This is Rosie's core object: it implements a generic pipeline to collect data, clean and normalize it. After analyzing the data it outputs a

Traveled Speeds classifier. Dataset ------- applicant_id : category column A personal identifier code for every person makin

Context manager to download, read data from a given year and cleanup

Election Expenses classifier. Check a `legal_entity` field for the presency of the political candidacy category in the Brazilian Federal

Invalid CNPJ/CPF classifier. Validate a `recipient_id` field by calculating its expected check digit and verifying the authenticity of t

Irregular Companies classifier. Check for the official state of the company in the Brazilian Federal Revenue and reports for rows with c

Meal Price Outlier classifier. Dataset ------- applicant_id : string column A personal identifier code for every person maki

Monthly Subquota Limit classifier. Dataset ------- issue_date : datetime column Date when the expense was made. month :

Abstraction to a list of Receipts read from the datasets

Twitter target. Maintains the logic for posting suspicious reimbursements in a Twitter account.

Cached the paginator count (for performance)