05Aug 2020 by Andrew Treadway
How to scrape news articles with Python

How to scrape news articles with Python

Python, Web Scraping
In this post we're going to discuss how to scrape news articles with Python. This can be done using the handy newspaper package. Introduction to Python's newspaper package The newspaper package can be installed using pip: [code] pip install newspaper [/code] Once its installed, we can get started. newspaper can work by either scraping a single article from a given URL, or by finding the links on a webpage to other news articles. Let's start with handling a single article. First, we need to import the Article class. Next, we use this class to download the content from the URL to our news article. Then, we use the parse method to parse the HTML. Lastly, we can print out the text of the article using .text. Scraping a single article…
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05May 2020 by Andrew Treadway
How to download fundamentals data with Python

How to download fundamentals data with Python

Python, Web Scraping
How can we download fundamentals data with Python? In this post we will explore how to download fundamentals data with Python. We'll be extracting fundamentals data from Yahoo Finance using the yahoo_fin package. For more on yahoo_fin, including installation instructions, check out its full documentation here or my YouTube video tutorials here. Getting started Now, let's import the stock_info module from yahoo_fin. This will provide us with the functionality we need to scrape fundamentals data from Yahoo Finance. We'll also import the pandas package as we'll be using that later to work with data frames. [code lang="python"] import yahoo_fin.stock_info as si import pandas as pd [/code] Next, we'll dive into getting common company metrics, starting with P/E ratios. How to get P/E (Price-to-Earnings) Ratios There's a couple ways to get…
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25Mar 2020 by Andrew Treadway
Python for Web Scraping and APIs Online Course

Python for Web Scraping and APIs Online Course

Python, Web Scraping
I recently worked with a great team at 365 Data Science to create an extensive online Python for Web Scraping and APIs course! The course is now available on Udemy. Check it out here! The course covers many important topics, including the following: All about APIs: Get and Post requests HTML syntax - what's it for and why is it useful for web scraping BeautifulSoup - scraping links, text, and other elements from a webpage How to easily scrape tables from webpages How to automatically download files from the web Handling modern challenges: how to scrape JavaScript-rendered webpages Exploring the requests-html package, a powerful alternative to BeautifulSoup Click here to learn more about Python for Web Scraping and APIs Fundamentals! For other resources on learning Python or R, also check…
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23Jul 2019 by Andrew Treadway
BeautifulSoup vs. Rvest

BeautifulSoup vs. Rvest

Python, R, Web Scraping
This post will compare Python's BeautifulSoup package to R's rvest package for web scraping. We'll also talk about additional functionality in rvest (that doesn't exist in BeautifulSoup) in comparison to a couple of other Python packages (including pandas and RoboBrowser). Getting started BeautifulSoup and rvest both involve creating an object that we can use to parse the HTML from a webpage. However, one immediate difference is that BeautifulSoup is just a web parser, so it doesn't connect to webpages. rvest, on the other hand, can connect to a webpage and scrape / parse its HTML in a single package. In BeautifulSoup, our initial setup looks like this: [code lang="python"] # load packages from bs4 import BeautifulSoup import requests # connect to webpage resp = requests.get(""https://www.azlyrics.com/b/beatles.html"") # get BeautifulSoup object soup…
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22Jun 2019 by Andrew Treadway
Web Browsing and Parsing with RoboBrowser and requests_html

Web Browsing and Parsing with RoboBrowser and requests_html

Python, Web Scraping
Background So you've learned all about BeautifulSoup. What's next? Python is a great language for automating web operations. In a previous article we went through how to use BeautifulSoup and requests to scrape stock-related articles from Nasdaq's website. This post talks about a couple of alternatives to using BeautifulSoup directly. One way of scraping and crawling the web is to use Python's RoboBrowser package, which is built on top of requests and BeautifulSoup. Because it's built using each of these packages, writing code to scrape the web is a bit simplified as we'll see below. RoboBrowser works similarly to the older Python 2.x package mechanize in that it allows you to simulate a web browser. A second option is using requests_html, which was also discussed here, and which we'll also…
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29Jan 2019 by Andrew Treadway
Creating a word cloud on R-bloggers posts

Creating a word cloud on R-bloggers posts

R, Web Scraping
This post will go through how to create a word cloud of article titles scraped from the awesome R-bloggers. Our goal will be to use R's rvest package to search through 50 successive pages on the site for article titles. The stringr and tm packages will be used for string cleaning and for creating a term document frequency matrix (with tm). We will then create a word cloud based off the words comprising these titles. First, we'll load the packages we need. [code lang="R"] # load packages library(rvest) library(stringr) library(tm) library(wordcloud) [/code] Let's write a function that will take a webpage as input and return all the scraped article titles. [code lang="R"] scrape_post_titles <- function(site) { # scrape HTML from input site source_html <- read_html(site) # grab the title attributes…
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19Jan 2019 by Andrew Treadway
Scraping data from a JavaScript webpage with Python

Scraping data from a JavaScript webpage with Python

Python, Web Scraping
This post will walk through how to use the requests_html package to scrape options data from a JavaScript-rendered webpage. requests_html serves as an alternative to Selenium and PhantomJS, and provides a clear syntax similar to the awesome requests package. The code we'll walk through is packaged into functions in the options module in the yahoo_fin package, but this article will show how to write the code from scratch using requests_html so that you can use the same idea to scrape other JavaScript-rendered webpages. Note: requests_html requires Python 3.6+. If you don't have requests_html installed, you can download it using pip: [cc] pip install requests_html [/cc] Motivation Let's say we want to scrape options data for a particular stock. As an example, let's look at Netflix (since it's well known). If…
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31Jul 2018 by Andrew Treadway

How to get live stock prices with Python

Python, Web Scraping
In a previous post, I gave an introduction to the yahoo_fin package. The most updated version of the package includes new functionality allowing you to scrape live stock prices from Yahoo Finance (real-time). In this article, we'll go through a couple ways of getting real-time data from Yahoo Finance for stocks, as well as how to pull cryptocurrency price information. The get_live_price function First, we just need to load the stock_info module from yahoo_fin. [code lang="python"] # import stock_info module from yahoo_fin from yahoo_fin import stock_info as si [/code] Then, obtaining the current price of a stock is as simple as one line of code: [code lang="python"] # get live price of Apple si.get_live_price("aapl") # or Amazon si.get_live_price("amzn") # or any other ticker si.get_live_price(ticker) [/code] Note: Passing tickers is not…
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16Jul 2018 by Andrew Treadway
How to download image files with RoboBrowser

How to download image files with RoboBrowser

Python, Web Scraping
In a previous post, we showed how RoboBrowser can be used to fill out online forms for getting historical weather data from Wunderground. This article will talk about how to use RoboBrowser to batch download collections of image files from Pexels, a site which offers free downloads. If you're looking to work with images, or want to build a training set for an image classifier with Python, this post will help you do that. In the first part of the code, we'll load the RoboBrowser class from the robobrowser package, create a browser object which acts like a web browser, and navigate to the Pexels website. [code lang="python"] # load the RoboBrowser class from robobrowser from robobrowser import RoboBrowser # define base site base = "https://www.pexels.com/" # create browser object,…
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