--- title: "Introduction to obrasgovr" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{Introduction to obrasgovr} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- ```{r, include = FALSE} knitr::opts_chunk$set(collapse = TRUE, comment = "#>") ``` `obrasgovr` provides an R interface to the Brazilian federal government's ObrasGov Open Data API. It validates filters locally, handles HTTP failures, collects paginated results, and returns tibbles with predictable types. This vignette walks through the usual sequence: discover a resource, inspect its filters, make a small query, inspect the result, and retrieve related data. ```{r setup} library(obrasgovr) ``` ## 1. Discover available resources Start with `list_resources()`. This function is entirely local and does not contact the API. ```{r resources} list_resources() ``` The `function_name` column identifies the function used to query each resource. All main package functions use English names. The API's filter names, response fields, and categorical values remain in Portuguese because they are part of the official ObrasGov contract. ## 2. Inspect filters before querying Use `list_filters()` to see the accepted filter names and their expected types. For example, projects can be filtered by state, status, registration year, dates, and several other attributes. ```{r project-filters} project_filters <- list_filters("projects") project_filters[c("filter", "type")] ``` Allowed categorical values are stored in the `allowed_values` list-column. The following code retrieves the values accepted by the `situacao` filter: ```{r filter-values} project_filters$allowed_values[ project_filters$filter == "situacao" ][[1]] ``` Dates can be supplied as `Date` values. The package serializes them using the ISO `YYYY-MM-DD` format expected by the API. ## 3. Retrieve a small first page Begin with a narrow query and a small `page_size`. Network calls are not run when this vignette is built, so installation and CRAN checks do not depend on the external service. ```{r first-query, eval = FALSE} projects_pe <- get_projects( uf_principal = "PE", situacao = "Em execução", dt_cadastro = as.Date("2024-01-01"), page_size = 25 ) projects_pe ``` The returned object is a tibble. Date-like fields such as `dt_cadastro` are converted to `Date` when every non-missing value uses the ISO date format. Nested one-to-many relationships are preserved as list-columns. ## 4. Inspect pagination metadata Every paginated result carries retrieval metadata. Check it before deciding whether more pages are required. ```{r inspect-metadata, eval = FALSE} metadata <- result_metadata(projects_pe) metadata$total_items metadata$total_pages metadata$pages_retrieved metadata$retrieved_at ``` The initial request retrieves only one page. To collect more pages safely, use `all_pages = TRUE` together with a finite `page_limit`. See `vignette("pagination-and-nested-data")` for details. ## 5. Retrieve related resources ObrasGov resources can be related through `id_projeto_investimento`. After selecting a project, use its identifier to retrieve physical execution, contracts, commitments, status history, and feasibility studies. ```{r related-resources, eval = FALSE} project_id <- projects_pe$id_projeto_investimento[[1]] physical_execution <- get_physical_execution( id_projeto_investimento = project_id ) contracts <- get_contracts( id_projeto_investimento = project_id ) commitments <- get_commitments( id_projeto_investimento = project_id ) status_history <- get_status_history( id_projeto_investimento = project_id ) ``` Filtering related endpoints by project identifier avoids downloading large tables and makes the relationship explicit in the analysis code. ## 6. Record the source update timestamp The API reports the time of its most recent data load. Store this value with the query results to identify the temporal version of the source. ```{r updated, eval = FALSE} source_updated_at <- get_last_update() source_updated_at ``` ## Portuguese aliases The original Portuguese function names remain available as compatibility aliases. Paginated aliases retain their original pagination argument names. ```{r portuguese-aliases, eval = FALSE} projetos_pe <- obter_projetos( uf_principal = "PE", tamanho_da_pagina = 25, todas_paginas = FALSE ) ``` New code should use `get_projects()`, `page_size`, and `all_pages`. ## Client configuration The API does not require authentication. Three options customize transport without changing every function call: ```{r options, eval = FALSE} options( obrasgovr.base_url = "https://api-publica.obrasgov.gestao.gov.br/obras", obrasgovr.timeout = 30, obrasgovr.user_agent = "my-project/1.0 (contact@example.org)" ) ``` By default, the client requests HTTP/2 over TLS, retries transient failures, and throttles requests to an average of 60 per minute. Throttling uses a token bucket, so a burst of up to 60 requests may go out before the rate settles. ## Next steps - Read `vignette("pagination-and-nested-data")` to collect multiple pages and normalize list-columns. - Read `vignette("end-to-end-workflow")` to build a reproducible dataset from multiple ObrasGov resources.