Up until now, your deployment process using Scrapy Cloud has probably been something like this: code and test your spiders locally, commit and push your changes to a GitHub repository, and finally deploy them to Scrapy Cloud using shub deploy.

Computers are great at repetitive tasks. They don't get distracted, bored, or tired.

Let's start with what is XPath? XPath is a powerful language that is often used for scraping the web. It allows you to select nodes or compute values from an XML or HTML document and is actually one of the languages that you can use to extract web data using Scrapy.

You can deploy, run, and maintain control over your Scrapy spiders in Scrapy Cloud, our production environment.

What if you could have complete control over your environment? Your crawling environment, that is...

The first rule of web crawling is you do not harm the website. The second rule of web crawling is you do NOT harm the website. We’re supporters of the democratization of web data, but not at the expense of the website’s owners.

It’s the end of an era. Python 2 is on its way out with only a few security and bug fixes forthcoming from now until its official retirement in 2020.

We eat our own spider food since Scrapy is our go-to workhorse on a daily basis. However, there are certain situations where Scrapy can be overkill and that’s when we use Parsel.

Fasten your seat belts, ladies and gentlemen: Scrapy 1.1 with Python 3 support is officially out! After a couple of months of hard work and four release candidates, this is the first official Scrapy release to support Python 3.

Welcome to Scrapy Tips from the Pros! Every month we release a few tricks and hacks to help speed up your web scraping and data extraction activities.

We recently announced our integration with MonkeyLearn, bringing machine learning to Scrapy Cloud. MonkeyLearn offers numerous text analysis services via its API. Since there are so many uses to this platform addon, we’re launching a series of tutorials to help get you started.

Welcome to the April Edition of Scrapy Tips from the Pros. Each month we’ll release a few tricks and hacks that we’ve developed to help make your Scrapy workflow go more smoothly.

Update: With the release of the Panama Papers, a reliable means of exposing corruption and the methods of money laundering and tax evasion are now even more important. Web scraping provides an avenue to find, collate, and organize data without relying on information leaks.

We’re pleased to announce that Splash 2.0 is officially live after many months of hard work.

Heads up, Kimono Labs users!
Today, we are releasing a tool to help you migrate your Kimono projects to Portia.

Welcome to the February Edition of Scrapy Tips from the Pros. Each month we’ll release a few tips and hacks that we’ve developed to help make your Scrapy workflow go more smoothly.

Imagine your business depended heavily on a third party tool and one day that company decided to shut down its service with only 2 weeks notice. That, unfortunately, is what happened to users of Kimono Labs yesterday.

Today we released the latest version of Portia bringing with it the ability to crawl pages that require JavaScript. To celebrate this release we are making Splash available as a free trial to all Portia users so you can try it out with your projects.

When scraping content from the web, you often crawl websites which you have no prior knowledge of. Link analysis algorithms are incredibly useful in these scenarios to guide the crawler to relevant pages.

33 Zytans from 15 countries will be meeting (most of them, for the first time) in Bilbao, for what is going to be our largest get-together event so far.

It's not uncommon to need to crawl a large number of unfamiliar websites when gathering content. Page ranking algorithms are incredibly useful in these scenarios as it can be tricky to determine which pages are relevant to the content you're looking for.

Imagine that you have a lot of samples for a certain kind of data in JSON format. Maybe you want to have a better feel of it, know which fields appear in all records, which appear only in some and what are their types. In other words, you want to know the schema for the data that you have.

In the context of web scraping, XPath is a nice tool to have in your belt, as it allows you to write specifications of document locations more flexibly than CSS selectors.

One of the things that takes more time when building a spider is reviewing the scraped data and making sure it conforms to the requirements and expectations of your client or team.

We have released an lxml-based version of this code as an open-source library called extruct. The Source code is on Github, and the package is available on PyPI. Enjoy!

Up until now, your deployment process using Scrapy Cloud has probably been something like this: code and test your spiders locally, commit and push your changes to a GitHub repository, and finally deploy them to Scrapy Cloud using shub deploy.

Computers are great at repetitive tasks. They don't get distracted, bored, or tired.

Let's start with what is XPath? XPath is a powerful language that is often used for scraping the web. It allows you to select nodes or compute values from an XML or HTML document and is actually one of the languages that you can use to extract web data using Scrapy.

You can deploy, run, and maintain control over your Scrapy spiders in Scrapy Cloud, our production environment.

What if you could have complete control over your environment? Your crawling environment, that is...

The first rule of web crawling is you do not harm the website. The second rule of web crawling is you do NOT harm the website. We’re supporters of the democratization of web data, but not at the expense of the website’s owners.

It’s the end of an era. Python 2 is on its way out with only a few security and bug fixes forthcoming from now until its official retirement in 2020.

We eat our own spider food since Scrapy is our go-to workhorse on a daily basis. However, there are certain situations where Scrapy can be overkill and that’s when we use Parsel.

Fasten your seat belts, ladies and gentlemen: Scrapy 1.1 with Python 3 support is officially out! After a couple of months of hard work and four release candidates, this is the first official Scrapy release to support Python 3.

Welcome to Scrapy Tips from the Pros! Every month we release a few tricks and hacks to help speed up your web scraping and data extraction activities.

We recently announced our integration with MonkeyLearn, bringing machine learning to Scrapy Cloud. MonkeyLearn offers numerous text analysis services via its API. Since there are so many uses to this platform addon, we’re launching a series of tutorials to help get you started.

Welcome to the April Edition of Scrapy Tips from the Pros. Each month we’ll release a few tricks and hacks that we’ve developed to help make your Scrapy workflow go more smoothly.

Update: With the release of the Panama Papers, a reliable means of exposing corruption and the methods of money laundering and tax evasion are now even more important. Web scraping provides an avenue to find, collate, and organize data without relying on information leaks.

We’re pleased to announce that Splash 2.0 is officially live after many months of hard work.

Heads up, Kimono Labs users!
Today, we are releasing a tool to help you migrate your Kimono projects to Portia.

Welcome to the February Edition of Scrapy Tips from the Pros. Each month we’ll release a few tips and hacks that we’ve developed to help make your Scrapy workflow go more smoothly.

Imagine your business depended heavily on a third party tool and one day that company decided to shut down its service with only 2 weeks notice. That, unfortunately, is what happened to users of Kimono Labs yesterday.

Today we released the latest version of Portia bringing with it the ability to crawl pages that require JavaScript. To celebrate this release we are making Splash available as a free trial to all Portia users so you can try it out with your projects.

When scraping content from the web, you often crawl websites which you have no prior knowledge of. Link analysis algorithms are incredibly useful in these scenarios to guide the crawler to relevant pages.

33 Zytans from 15 countries will be meeting (most of them, for the first time) in Bilbao, for what is going to be our largest get-together event so far.

It's not uncommon to need to crawl a large number of unfamiliar websites when gathering content. Page ranking algorithms are incredibly useful in these scenarios as it can be tricky to determine which pages are relevant to the content you're looking for.

Imagine that you have a lot of samples for a certain kind of data in JSON format. Maybe you want to have a better feel of it, know which fields appear in all records, which appear only in some and what are their types. In other words, you want to know the schema for the data that you have.

In the context of web scraping, XPath is a nice tool to have in your belt, as it allows you to write specifications of document locations more flexibly than CSS selectors.

One of the things that takes more time when building a spider is reviewing the scraped data and making sure it conforms to the requirements and expectations of your client or team.

We have released an lxml-based version of this code as an open-source library called extruct. The Source code is on Github, and the package is available on PyPI. Enjoy!