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Category: open-source

Do Androids Dream of Electric Sheep?

It got very easy to do Machine Learning: you install a ML library like scikit-learn or xgboost, choose an estimator, feed it some training data, and get a model which can be used for predictions.

Incremental Crawls with Scrapy and DeltaFetch

Welcome to Scrapy Tips from the Pros! In this monthly column, we share a few tricks and hacks to help speed up your web scraping activities. As the lead Scrapy maintainers, we’ve run into every obstacle you can imagine so don’t worry, you’re in great hands. Feel free to reach out to us on Twitter or Facebook with any suggestions for future topics.

Improving Access to Peruvian Congress Bills with Scrapy

Many governments worldwide have laws enforcing them to publish their expenses, contracts, decisions, and so forth, on the web. This is so the general public can monitor what their representatives are doing on their behalf.

Portia: The Open Source Alternative to Kimono Labs

Attention Kimono users: we've created an exporter so you can easily convert your projects from Kimono to Portia!

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.

And it’s one of the many reasons why we love open source so much.

...

Skinfer: A Tool for Inferring JSON Schemas

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.

Scrapinghub Crawls the Deep Web

"The easiest way to think about Memex is: How can I make the unseen seen?"

Optimizing Memory Usage of Scikit-Learn Models Using Succinct Tries

We use the scikit-learn library for various machine-learning tasks at Scrapinghub. For example, for text classification we'd typically build a statistical model using sklearn's Pipeline, FeatureUnion, some classifier (e.g. LinearSVC) + feature extraction and preprocessing classes. The model is usually trained on a developers machine, then serialized (using pickle/joblib) and uploaded to a server...

Autoscraping casts a wider net

We have recently started letting more users into the private beta for our Autoscraping service. We're receiving a lot of applications following the shutdown of Needlebase and we're increasing our capacity to accommodate these users.

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Here we blog about all things related to web scraping and web data.

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