What is the difference between Octoparse and Scrapy?

What is the best web scraping tool in R?

I have a task in which I have to scrape data from a website. I am interested in the most efficient tool in terms of speed and quality of the results.

From my experience I know that: a) R has an excellent library called RSelenium, however it is based on Webdriver, which is not as fast as headless browsers. B) CURL is quite slow, but it is very effective. However, I need to run multiple requests one after another.

C) rvest could be used to scrape, but this is no longer in development (). D) RCurl is probably the fastest of the three. However, it does not work with JavaScript-based pages (which I need to scrape).

So what is the best option for me? Could you please suggest the best tool? This question came from our site for R programming experts. Feel free to select more than one answer if you believe you provide better than one solution. 5 Answers.
To summarize, the best web scraping tool in R is "the one you know how to use." There is no such thing as "the best web scraping tool in R" because "best" is subjective, context-dependent, and a bit like asking what's the best programming language.

Here's a brief review of all of the options that I am aware of: RSelenium provides two major advantages: It uses an existing browser engine and can therefore work on most browsers. It allows you to write and execute R code that operates within the same environment as the browser. You can download the browser from the Selenium IDE, open it, navigate to a web page, and click on buttons. You can then paste the XML returned by the browser into a R script and get the results. This is great for getting started, but it's also very limited, and can be cumbersome to implement.

The downside is that it is browser-based and therefore limited by browser and OS capabilities. For example, I'm not sure if RSelenium would work on IE8 (but I'm pretty sure it works on IE11).

Which tool is best for data scraping?

I have a data scraper.

I'm going to scrape the top 100 apps from the app store and save them as a .csv file. I want to know what tool would best for the job? (I can't spend a lot of money on it because this is just a hobby) Thanks!

If you're familiar with scripting languages, I'd recommend using Perl. The data::table module allows you to manipulate CSV tables as if they were SQL tables.

Perl has some additional advantages, too: It's got excellent support for dealing with all kinds of Internet access. And many other good reasons.

What is the difference between Octoparse and Scrapy?

I want to know which is more useful.

Octoparse is a Python library that uses the built-in GAE APIs to crawl and process websites as if they were hosted in your own environment. It does this by running the specified start URL in a container, processing requests using the Python request and response modules, downloading files, and storing them in a blob storage bucket. Octoparse has options to cache results, control cookies and user agent strings, and to limit the amount of data processed (in Gigabytes).

Scrapy uses the Scrapy libraries to crawl and process a website as it would in a local development environment. It uses a similar user interface to Octoparse, but rather than use standard Python HTTP request and response APIs, it makes use of the standard Scrapy API. This gives you full control over cookies, meta tags, user agents, and more.

While the Octoparse module has more options for customizing how it will crawl websites, it is not recommended for most uses because it relies on standard HTTP request and response modules which make crawling difficult. Most crawling can be achieved using the simple-scrapy module. The Scrapy module makes use of some extensions which allow one to specify different user agents and so forth, but does not provide the degree of control available to the user with the Octoparse module. Scrapy can also be used to directly process XML documents and save them to database.

Requires Python 2.6 or 2.7. Requires requests or mechanize for
Only compatible with Python 2.7 Takes 1GB of memory. Requires Python 2.7 Requires Scrapy libraries (and optional CrawlSpider). Comes with a command line tool. So basically, while both of these are crawlers, Octoparse crawls using the GAE HTTP APIs and saves the output to blob storage while Scrapy's crawler works through direct URLs and saves results to an in memory list of items which get saved to a DB after spider is done. I would go with Scrapy as it has more options and flexibility while supporting Python 2.6 or above. I also like the fact that it is command line based, instead of just a module.

Is Octoparse worth it?

This is my second review on this site of Octoparse.

I've done a few reviews of other sites but they tend to get less use so I thought I would just try it out and see if it has much use as a web-master. I've not done any of the competitions so cannot comment on that but just wanted to give an insight into how this works. I have a Google adsense account but only place my ads on a limited number of websites so I don't expect to be earning any money from this one.

It's free to sign up to Octoparse (the main site is called Octoparse.com but you can sign up for their newsletter here - this is the one that gives you email updates when they launch new features) but like many other things in life it's not free if you want to use it all the time so you need to spend 18.95 per month or 149.95 per year. The good news is that if you are already using a keyword research tool then you can import your findings to this site from that, there is also a monthly price for this service of 99.95 but it's not available to UK residents and so I can't use that service.

For a small site I'm managing I pay 24.95 for a yearly subscription to this service and I find it very useful. My only concern with it is that it seems that they have some kind of problem that has seen their site load slow down quite a bit recently so I have had to close off a few of their domains which has had a big impact on their stats which is what makes me wonder about how reliable their site is. The other advantage of this service is that you can import your rankings into it from other tools (there are quite a few now, I've done the link above) so you can keep an eye on how things are doing.

To summarise, I think Octoparse is worth the cost for a small website but not a big one. The Good and the Bad. So here are my impressions of this site: It's comprehensive. It covers all the niches I'm interested in. It has useful reports. It imports my data from other tools. It's easy to sign up for it.