The DataGator project aims to realize the crowd-source data analytics platform as envisioned by the Frederick S. Pardee Center for International Futures (abbr. Pardee) at the University of Denver.
Once evolved to its full-fledged form, DataGator will serve as a collaboration tool for sharing, cleansing, and augmenting data sets among an online research community, which gears up domain-specific studies with data science methodologies including exploration, visualization, and quantitative analytics.
This repository collects public resources including specification documents, sample data, and code snippets for prospective contributors of the DataGator project.
The HTTP client libraries of DataGator (aka. clients) collects various language bindings of DataGator's backend services, currently available in the following programming languages,
- python:
- Pythonic binding of RESTful API
The public data set of DataGator (aka. data) collects examples of data items both in various raw formats and in consolidated JSON format.
- raw:
- data items in various original formats
- json:
- data items in consolidated JSON format
The public documentation of DataGator (aka. docs) collects specifications on data model, data exchange format, programming interfaces, etc.
The public test suite of DataGator (aka. tests) is designed for (i) regression test of DataGator's backend services through the RESTful API, and (ii) coverage test of DataGator's HTTP client libraries.
Basic usage is simply,
$ python -m tests -vOptional settings can be passed via the following environment variables,
| Variable | Description |
DATAGATOR_API_HOST |
domain name or IP address of DataGator's backend
portal, defaults to www.data-gator.com |
DATAGATOR_CACHE_BACKEND |
implementation of cache manager backend, defaults to
datagator.api.client._cache.leveldb.LevelDBCache |
DATAGATOR_CREDENTIALS |
access key in the form of <repo>:<secret> |
DEBUG |
DEBUG=1 turns on debugging mode |