Web Scraping And Api Fundamentals In Python

Learn Web Scraping with Beautiful Soup and requests-html; harness APIs whenever available; automate data collection!

What you'll learn

Learn the fundamentals of Web Scraping

Implement APIs into your applications

Master working with Beautiful Soup

Start using requests-html

Create functioning scrapers

Scrape jаvascript

Familiarize yourself with HTML

Get the hang of CSS Selectors

Make HTTP requests

Understand website cookies

Explore scraping content locked behind a log-in system

Limit the rate of requests

Requirements

Python 3 and the Anaconda distribution

Basic Python knowledge

Curiosity and enthusiasm to learn and practice

Description

Are you tired of manually copying and pasting values in a spreadsheet?Do you want to learn how to obtain interesting, real-time and even rare information from the internet with a simple script?Are you eager to acquire a valuable skill to stay ahead of the competition in this data-driven world?If the answer is yes, then you have come to the right place at the right time!Welcome to Web Scraping and API Fundamentals in Python!The definitive course on data collection!Web Scraping is a technique for obtaining information from web pages or other sources of data, such as APIs, through the use of intelligent automated programs. Web Scraping allows us to gather data from potentially hundreds or thousands of pages with a few lines of code.From reporting to data science, automating extracting data from the web avoids repetitive work. For example, if you have worked in a serious organization, you certainly know that reporting is a recurring topic. There are daily, weekly, monthly, quarterly, and yearly reports. Whether they aim to organize the website data, transactional data, customer data, or even more easy-going information like the weather forecast – reports are indispensable in the current world. And while sometimes it is the intern's job to take care of that, very few tasks are more cost-saving than the automation of reports.When it comes to data science – more and more data comes from external sources, like webpages, downloadable files, and APIs. Knowing how to extract and structure that data quickly is an essential skill that will set you apart in the job market.Yes, it is time to up your game and learn how you can automate the use of APIs and the extraction of useful info from websites.In the first part of the course, we start with APIs. APIs are specifically designed to provide data to developers, so they are the first place to check when searching for data. We will learn about GET requests, POST requests and the JSON format.These concepts are all explored through interesting examples and in a straight-to-the-point manner.Sometimes, however, the information may not be available through the use of an API, but it is contained on a webpage. What can we do in this scenario? Visit the page and write down the data manually?Please don't ever do that!We will learn how to leverage powerful libraries such as 'Beautiful Soup' and 'requests HTML' to scrape any website out there, no matter what combination of languages are used – HTML, jаvascript, and CSS.Certainly, in order to scrape, you'll need to know a thing or two about web development. That's why we have also included an optional section that covers the basics of HTML. Consider that a bonus to all the knowledge you will acquire!We will also explore several scraping projects. We will obtain and structure data about movies from a "Rotten Tomatoes" rank list, examining each step of the process in detail. This will help you develop a feel for what scraping is like in the real world.We'll also tackle how to scrape data from many webpages at once, an all-to-common need when it comes to data extraction.And then it will be your turn to practice what you've learned with several projects we'll set out for you.But there's even more!Web Scraping may not always go as planned (after all, that's why you will be taking this course). Different websites are built in different ways and often our bots may be obstructed. Because of this, we will make an extra effort to explore common roadblocks that you may encounter while scraping and present you with ways to circumnavigate or deal with those problems. These include request headers and cookies, log-in systems and jаvascript generated content.Don't worry if you are familiar with few or none of these terms. We will start from the basics and build our way to proficiency. Moreover, we are firm believers that practice makes perfect, so this course is not so much on the theory side of things, as it adopts more of a hands-on approach. What's more, it contains plenty of homework exercises, downloadable files and notebooks, as well as quiz questions and course notes.We, the 365 Data Science Team are committed to providing only the highest quality content to you – our students. And while we love creating our content in-house, this time we've decided to team up with a true industry expert - Andrew Treadway. Andrew is a Senior Data Scientist for the New York Life Insurance Company. He holds a Master's degree in Computer Science with Machine learning from the Georgia Institute of Technology and is an outstanding professional with more than 7 years of experience in data-related Python programming. He's also the author of the 'yahoo_fin' package, widely used for scraping historical stock price data from Yahoo.As with all of our courses, you have a 30-day money-back guarantee, if at some point you decide that the training isn't the best fit for you. So. you've got nothing to lose – and everything to gain ?So, what are you waiting for?Click the 'Buy now' button and let's start collecting data together!

Overview

Section 1: Introduction to the course

Lecture 1 What does the course cover?

Lecture 2 What is Web Scraping?

Lecture 3 Ethics of Scraping

Lecture 4 Download All Resources

Section 2: Setting up the environment

Lecture 5 Setting up the environment - Do not skip, please!

Lecture 6 Why Python and why Jupyter?

Lecture 7 Installing Anaconda

Lecture 8 Jupyter Dashboard - Part 1

Lecture 9 Jupyter Dashboard - Part 2

Lecture 10 Installing the packages

Section 3: Working with APIs

Lecture 11 API overview

Lecture 12 HTTP requests: GET and POST requests

Lecture 13 JSON: preferred data exchange format for APIs

Lecture 14 Exchange rates API: GETting a JSON reply

Lecture 15 Incorporating parameters in a GET request

Lecture 16 Additional API functionalities

Lecture 17 Creating a simple currency converter

Lecture 18 iTunes API

Lecture 19 iTunes API: Exercise

Lecture 20 iTunes API: Structuring and exporting the data

Lecture 21 APIs: Exercise

Lecture 22 GitHub API: Pagination

Lecture 23 EDAMAM API: Initial setup and registration

Lecture 24 EDAMAM API: Sending a POST request

Lecture 25 Downloading files with requests

Section 4: HTML overview

Lecture 26 What is HTML?

Lecture 27 Structure of HTML

Lecture 28 Syntax of HTML. Tags

Lecture 29 Tag attributes

Lecture 30 Popular tags

Lecture 31 CSS and jаvascript

Lecture 32 Character encoding

Lecture 33 XHTML and code style

Section 5: Web Scraping with Beautiful Soup

Lecture 34 Introduction to the Beautiful Soup package

Lecture 35 Workflow of Web Scraping

Lecture 36 Setting up your first scraper

Lecture 37 Searching and navigating the HTML tree

Lecture 38 Searching the HTML tree by attributes

Lecture 39 Extracting data from the HTML tree

Lecture 40 Extracting text from an HTML tag

Lecture 41 Practical example: dealing with links

Lecture 42 Practical example: Exercise

Lecture 43 Extracting data from nested HTML tags

Lecture 44 Scraping multiple pages automatically

Section 6: Practical project: Scraping Rotten Tomatoes

Lecture 45 Setting up your scraper

Lecture 46 Extracting the title and year of each movie

Lecture 47 Extracting the score of each movie: Exercise

Lecture 48 Extracting the rest of the information

Lecture 49 Dealing with the cast of the movies

Lecture 50 Extracting the rest of the information: Exercise

Lecture 51 Storing and exporting the data in a structured form

Section 7: Scraping HTML tables

Lecture 52 Scraping HTML tables with the help of Pandas

Section 8: Practical projects

Lecture 53 Scraping Steam

Lecture 54 Scraping YouTube

Section 9: Common roadblocks when scraping

Lecture 55 Common roadblocks when Web Scraping.

Section 10: The requests-html package

Lecture 56 Introduction to the requests-html package

Lecture 57 Exploring the capabilities of requests-html for Web Scraping

Lecture 58 Searching for text

Lecture 59 CSS selectors

Lecture 60 Scraping jаvascript

Lecture 61 Scraping jаvascript: Exercise

Lecture 62 Completing 100%

You should take this course if you want to learn how to use APIs,This course is for you if you want to learn how to scrape websites,Anyone who wants to learn how to automate the boring and mundane everyday tasks,Individuals who are curious and passionate about data,The course is ideal for beginners to programming who want to learn Beautiful Soup and requests-html