven products, you will find this book useful as each recipe has a clear purpose and objective.

Right from extracting data from websites to writing a sophisticated web crawler, the book's independent recipes will be extremely helpful while on the job. This book covers Python libraries, requests, and BeautifulSoup. You will learn about crawling, web spidering, working with AJAX websites, and paginated items. You will also understand to tackle problems such as 403 errors, working with proxy, scraping images, and LXML.

By the end of this book, you will be able to scrape websites more efficiently and deploy and operate your scraper in the cloud.

https://github.com/PacktPublishing/Python-Web-Scraping-Cookbook < 100星

Website Scraping with Python - 2018.pdf

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仔细检查网站抓取和数据处理:以适合进一步分析的格式从网站提取数据的技术。您将查看要使用的工具,并比较它们的功能和效率。本书简明扼要专注于BeautifulSoup4和Scrapy,突出了常见问题,并提出了读者可以自行实施的解决方案。

您将看到如何单独或一起使用BeautifulSoup4和Scrapy以获得所需的结果。由于许多站点都使用JavaScript,因此您还将使用Selenium和浏览器模拟器来呈现这些站点。

在本书的最后,您将拥有一个完整的抓取应用程序来使用和重写以满足您的需求。

https://github.com/Apress/website-scraping-w-python

Social Media Data Mining and Analytics - 2018.pdf

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Harness the power of social media to predict customer behaviorand improve sales

Social media is the biggest source of Big Data. Because of this,90% of Fortune 500 companies are investing in Big Data initiativesthat will help them predict consumer behavior to produce bettersales results. Written by Dr. Gabor Szabo, a Senior Data Scientistat Twitter, and Dr. Oscar Boykin, a Software Engineer at Twitter,Social Media Data Mining and Analytics shows analysts how touse sophisticated techniques to mine social media data, obtainingthe information they need to generate amazing results for theirbusinesses.
Social Media Data Mining and Analytics isn’t just anotherbook on the business case for social media. Rather, this bookprovides hands-on examples for applying state-of-the-art tools andtechnologies to mine social media – examples include Twitter,Facebook, Pinterest, Wikipedia, Reddit, Flickr, Web hyperlinks, andother rich data sources. In it, you will learn:

The four key characteristics of online services-users, socialnetworks, actions, and content
The full data discovery lifecycle-data extraction, storage,analysis, and visualization
How to work with code and extract data to create solutions
How to use Big Data to make accurate customer predictions

Szabo and Boykin wrote this book to provide businesses with thecompetitive advantage they need to harness the rich data that isavailable from social media platforms.

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