Add electoral campaign donations datasets

[cuducos]

What is the purpose of this Pull Request? Add the electoral campaign donation datasets to the toolbox downloader.

What was done to achieve this purpose? Outside the repo I uploaded the .xz files to S3 and here I added the files to the LATEST constant.

How to test if it really works?

from serenata_toolbox.datasets import fetch, fetch_latest_backup
files = (
   '2017-11-30-donations-candidates.xz',
    '2017-11-30-donations-committees.xz',
   '2017-11-30-donations-parties.xz'
)
for filename in files:
    fetch(filename, 'data/')

And check if the filer were downloaded successfully ; )

Who can help reviewing it? @anaschwendler

[cuducos]

BTW:

FIx #165

And maybe it's useful to test the fetch_latest_backup function too:

from serenata_toolbox.datasets import fetch_latest_backup
fetch_latest_backup('data/')

That way we test if these new datasets are being downloaded by default in a default Serenata installation ; )

[anaschwendler]

:tada:

What I did to test this PR:

1. Cloned the project:

   $ git clone git@github.com:datasciencebr/serenata-toolbox.git

2. Change to its folder:

   $ cd serenata-toolbox

3. Change to @cuducos’ branch:

   $ git fetch origin
   $ git checkout -b cuducos-donation-data origin/cuducos-donation-data
   $ git merge master

4. Run the python fetch script:

   >>> from serenata_toolbox.datasets import fetch, fetch_latest_backup
   >>> files = (
   '2017-11-30-donations-candidates.xz',
   '2017-11-30-donations-committees.xz',
   '2017-11-30-donations-parties.xz'
   )
   >>> for filename in files:
   fetch(filename, 'data/')

The result:

Downloading 2017-11-30-donations-candidates.xz: 100%|█| 239M/239M [02:34<00:00, 1.54Mb/s]
Downloading 2017-11-30-donations-committees.xz: 100%|█████████████████████████████████████████████████| 5.64M/5.64M [00:03<00:00, 1.69Mb/s]
Downloading 2017-11-30-donations-parties.xz: 100%|████████████████████████████████████████████████████| 6.47M/6.47M [00:03<00:00, 1.72Mb/s]

And for fetch_latest_backup script:

>>> from serenata_toolbox.datasets import fetch_latest_backup
>>> fetch_latest_backup('data/')

Good! 🎉