PietrH

repo <- "my_org/my_repo"
zenodo_token <- "token from url in webhook page of repo"

repo_response <- 
  httr2::request("https://api.github.com/repos") %>% 
  httr2::req_url_path_append(repo) %>% 
  httr2::req_perform() %>% 
  httr2::resp_body_json()

release_response <- 

PietrH

ripple_shuffle <- function(object) {
  purrr::map(
    seq(1, length(object) / 2),
    ~ c(
      purrr::chuck(object, .x),
      purrr::chuck(object, length(object) - .x + 1)
    )
  ) %>% 
    unlist()
}

PietrH

get_inat_obs_radius <- function(taxon_id, lat, lng, radius) {
  api_response <- httr2::request(
    "https://api.inaturalist.org/v1/observations/"
  ) %>%
    httr2::req_url_query(
      taxon_id = taxon_id,
      lat = lat,
      lng = lng,
      radius = radius
    ) %>%

PietrH

library(dplyr)
# Ensure ETN API-beta version
remotes::install_github("inbo/[email protected]")
library(etn)

# Get number of detections, species and animals for lifewatch presentation
project_codes_to_investigate <- c(
  "2010_PHD_REUBENS",
  "2011_RIVIERPRIK",
  "2012_LEOPOLDKANAAL",

PietrH

# We are trying to find the closest allele per gene

## You could possibly do this with this package as well: 
## https://bioconductor.org/packages/release/bioc/vignettes/GenomicRanges/inst/doc/GenomicRangesIntroduction.html#finding-the-nearest-genomic-position-in-granges-objects

library(dplyr) # A Grammar of Data Manipulation
library(assertthat) # Easy Pre and Post Assertions

# Some example data

PietrH

cli::cli_abort("Friend{?s}: {zwoog}",
               .envir = rlang::new_environment(
                 data = list(zwoog = c("Luc","Tendi")
                             )
                 )
               )

PietrH

httr2::request("https://raw.githubusercontent.com/enram/aloftdata.eu/refs/heads/main/_data/OPERA_RADARS_DB.json") |>
  httr2::req_perform() |>
  httr2::resp_body_json(check_type = FALSE) |>
  purrr::map(~dplyr::tibble(
    number = .x$number,
    country = .x$country,
    countryid = .x$countryid,
    oldcountryid = .x$oldcountryid,
    wmocode = .x$wmocode,
    odimcode = .x$odimcode,

PietrH

library(magrittr)
rmi_url <- "https://opendata.meteo.be/ftp/observations/radar/vbird/denhb/2024/denhb_vpts_20240128.txt"

header <- readr::read_lines(rmi_url) %>% 
  .[stringr::str_starts(.,"#")] %>%
  tail(1) %>% 
  stringr::str_remove("#") %>% 
  stringr::str_split(" ", simplify = TRUE) %>%
  .[nchar(.) > 0]

PietrH

Library(dplyr)

# Which package to check
trias_namespace <- asNamespace("trias")

# Character vector of all functions and their arguments, print method of base ls with str() on every object
trias_fns_args <- capture.output(utils::lsf.str(trias_namespace))

# Extract the functions

PietrH

round_coordinates <- function(wkt_string, digits = 4) {
  wkt_object_type <- wkt_string %>%
    stringr::str_extract(".*?(?=\\()")

  x_coord <- wkt_string %>%
    stringr::str_extract("(?<=POINT\\()[0-9]+\\.[0-9]+") %>%
    as.numeric()

  y_coord <- wkt_string %>%
    stringr::str_extract("[0-9]+\\.[0-9]+(?=\\))") %>%