ChunkedTerminationError ResponseReadErrorMechanize File 'lib/ mechanize/icvamlakunsva.tk', line def pdf=(klass) register_parser( CONTENT_TYPES[:pdf], Generated on Thu Feb 14 by yard 16 (ruby). GETs uri and writes it to io_or_filename without recording the request in the history. If io_or_filename does not respond to #write it will be used as a file name. Method: Mechanize::PluggableParser#pdf= Defined in: lib/mechanize/ icvamlakunsva.tk #pdf=(klass) ⇒ Object. Registers klass as the parser for application/pdf content Generated on Thu Feb 14 by yard (ruby).
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Here is an example that saves all the PDF files it encounters: require 'rubygems' require 'mechanize' agent = icvamlakunsva.tk icvamlakunsva.tk Mechanize is the obvious choice if you need to scrape websites in Ruby, but it can be confusing to use. Particularly if you're new to web scraping, or new to. A simple Ruby script to scrape PDF files from an Indian newspaper website. In case of errors see icvamlakunsva.tk for inforamtion. #. # With a.
This will allow you to manage gems for our scraping project. You'll now notice there is a Gemfile in your project directory. This is where we can specify the gems we want to use in our project. Make sure your Gemfile looks like this:. You should also be using a browser like Chrome or Firefox which has an extensive set of developer tools for debugging.
Before we can programmatically scrape a page, we need to know what we actually want to pull off of it. The only way to do so is by first inspecting the page manually and taking a few notes along the way.
First, we set up a Ruby script. These all end in.
For the sake of being extremely accessible to various readers, we're going to write this scraper in an entirely linear, procedural style, but if you're used to object-oriented programming in Ruby, it should be pretty trivial to wrap all this in a portable, modular ApartmentScraper object.
We'll start by using require statements to call in the various modules we need for the script. That includes:. The scraper is a new Mechanize object that has all the powers of the Mechanize gem.
We'll get into the special methods it contains soon enough. What it's doing is rate limiting your scraping, so that you stop and wait half a second between each time you visit a page.
If you go much faster than that, many sites will decide your scraper is a bot that might be DDOSing them or otherwise up to no good, so this way you just look like a human clicking through things quickly.
This way, it's only hard-coded in one place. If you had been scraping a site in more varied ways for more than just apartments.
Next up, we pull up our information grabbed from that initial information scavenger hunt and start the scrape in earnest. First, everything in your scraping session is going to be wrapped up in a single block of Ruby code that looks like this:.
That variable gives you all the HTML of visiting the actual page, plus some very convenient methods to find elements and keep navigating through the site. Pass in an id, and we get that specific form back as a Ruby object.
However, we'll take one step further and pass it a block of configuration code, which is very common Ruby style. In that configuration code, we can directly fill in form fields by name.
Web Scraping with Ruby and Nokogiri for Beginners
Remember how we grabbed the field names in the setup? You'll see below how that works:. The result? This is going to be our test run, so we just make up some parameters for the query, min price and max price fields.
With the form all set to go, we can submit the form and again return a new object representing the results page, using a convenient submit method found on Mechanize form objects:.
Now that you've got this far, it's going to be time to do some dirtier work: In order to do that, you probably want to pull up a console like Pry that lets you input Ruby code on the fly and try various commands out on your variables.
That means that when your script runs, it will stop at that point and start a console in which you can inspect current variables. Run your script on the command line by typing ruby scrape. Pry has built-in object inspection, so it'll show you a giant object full of instance variables.
Check out properties of the object like forms or links or the raw HTML with body. But really, what you're looking to do is to grab a collection of all the results that you can then parse for data.
Then, we run an each iterator through all of those rows, grabbing the actual link inside that contains all the useful information for each result. What that looks like in code:. Now, it's time to parse those result fields in specific to get the information you'd like to save into your spreadsheet.
What can you grab from that initial search page?
The link itself, the title of the listing, the price of the apartment, and the location. These take a lot more inspecting of the result element to figure out in detail, so we'll poke around for a while. So the name is the easy part. It's just the text of the link, and you use. Now that we have a mechnize instance, we can retrieve the login page of the application we need to login to.
Fetching the data Now that we are logged in properly, we can start retrieving our data.
This page contains the data table we need. But a single page is limited to 20 items, but we currently hold items. So that means we have about 10 pages to process. So on each page you will find a table containing data.
So we want to collect the following data: first name: column 4. Download agent. Renato Renato 4 9. I would add that I've just exactly used your solution except I had Mechanize: FileSaver instead of Mechanize: I've just replaced it with Download and the whole is perfect: Where does the file get saved?
Scripting Beyond HTML
Here is an example that saves all the PDF files it encounters: FileSaver agent. Nemo 2, 2 20 Gerhard Gerhard 4, 3 40 Sign up or log in Sign up using Google.
Sign up using Facebook. Sign up using Email and Password. Post as a guest Name. Email Required, but never shown. Featured on Meta.Typical tasks would be: generate a pdf invoice every 2 weeks and email it to your employer generate a "hall of fame" list based on a text file of names and upload it to the right place on an FTP server automatically scan a given web page for some text and do stuff when a particular phrase is detected see the sci-fi novel Daemon for an interesting take on this.
Use RestClient. I've just replaced it with Download and the whole is perfect: What are things that could break your scraper? So, you loop through your 2D results array, row by row and shovel them all onto this file object. Just use your browser's "inspect element" feature to figure this out.
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