The internet contains a wealth of data. This data is both provided through structured APIs as well as by content delivered directly through websites. While the data in APIs is highly structured, information found in web pages is often unstructured and requires collection, extraction, and processing to be of value. And collecting data is just the start of the journey, as that data must also be stored, mined, and then exposed to others in a value-added form.
With this book, you will learn many of the core tasks needed in collecting various forms of information from websites. We will cover how to collect it, how to perform several common data operations (including storage in local and remote databases), how to perform common media-based tasks such as converting images an videos to thumbnails, how to clean unstructured data with NTLK, how to examine several data mining and visualization tools, and finally core skills in building a microservices-based scraper and API that can, and will, be run on the cloud.
Through a recipe-based approach, we will learn independent techniques to solve specific tasks involved in not only scraping but also data manipulation and management, data mining, visualization, microservices, containers, and cloud operations. These recipes will build skills in a progressive and holistic manner, not only teaching how to perform the fundamentals of scraping but also taking you from the results of scraping to a service offered to others through the cloud. We will be building an actual web-scraper-as-a-service using common tools in the Python, container, and cloud ecosystems.
