transferegovr

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An R interface to the open data APIs of TransfereGov, the Brazilian federal government’s platform for transfers to states, municipalities and civil society.

The platform publishes three APIs, covering 48 tables in all:

Module Covers Tables
transferenciasespeciais Special transfers, created by Constitutional Amendment 105/2019 for individual parliamentary amendments 14
fundoafundo Fund-to-fund transfers, from federal funds directly to state, district and municipal funds 21
ted Decentralized credit between federal bodies (termo de execução descentralizada) 13

All three are PostgREST services, so this package exposes their filtering, column selection and ordering directly, rather than wrapping each table in a function of its own.

Installation

# install.packages("pak")
pak::pak("StrategicProjects/transferegovr")

Getting started

library(transferegovr)

tg_modules()
tg_tables("ted")
tg_fields("ted", "plano_acao")

tg_get() retrieves rows. Name each filter after the column it applies to:

tg_get("ted", "plano_acao", aa_ano_plano_acao = 2024)

A bare value means “equals”, a bare vector means “is one of”, and the operators from tg_operators() cover the rest:

tg_get(
  "ted", "plano_acao",
  aa_ano_plano_acao = gte(2024),
  sigla_unidade_descentralizada = c("CNPq", "CAPES"),
  tx_objeto_plano_acao = ilike("*pesquisa*"),
  .select = c("id_plano_acao", "vl_total_plano_acao", "dt_inicio_vigencia"),
  .order = "vl_total_plano_acao.desc",
  .limit = 20
)

Several conditions on one column go in a list, and the API combines them with AND:

tg_get(
  "fundoafundo", "plano_acao",
  data_inicio_vigencia_plano_acao = list(gte("2024-01-01"), lt("2025-01-01"))
)

Size first, download second

The service returns at most 1000 rows per request, and these tables are not small — the largest holds over a million rows, which is more than a thousand requests. Ask before you fetch:

tg_count("fundoafundo", "gestao_financeira_lancamentos")
#> [1] 1115444

.limit counts rows, not pages. Anything above 1000 is collected page by page, in an explicit order so that the pages cannot overlap or skip rows, and the total collected is checked against what the API reported:

plans <- tg_get("ted", "plano_acao", .limit = Inf)

tg_metadata(plans)$total_rows
tg_metadata(plans)$pages

Types

Columns are typed from the API’s own schema rather than guessed, so a column that happens to be entirely null on one page does not change class on the next:

plans <- tg_get("ted", "plano_acao", .limit = 5)

class(plans$dt_inicio_vigencia)
#> [1] "Date"
class(plans$in_forma_execucao_direta)
#> [1] "logical"

Caching

Responses are cached for an hour in the session’s temporary directory, so nothing is written outside the session unless you ask for it. To keep them between sessions:

tg_cache_dir(tools::R_user_dir("transferegovr", "cache"))

or set TRANSFEREGOVR_CACHE_DIR in your .Renviron. tg_cache_clear() empties it.

How it works

Architecture of transferegovr: the public verbs pass through filter and schema validation, the pagination loop, and the HTTP client and its cache, reach the three PostgREST services, and return through the parser as a typed tibble.

Two things in that picture are worth stating plainly, because they are where a naive client of these APIs loses data:

Column names are in Portuguese

Table names, column names and categorical values belong to the API and are left as the government publishes them. The package’s own functions, arguments and documentation are in English, with Portuguese aliases (tg_obter(), tg_contar(), tg_tabelas(), tg_campos()) for the exported verbs.

Official documentation