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Scala for Data Science

You're reading from   Scala for Data Science Leverage the power of Scala with different tools to build scalable, robust data science applications

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Product type Paperback
Published in Jan 2016
Publisher
ISBN-13 9781785281372
Length 416 pages
Edition 1st Edition
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Author (1):
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Pascal Bugnion Pascal Bugnion
Author Profile Icon Pascal Bugnion
Pascal Bugnion
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Toc

Table of Contents (17) Chapters Close

Preface 1. Scala and Data Science FREE CHAPTER 2. Manipulating Data with Breeze 3. Plotting with breeze-viz 4. Parallel Collections and Futures 5. Scala and SQL through JDBC 6. Slick – A Functional Interface for SQL 7. Web APIs 8. Scala and MongoDB 9. Concurrency with Akka 10. Distributed Batch Processing with Spark 11. Spark SQL and DataFrames 12. Distributed Machine Learning with MLlib 13. Web APIs with Play 14. Visualization with D3 and the Play Framework A. Pattern Matching and Extractors Index

Querying external APIs and consuming JSON

So far, we have learnt how to provide the user with a dummy JSON array of repositories in response to a request to /api/repos/:username. In this section, we will replace the dummy data with the user's actual repositories, dowloaded from GitHub.

In Chapter 7, Web APIs, we learned how to query the GitHub API using Scala's Source.fromURL method and scalaj-http. It should come as no surprise that the Play framework implements its own library for interacting with external web services.

Let's edit the Api controller to fetch information about a user's repositories from GitHub, rather than using dummy data. When called with a username as argument, the controller will:

  1. Send a GET request to the GitHub API for that user's repositories.
  2. Interpret the response, converting the body from a JSON object to a List[Repo].
  3. Convert from the List[Repo] to a JSON array, forming the response.

We start by giving the full code listing before explaining...

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