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download climate data from DWD (German Weather Service)
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DWDdata
R readDWD.raster: gunzip arguments can now be changed. The default is n… Apr 19, 2019
data selectDWD: computing speed extremely increased by removing grepl call… Mar 15, 2019
localtests createVignettes: parallized markdown rendering, removed functionally … Apr 23, 2019
man readDWD.raster: gunzip arguments can now be changed. The default is n… Apr 19, 2019
presentation presentation: map code and links updated Feb 6, 2017
vignettes
.Rbuildignore implementing new vignette policy of devtools Feb 11, 2019
.Rprofile BugReports entry added Aug 25, 2017
.gitignore
DESCRIPTION readDWD.raster: gunzip arguments can now be changed. The default is n… Apr 19, 2019
NAMESPACE gridbase is now exported, as intented from the start Apr 19, 2019
NEWS
README.md
cran-comments.md indexes updated Nov 26, 2018
zz_rdwd.Rproj Rproj files unified Aug 11, 2017

README.md

rdwd

rdwd is an R package to select, download and read climate data from the German Weather Service (Deutscher Wetterdienst, DWD). They provide over 228 thousand datasets with weather observations online at ftp://ftp-cdc.dwd.de/pub/CDC/observations_germany/climate.

rdwd is available on CRAN: CRAN_Status_Badge downloads Rdoc "rdwd dependencies"

It has been presented at FOSDEM 2017 and UseR!2017 in Brussels, featured in Rstudios data package list and written about in OSOR.

Usage of the package usually looks something like the following:

# download and install the rdwd package (only needed once):
install.packages("rdwd")
# if wanted, latest development version, incl. vignettes:
remotes::install_github("brry/rdwd", build_opts="--no-manual")

# load the package into library (needed in every R session):
library(rdwd)

# select a dataset (e.g. last year's daily climate data from Potsdam City):
link <- selectDWD("Potsdam", res="daily", var="kl", per="recent")

# Actually download that dataset, returning the local storage file name:
file <- dataDWD(link, read=FALSE)

# Read the file from the zip folder:
clim <- readDWD(file, varnames=TRUE)

# Inspect the data.frame:
str(clim)

You can also select datasets with the interactive map.
Installation instructions and more examples are available in the package vignette.
Long actual-usage examples can be found in the use cases vignette.

vignette("mapDWD") # interactive map, likely faster than CRAN link above
vignette("rdwd")   # package instructions and examples
vignette("cases")  # longer use case examples

help

I'm looking for someone to help implement multiple downloads in dataDWD via e.g. curl or wget. The requirements are as follows:

  • works cross-platform
  • is called from R
  • has as few dependencies as possible
  • does not fail completely at a single failure, e.g. can be called within try
  • optimally enables a progress bar
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