Managing dependencies for your Java applications is difficult, unless you have Maven
! Maven is an Apache build manager for Java projects. In this post, we will use a Maven plugin (Maven Assembly
) to pull all the unirest-java dependencies in one bundle/jar file.
Let’s get started (the steps below assume you already have Java and Git
Update: If you’re building for Android, please refer to this post
1. Download/Install Maven
To check if you already have Maven in your machine, run
in your Terminal. OS X prior to Maverick already comes with Maven. If…
Here’s a list of resources on how to make REST calls in different languages. (We also have this list of 40+ tutorials on how to create an API in different languages
If you dabble with one or more of these languages in your different projects, we highly recommend that you check out Unirest.io
, an open source lightweight HTTP client library. It’s goal is to provide a consistent way for developers to make HTTP calls across different languages (node.js
If you have suggested additions to…
Photo credit: Parse
is a backend-as-a-service (BAAS) platform that lets you focus on building your applications without worrying about server and infrastructure maintenance and complexities. If you haven’t heard or tried Parse before, I encourage you to try their Quickstart here
to get an idea of how the BAAS paradigm works.
This post shows an example of a Mashape API integrated with Parse through Parse Modules. Parse Modules are libraries that Parse developers import into their app to use certain functionality offered by 3rd-party APIs. Once your API is turned into a Parse Module, it will be easier for…
This post is brought to you in part by Geeklist
, a vibrant platform for geeks to discover, connect and share the great work they have done. Check out the upcoming ‘Hack for Good’
global mobile hackathon this coming June 28th – 30th.
We love hackathons! We love seeing what developers can do with APIs. Just look at this
, and this
! However with hackathons running almost every day, it’s easy to run out of app ideas. What if your app was already created in some hackathon that you…
Note: Check out our latest API collections page for the list of updated APIs.
There has been a lot of buzz around Face Recognition since Google Glass
was announced. We believe that face recognition will open up a ton of possibilities in how we interact not just with each other, but with objects as well – whether it’s with Glass or not.
To help you in your journey of exploring face recognition, we have below a long list of face detection and recognition APIs that you can use for your applications. Enjoy!
After the successful launch of Unirest
, an open source lightweight http client library, we received a lot of requests for a C# .NET port on Windows Desktop and Windows 8. Even before we got to work, we’ve received contributions from the open source community who ported Unirest to .NET.
This tutorial will show you how to use the Windows 8 (RT) port of Unirest
in your application (We will follow this up with the Windows Desktop port
in a later post, but it will follow pretty much the same steps). Let’s get started!
NOTE: We will be updating this…
After we posted the list of NLP
, Sentiment Analysis
, and Machine Learning
APIs a while ago, we noticed that some API descriptions require a little bit of digging into, to fully appreciate what these APIs can do. Here’s an example:
Text analysis API including wordnet synsets,relation extraction,named entity recognition and classification,lemmatization,part of speech tagging,tokenization, and semantic role labeling.
If you’re not familiar with these words, you could totally miss the features that this API
is capable of.
To help with that, we have listed below an explanation to some of these words in the NLP/Machine Learning context; as…
This post is intended to help data scientists and engineers who, in some capacity, have implemented routines/algorithms/data that does a specialized function (e.g. machine learning) using a dynamically typed language, such as Python. The goal is to web-enable these routines/algorithms using an application programming interface (API).
Exposing these functions/data as an API allows for:
Easier, faster, and consistent sharing of functionality/data that could further progress the research. A good example of this is the Materials Project from the Lawrence Berkeley National Laboratory. They deemed it necessary for the scientific community to have access to their data, hence exposing it as
Image credit: https://flic.kr/p/2nmAe
Into APIs now, Yoda