Metadata-Version: 2.0
Name: dadosgovbr
Version: 0.1.3
Summary: A library to programatically explore the Brazillian open data program
Home-page: https://github.com/georgeyk/dadosgovbr
Author: George Y. Kussumoto
Author-email: contato@georgeyk.com.br
License: MIT
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Information Technology
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Topic :: Internet :: WWW/HTTP :: Dynamic Content
Requires-Dist: requests

# dadosgovbr

[![PyPI version](https://badge.fury.io/py/dadosgovbr.svg)](http://badge.fury.io/py/dadosgovbr)
[![Build Status](https://travis-ci.org/georgeyk/dadosgovbr.svg?branch=master)](https://travis-ci.org/georgeyk/dadosgovbr)
[![Coverage Status](https://coveralls.io/repos/georgeyk/dadosgovbr/badge.svg?branch=master)](https://coveralls.io/r/georgeyk/dadosgovbr?branch=master)


---

A library to programatically explore the Brazilian open data program.

More details at [dados.gov.br][1]

## Motivation

Basically, I did this library because their web interface was broken for me, specially the search feature.

Also, I feel more confortable exploring the data using a python shell with all the libraries available to handle json,
csv and so on.


## Install

Available in PyPi, just:

```shell
$ pip install dadosgovbr
```


## Examples

The library just provides an "object-wrapping" for the API results, so we can access every attribute as we
inspect any regular python object:

```python

>>> from dadosgovbr import DadosGovBR
>>> api = DadosGovBR()
>>> api.get_tag('VT')
Tag(vocabulary_id=None, packages=<generator object model_list_factory at 0x7f7dac17af00>, display_name=u'VT',
id=u'41a7ab78-3cec-44a3-b2c3-ca15ad55a50f', name=u'VT')
```

Check the tests directory for more examples, like [this one][2].


## NOTE

This is very *work-in-progress* lib.
Contributions are super-welcome. =)

## Development

1. fork the project
2. create virtualenv (optional)
3. pip install -r requirements-devel.txt
4. pre-commit install
5. tox


[1]: http://dados.gov.br/dataset
[2]: example.py


## History

## 0.1.3

* First tag release
* Bug fixes

## 0.1.2

* Improve test coverage
* Minor fixes

## 0.1.1

* Fix import errors

## 0.1.0

* Initial release


