R Observatory: Metrics for BigDataPE version 0.3.0

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

BigDataPE

0.3.0Package record

Secure and Intuitive Access to 'BigDataPE' 'API' Datasets

0packages depend

6.4Kdownloads / year

–test coverage

13/13flavors OK

Overview

About

Maintained by André LeiteCRAN page ↗GitHub ↗Website ↗Issues ↗

Designed to simplify the process of retrieving datasets from the 'Big Data PE' platform using secure token-based authentication. It provides functions for securely storing, retrieving, and managing tokens associated with specific datasets, as well as fetching and processing data. The data-retrieval engine is provided by the generic 'apifetch' package, which 'BigDataPE' configures for the Big Data PE service.

Changes in 0.3.0

Breaking changes

bdpe_fetch_chunks() now requests chunk_size = 50000 records per chunk by default (was 500000), matching 'apifetch'. Very large chunks were prone to timeouts and high memory use; pass chunk_size = 500000 to restore the old behaviour.
bdpe_fetch_data() now drops the API's Mensagem status column, as bdpe_fetch_chunks() already did, so both functions return the same columns.

Other changes

Now requires 'apifetch' >= 0.2.0, which brings its bug fixes to every bdpe_* function: bdpe_fetch_chunks() accepts chunk_size = Inf and never returns more than total_limit rows; the query argument drops NULL/NA values, repeats multi-valued parameters and works with an endpoint that already has a query string; dataset names with accents map to the same plain-ASCII token name on every platform (macOS used to produce names such as BigDataPE_Sa'ude); and HTTP 401/403, empty and non-JSON responses give clearer messages.

Show all changes in 0.3.0Hide the rest of the changes in 0.3.0

bdpe_store_token() gains overwrite = FALSE, to replace an expired token. Previously the "already defined" warning suggested overwrite = TRUE, which bdpe_store_token() did not accept.
Added a test suite (with mocked HTTP) for the Big Data PE service conventions.
Added authors' ORCID iDs and a BugReports field.

From NEWS.md in the release

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("BigDataPE", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("StrategicProjects/BigDataPE")

Development version from StrategicProjects/BigDataPE. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-bigdatape

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-BigDataPE

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-BigDataPE

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 1.6 min · r-oldrel-macos-x86_64

Status changes

OK13 OK2026-08-05
NOTE12 OK, 1 NOTE2026-08-01
OK14 OK2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 0.3.0

READMEYes · 627 wordsVignettesYes · 1 · staticNEWSYes · 100% structured · mentions 0.3.0Citation fileNoWebsiteYes · pkgdown

Help pages: 7
Examples that run: 71%5 run in a plain check · 2 never run
Exported functions with examples: 100%
Documented parameters: 100%
Return-value docs: 100%
Help pages citing references: 0%

Vignettes (1)

Exploring Dengue Data with BigDataPE HTML

How these are measured

Downloads

6.4K

CRAN downloads in the past year

Rank #7,565 · ~18/day · ~533/mo

Releases R versions

Daily download trend is not available in this view yet.

44630 days

1.2K90 days

6.4K1 year

Compare downloads with other packages →

Also on120 r2u53 autocran

How downloads are counted

Repository

strategicprojects/bigdatape ↗Organization: StrategicProjects

0Stars

0Forks

0Open issues

0Open PRs

1Releases

40Commits

2Commit identities

40 commits · Last activity 2026-10-01 · Default branch at 0.3.0.9000, ahead of CRAN 0.3.0 (checked 2026-10-25)

Responsiveness

How these are sampled

PRs merged (all time): 100%
Median days to close, 50 most recently updated closed issues: not measured
Median days to close, 50 most recently updated closed PRs: 19

Releases over time

2026-07-07 · 02026-10-01 · 1

How these are measured

PracticesBeta

9 development-tooling and community-health practices detected across 5 families in the upstream repository

Checks run against github.com/strategicprojects/bigdatape on 2026-10-25.

Continuous integration (2)

GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux, macOS and Windows

Docs source (4)

README.Rmdpkgdown

GitHub Pages site last deployed 2026-10-01 · The repository has a site deploy workflow

CRAN release process (1)

cran-comments.md

Lint, format, editor (1)

RStudio project

Show all practicesHide 1 practice

Git structural (1)

.gitattributes

How this is detected·Detection ruleset v4 (2026-10-20)

AI coding toolsBeta

This repository shows signs of AI coding tools.

Claude Codefirst seen 2026-06-26
Named in .Rbuildignore: .claude, CLAUDE.md
Named in .gitignore: .claude, CLAUDE.md
Commits: at least 23 crediting it in the message

From outside contributors

Claude Code
Pull requests: 1 from outside contributors, first on 2026-06-26

Models named in its commits

Claude Opus 4.814 commits · Jun to Jul 2026
Claude Opus 5.58 commits · Sep to Oct 2026
Claude Fable 51 commit · Jul 2026

Counts are commits, not lines of code. Commits by a tool's accounts count once across all of its accounts. Commits crediting it are the largest count among its credit lines, a minimum.How this is detected·Detection ruleset v4 (updated 2026-09-27)

Dependencies

Declared dependencies

9 external dependencies (excludes base and recommended)

Installing BigDataPE adds 21 packages (13 with compiled code, 7.4 MB of source tarballs). Heaviest: openssl 1.1 MB, vctrs 1.0 MB, dplyr 902 KB.

Depends (1)

R >= 4.1.0

Imports (1)

apifetch

LinkingTo (0)

none

Suggests (8)

knitr rmarkdown tidyr dplyr tibble httr2 testthat withr

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

People & History

People (6)

André Leite

Author, Maintainer · added in 0.2.0

Carlos Amorim

Author · added in 0.2.0

Diogo Bezerra

Author

Júlia Nascimento Barreto

Author · added in 0.3.0

Hugo Vasconcelos

Author · added in 0.2.0

Marcos Wasiliew

Author · added in 0.2.0

Maintainer since 0.0.9 (2024)

Listed in earlier versions (4)

Show 4 peopleHide 4 people

Andre Leite

no longer listed · 0.0.9 to 0.1.0

Hugo Vaconcelos

no longer listed · 0.0.9 to 0.1.0

Carlos Amorin

no longer listed · 0.1.0

Marcos Wasilew

no longer listed · 0.1.0

Releases (6)

Pick two releases to compare their code metrics.

0.3.0Latest
record
2026-10-01 · current release · diff ↗
0.2.0
record
2026-07-15 · diff ↗
R
R 4.6.0 released · 2026-04-24
0.1.0
record
2026-04-07 · diff ↗
R
R 4.5.0 released · 2025-04-11
0.0.96
record
2025-04-02 · diff ↗
unarchivedReturned to CRAN
2025-02-17
0.0.95
record
2025-02-17 · diff ↗
archivedRemoved from CRAN
2025-01-31
policy violation Phishing attempt on macOS
0.0.9
record
2024-12-16
R
R 4.4.0 released · 2024-04-24

Package metadata

First published: 2024-12-16
Total releases: 6 / 2 yrs
License: MIT + file LICENSE OSI
Minimum R: ≥ 4.1.0
Download size: 100 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("BigDataPE")

Format

Leite, A., Amorim, C., Bezerra, D., Nascimento Barreto, J., Vasconcelos, H., & Wasiliew, M. (2026). BigDataPE: Secure and Intuitive Access to 'BigDataPE' 'API' Datasets (Version 0.3.0) [Computer software]. https://doi.org/10.32614/CRAN.package.BigDataPE

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for BigDataPE version 0.3.0 [Data set]. HJJB, LLC. Data release v2026-10-26. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-26, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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