A bit of web scraping with Jsoup and REST API calls with groovy-wsclient helped me build my latest demo with Glide / Gaelyk on App Engine, but now, it’s time to look a bit deeper into the analysis of the White House speeches: I wanted to have a feel of how positive and negative sentences flow together in speeches. Looking at the rhetoric of those texts, you’d find some flows of generally neutral introduction, then posing the problem with some negativity connotation, then the climax trying to unfold the problems with positive solutions. Read more...

After my Twitter sentiment article, those past couple of days, I’ve been playing again with the Cloud Natural Language API. This time, I wanted to make a little demo analyzing the text of speeches and remarks published by the press office of the White House. It’s interesting to see how speeches alternate negative and positive sequences, to reinforce the argument being exposed. As usual, for my cloud demos, my weapons of choice for rapid development are Apache Groovy, with Glide & Gaelyk on Google App Engine! Read more...

What’s the mood on Twitter today? Looking at my little twitter demo from a few weeks ago (using Glide & Gaelyk on Google App Engine), I thought I could enrich the visualization with some sentiment analysis to give more color to those tweets. Fortunately, there’s a new API in Google-town, the Cloud Natural Language API (some more info in the announcement and a great post showing textual analysis of Harry Potter and New York Times)! Read more...

Back in 2009, I created Gaelyk, a lightweight toolkit for developing Google App Engineapps using the Apache Groovyprogramming language. I even had the chance to speak at Google I/O 2009about it! Good times, good times… Vladimír Oranýlater joined me in maintaining and evolving Gaelyk, and Kunal Dabircreated the fun Glide project, which is a thin wrapper around Gaelyk to further streamline the development of small to mid-sized apps for Google App Engine. Read more...

Github and Google recently announced and released the Github archive to BigQuery, liberating a huge dataset of source code in multiple programming languages, and making it easier to query it and discover some insights. Github explained that the dataset comprises over 3 terabytes of data, for 2.8 million repositories, 145 million commits over 2 billion file paths! The Google Cloud Platform blog gave some additional pointers to give hints about what’s possible to do with the querying capabilities of BigQuery. Read more...

As I recently joined Google’s developer advocacy team for Google Cloud Platform, I thought I could have a little bit of fun with combining my passion for Apache Groovy with some cool cloudy stuff from Google! Incidentally, Paolo Di Tommaso tweeted about his own experiments with using Groovy with Apache Spark, and shared his code on Github: I thought that would be a nice fun first little project to try to use Groovy to run a Spark job on Google Cloud Dataproc! Read more...

The cat is out the bag: I’m joining Google on June 6th, as a Developer Advocate for the Google Cloud Platform team! My Groovy friends will likely remember when I launched Gaelyk, a lightweight toolkit for developing Groovy apps on Google App Engine? Since then, I’ve always been a big fan of the Google Cloud Platform (although it wasn’t called that way then) and followed the latest developments of the whole platform. Read more...

At our disposal, we have so many ways to interact with an API: from a mobile on iOS or Android, from a web application, or from other services or microservices. And all of them have different needs: one wants only a shallow overview of the data, while the other desires a detailed view of a certain resource and all its sub-resources. It’s becoming difficult to design an API that caters to the needs of those varied consumers. Read more...

I had the pleasure of writing an article for Nordic APIs on Web API definition languages. If you’re into the world of Web APIs, you’ve probably heard of formats like Swagger, RAML or API Blueprint. They allow developers to define the contract of the API, with its endpoints, its resources, its representations, allowed methods, the kind of payloads it understands, the status codes returned, and more. With the contract of your Web API, you can generate code for your backend implementation or client kits, documentation for publishing the details of your API for your API consumers. Read more...

The most common API definition languages we spot in the wild are Swagger / OpenAPI Spec, RAML and API Blueprint. All three let you define your endpoints, your resources, your query or path parameters, your headers, status codes, security schemes, and more. In a nutshell, these definition languages define the structure of your API, and allow you to describe many elements. As standards in the API industry evolve, however, their purpose and design are under continuous scrutiny. Read more...