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📦 pip module containing code shared across Serenata de Amor's projects
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Serenata de Amor Toolbox

pip installable package to support Serenata de Amor and Rosie development.

Serenata_toolbox is compatible with Python 3.6+


$ pip install -U serenata-toolbox

If you are a regular user you are ready to get started after pip install.

If you are a core developer willing to upload datasets to the cloud you need to configure AMAZON_ACCESS_KEY and AMAZON_SECRET_KEY environment variables before running the toolbox.


We have plenty of them ready for you to download from our servers. And this toolbox helps you get them. Here some examples:

Example 1: Using the command line wrapper

# without any arguments will download our pre-processed datasets and store into data/ folder
$ serenata-toolbox

# will download these specific datasets and store into /tmp/serenata-data folder
$ serenata-toolbox /tmp/serenata-data --module federal_senate chamber_of_deputies

# you can specify a dataset and a year
$ serenata-toolbox --module chamber_of_deputies --year 2009

# or specify all options simultaneously
$ serenata-toolbox /tmp/serenata-data --module federal_senate --year 2017

# getting help
$ serenata-toolbox --help

Example 2: How do I download the datasets?

Another option is creating your own Python script:

from serenata_toolbox.datasets import Datasets
datasets = Datasets('data/')

# now lets see what are the latest datasets available
for dataset in datasets.downloader.LATEST:
    print(dataset)  # and you'll see a long list of datasets!

# and let's download one of them'2018-01-05-reimbursements.xz')  # yay, you've just downloaded this dataset to data/

# you can also get the most recent version of all datasets:
latest = list(datasets.downloader.LATEST)

Example 3: Using shortcuts

If the last example doesn't look that simple, there are some fancy shortcuts available:

from serenata_toolbox.datasets import fetch, fetch_latest_backup
fetch('2018-01-05-reimbursements.xz', 'data/')
fetch_latest_backup( 'data/')  # yep, we've just did exactly the same thing

Example 4: Generating datasets

If you ever wonder how did we generated these datasets, this toolbox can help you too (at least with the more used ones — the other ones are generated in our main repo):

from serenata_toolbox.federal_senate.dataset import Dataset as SenateDataset
from serenata_toolbox.chamber_of_deputies.reimbursements import Reimbursements as ChamberDataset

chamber = ChamberDataset('2018', 'data/')

senate = SenateDataset('data/')

Documentation (WIP)

The full documentation is still a work in progress. If you wanna give us a hand you will need Sphinx:

$ cd docs
$ make clean;make rst;rm source/modules.rst;make html


Firstly, you should create a development environment with Python's venv module to isolate your development. Then clone the repository and build the package by running:

$ git clone
$ cd serenata-toolbox
$ python develop

Always add tests to your contribution — if you want to test it locally before opening the PR:

$ pip install pytest pytest-cov
$ pytest

When the tests are passing, also check for coverage of the modules you edited or added — if you want to check it before opening the PR:

$ pytest
$ open htmlcov/index.html

Follow PEP8 and best practices implemented by Landscape in the veryhigh strictness level — if you want to check them locally before opening the PR:

$ pip install prospector
$ prospector -s veryhigh serenata_toolbox

If this report includes issues related to import section of your files, isort can help you:

$ pip install isort
$ isort **/*.py --diff

Always suggest a version bump. We use Semantic Versioning – or in Elm community words:

  • MICRO: the API is the same, no risk of breaking code
  • MINOR: values have been added, existing values are unchanged
  • MAJOR: existing values have been changed or removed

This is really important because every new code merged to master triggers the CI and then the CI triggers a new release to PyPI. The attemp to roll out a new version of the toolbox will fail without a version bump. So we do encorouge to add a version bump even if all you have changed is the README.rst — this is the way to keep the README.rst updated in PyPI.

If you are not changing the API or README.rst in any sense and if you really do not want a version bump, you need to add [skip ci] to you commit message.

And finally take The Zen of Python into account:

$ python -m this
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