A Python application reading receipts from the Quota for Exercising Parliamentary Activity (aka CEAP) from the Brazilian Chamber of Deputies and outputs, for each of the receipts, a probability of corruption and a list of reasons why it was considered this way.
$ docker run --rm -v /tmp/serenata-data:/tmp/serenata-data datasciencebr/rosie run <module_name>
Then check your /tmp/serenata-data/
directory in you host machine for irregularities.xz
.
For testing
$ docker run --rm -v /tmp/serenata-data:/tmp/serenata-data datasciencebr/rosie test
$ conda update conda
$ conda create --name serenata_rosie python=3
$ source activate serenata_rosie
$ ./setup
To run Rosie, you need to select a module to be called.
For example, if you want to run chamber_of_deputies
module, you should run this command:
$ python rosie.py run chamber_of_deputies
A /tmp/serenata-data/irregularities.xz
file will be created. It's a compacted CSV with all the irregularities Rosie is able to find.
Also a target directory (where files are saved) can de passed — for example:
$ python rosie.py run chamber_of_deputies /my/serenata/directory/
You can either run all tests with:
$ python rosie.py test
Or test each submodule a time by passing a name:
$ python rosie.py test core
$ python rosie.py test chamber_of_deputies
$ python rosie.py test federal_senate