Blog – Hugo Gruson

Categories

All (19)

API (2)

COVID-19 (1)

GitHub Actions (1)

R (14)

R package (3)

S3 (1)

accessibility (1)

automation (2)

code quality (1)

community (2)

continuous integration (3)

contribution (1)

data aggregation (1)

data-extraction (1)

ecosystem (1)

health (1)

input validation (1)

interoperability (2)

lifecycle (1)

object orientation (1)

open access (1)

open science (2)

open source (1)

package development (4)

progressive enhancement (1)

recognition (1)

renv (1)

reproducibility (1)

research software (1)

rvest (1)

software review (1)

testing (1)

tibble (1)

tidy-data (1)

tidyverse (1)

web scraping (1)

Politely mapping recommended travel vaccines

R

web scraping

rvest

health

Ahead of any trip I am planning, I check if any travel vaccines are recommended, because of the potential presence of pathogens that may not be present in my home country.

Improving Ecosystem Interoperability Iteratively via Progressive Enhancement

R

interoperability

S3

progressive enhancement

ecosystem

lifecycle

object orientation

2024 mpox outbreak: common analytics tasks and available R tools

James Azam, Hugo Gruson, Adam Kucharski

Choosing the Right Parent for R Object Classes

Make your functions compa-tibble

R

interoperability

tidyverse

tibble

tibbles are described as “a modern reimagining of the data.frame, with subtle differences in the way the default data.frame behaviour, based on years of experience”.

Things that can go wrong when using renv

R

reproducibility

renv

System dependencies in R packages and automatic testing

package development

R

R package

continuous integration

From hidden to visible: how can we recognise research software?

research software

recognition

open science

Stephan Druskat, Hugo Gruson, Carlos Martinez, João Morado, Deborah Leem

xlcutter 0.1.0

R

R package

data-extraction

tidy-data

The starting point of every analysis is getting good data. Importantly, this data should be accessible, and not be locked in, e.g., a PDF. Many data analysts and data…

Ensuring & Showcasing the Statistical Correctness of your R Package

R

code quality

testing

continuous integration

Minimum R version dependency

package development

R

R package

Hugo Gruson, Maëlle Salmon

Opening the door to new contributors in open source projects

open source

community

contribution

Hugo Gruson, Heather Turner

Why You Should (or Shouldn’t) Build an API Client?

API

R

package development

Maëlle Salmon, Matthias Grenié, Hugo Gruson

Dealing with flaky GitHub Actions

GitHub Actions

continuous integration

R

automation

Checking the Inputs of your R Functions

R

package development

input validation

Hugo Gruson, Sam Abbott, Carl Pearson

Covidpreprints.com: Automating Website Updates with the europepmc and rAltmetric Packages

R

automation

COVID-19

data aggregation

Zhang-He Goh, Jonny Coates, Hugo Gruson

Community Captioning of rOpenSci Community Calls

community

accessibility

Matthias Grenié, Hugo Gruson

Access Publisher Copyright & Self-Archiving Policies via the ‘SHERPA/RoMEO’ API

R

open access

API

Matthias Grenié, Hugo Gruson

When Standards Go Wild - Software Review for a Manuscript

R

software review

open science

Stefanie Butland, Nick Golding, Chris Grieves, Hugo Gruson, Thomas White, Hao Ye