I'd like to share a project that I am developing that it may be useful for anyone who wants to create datasets from mobile location networks. Specifically, I developed a wrapper in Python for accessing the Foursquare API called PyFoursquare
For anyone who doesn't know what is Foursquare, it is a popular mobile social-location network with more 10.000.000 of users around the world. The idea is that you can share your current location with your friends and as result discover new places, find where your friends are and even check some tips and recommendations about a place and what to do when you arrive there. It is an amazing project with lots of data available for anyone who wants to develop new apps for connect or mine (data mining) its data!
|Foursquare Mobile Application|
This Python API is one of the results of my master degree project where I proposed a new architecture for mobile recommenders that fetches reviews from social networks to improve the explanation and the quality of the given recommendations. I used this library to collect tips (text reviews) from Foursquare from places at my neighborhood Recife, Brazil. This API was a little messy, so I decided to clean it up, organize and documment it for publish for the open-source community.
One of advantages of this API is that you can handle each entity from the Foursquare data as Model object. So instead of handling with json dictionaries, I encapsulate the results in the respective models (Venue, Tips, User, etc.) and access its attributes as common object in Python!
I inspired myself at the work of Joshua at Tweepy, which is a Python library for Twitter. In this version released 0.0.1 I only implemented some API's such as search/venues, venue_details and venue_tips. In future releases I pretend to add more models and support for more API methods available at Foursquare.
How can you use it at your project ?
It is simple! Just install it by downloading at the Github's home project, extract the source from the tar.gz and at the directory of the project run the command below:
$ python setup.py install
or the easier way is to install by the command easy_install:
$ easy_install pyfoursquare
After that, you can simple test by running the command below at your Python Shell
>>> import pyfoursquare
Now let's see how you can get started with the PyFoursquare:
First you need to create an application at Foursquare. The link is this. There you can also get further information about the API, another libraries and several applications using the Foursquarw API's.
|The Foursquare Developer's Settings|
After creating your application, you must get the client_id and your client_secret. Those keys will be important to connect the app to the users' accounts. Foursquare uses the secure authentication based on OAuth2. In PyFoursquareAPI, you won't need to handle with all steps provided by OAuth2. It already encapsulates all the steps and handshakes between your app and Foursquare servers. \m/
Below the code you must write for authenticate an user to connect to your app:
After the user authorized, you now can instantiate the PyFoursquare API. It will give you access to the Foursquare API methods. I implemented several methods, but feel free to add new ones! Don't forget to submit the final results as pull requests at the project's repository at Github.
In this example I fetched a venue by giving as input the latitude and longitude and querying for the place with the name 'Burburinho'. Burburinho is a popular bar nearby where I work!
Now you can access the result and access the Venue as a Python Object. All elements of the Venue are represented as attributes of the object Venue at PyFoursquare. The goal is to make easier the life of the developer when he access the Foursquare API by parsing all the JSON (the result) and placing in the correct model for him.
I expect you enjoyed this API. Feel free to use it at your applications or research! I'd like to thank the Foursquare team for expose their data by providing those API's! For data mining researchers instered in mobile location data, it is a mine of gold!
Further information about PyFoursquare, you can find here.
Feel free to give sugestions, improvements and comments,