I was recently forced to update R to the latest version of 4.1.2 and since then my connection to db2 is not working. I use ibmdbR. I follow the steps as recommended by IBM:
https://www.ibm.com/docs/en/db2-warehouse?topic=science-r-development-environment
it fails at step d, nitialising the analytics package by issuing the following R command.
The ODBC connection works (or seems to be working) but idaInit(con) fails with the following error:
> idaInit(con) #this fails
Error in assign("idaRGlobal", new.env(parent = baseenv()), envir = baseenv()) :
cannot add binding of 'idaRGlobal' to the base environment
The con object is created without an issue:
> con <- idaConnect(con.text) # this is successful and con is created
I've tested my ODBC connection using online reference (below) and it's successful.
https://www.ibm.com/docs/en/db2-warehouse?topic=programmatically-odbc-cli
More info on setup:
> sessionInfo()
R version 4.1.2 (2021-11-01)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 18363)
Matrix products: default
locale:
[1] LC_COLLATE=English_Australia.1252 LC_CTYPE=English_Australia.1252 LC_MONETARY=English_Australia.1252 LC_NUMERIC=C
[5] LC_TIME=English_Australia.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] ibmdbR_1.50.0 arules_1.7-2 Matrix_1.4-0 RODBC_1.3-19
loaded via a namespace (and not attached):
[1] magrittr_2.0.1 MASS_7.3-54 tidyselect_1.1.1 munsell_0.5.0 colorspace_2.0-2 lattice_0.20-45 R6_2.5.1 rlang_0.4.12 fansi_0.5.0 dplyr_1.0.7
[11] tools_4.1.2 parallel_4.1.2 grid_4.1.2 rpart.plot_3.1.0 gtable_0.3.0 utf8_1.2.2 ellipsis_0.3.2 tibble_3.1.6 lifecycle_1.0.1 crayon_1.4.2
[21] purrr_0.3.4 ggplot2_3.3.5 vctrs_0.3.8 rpart_4.1-15 glue_1.5.1 compiler_4.1.2 pillar_1.6.4 generics_0.1.1 scales_1.1.1 pkgconfig_2.0.3
It seems the error comes from executing this assignment in the code: assign("idaRGlobal", new.env(parent = baseenv()), envir=baseenv())
idaInit() code can be found here: rdrr.io/cran/ibmdbR/src/R/connection.R
I have completely removed R with all its libraries and installed everything from scratch, so I don't see how it could be a versioning issue. All packages seem to have the latest version. The only package that hasn't been updated after the release of R 4.2.1 are RODBC and IBMDBR.
Edit: Tried using RODBC directly and the connection works fine.
Related
I have ggplot2 3.4.0 installed on Ubuntu 22.04, but for some reasons I would like to use older version ggplot2 3.3.6.
library(ggplot2, lib.loc="~/R/ggplot336/")
I worked fine when I started with a clean script file. However, when I use an existing script file like:
library(ggplot2, lib.loc="~/R/ggplot336/")
ggimage::geom_image()
I got the following error massage:
Error in value[3L] :
Package ‘ggplot2’ version 3.4.0 cannot be unloaded:
Error in unloadNamespace(package) : namespace ‘ggplot2’ is imported by ‘ggfun’, ‘ggplotify’, ‘ggimage’ so cannot be unloaded
Edit
Fresh start Rstudio
Open my R script file with following 3 lines:
sessionInfo()
library(ggplot2, lib.loc="~/R/ggplot336/")
ggimage::geom_image()
When I run the first line, sessionInfo() before doing anything else. We can see ggplot2_3.4.0 there. Could this be a Rstudio feature or an issue?
R version 4.2.2 Patched (2022-11-10 r83330)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 22.04.1 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.10.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0
locale:
[1] LC_CTYPE=en_AU.UTF-8 LC_NUMERIC=C LC_TIME=en_AU.UTF-8
[4] LC_COLLATE=en_AU.UTF-8 LC_MONETARY=en_AU.UTF-8 LC_MESSAGES=en_AU.UTF-8
[7] LC_PAPER=en_AU.UTF-8 LC_NAME=C LC_ADDRESS=C
[10] LC_TELEPHONE=C LC_MEASUREMENT=en_AU.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
loaded via a namespace (and not attached):
[1] Rcpp_1.0.9 highr_0.9 pillar_1.8.1 compiler_4.2.2
[5] R.utils_2.12.2 R.methodsS3_1.8.2 yulab.utils_0.0.5 tools_4.2.2
[9] digest_0.6.30 evaluate_0.18 jsonlite_1.8.3 lifecycle_1.0.3
[13] tibble_3.1.8 gtable_0.3.1 ggimage_0.3.1 R.cache_0.16.0
[17] pkgconfig_2.0.3 rlang_1.0.6 reprex_2.0.2 DBI_1.1.3
[21] cli_3.4.1 ggplotify_0.1.0 rstudioapi_0.14 magick_2.7.3
[25] yaml_2.3.6 xfun_0.35 fastmap_1.1.0 knitr_1.41
[29] withr_2.5.0 dplyr_1.0.10 styler_1.8.1 generics_0.1.3
[33] vctrs_0.5.1 fs_1.5.2 gridGraphics_0.5-1 grid_4.2.2
[37] tidyselect_1.2.0 glue_1.6.2 R6_2.5.1 processx_3.8.0
[41] fansi_1.0.3 rmarkdown_2.18 clipr_0.8.0 callr_3.7.3
[45] ggplot2_3.4.0 purrr_0.3.5 magrittr_2.0.3 ps_1.7.2
[49] htmltools_0.5.3 scales_1.2.1 assertthat_0.2.1 colorspace_2.0-3
[53] utf8_1.2.2 munsell_0.5.0 ggfun_0.0.9 R.oo_1.25.0
It looks like R studio is loading in all of the previous libraries from a previous session. Maybe something leftover in .RData or .Rhistory. A fresh start of R should have far few loaded libraries.
Here is my fresh start:
sessionInfo()
R version 4.2.2 (2022-10-31)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Monterey 12.6.1
Matrix products: default
LAPACK: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
loaded via a namespace (and not attached):
[1] compiler_4.2.2 tools_4.2.2
In Rstudio's preference you should see this screen:
I would try unchecking all of the boxes and then quit and restart Rstudio to see if that clears up the problem.
After some experiments, I kind of worked out the problem. Since this has consumed so much time of my time, I thought this could be helpful to others.
The problem is :: (double colon) with packages using ggplot2, such as ggimage in my example. It appears that RStudio automatically load some dependent packages when a script file is open. One way to fix this problem for my work now is to remove ::, but use library() then function (geom_image) instead.
This fixed my problem but I still don't understand why RStudio behaves this way.
If :: (double colon) is necessary, comment lines containing ::, then after loading older version of ggplot2, uncomment those lines. A little awkward, but it works for me.
My website used to work fine in my previous laptop, which used R 3.6.3. In my new laptop when I run blogdown::serve_site() I get the error Error in !server$daemon : invalid argument type. I tried doing what was suggested here but didn't help.
Here is the session info:
R version 4.1.0 (2021-05-18)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Big Sur 11.2.3
Matrix products: default
LAPACK: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRlapack.dylib
locale:
[1] en_GB.UTF-8/en_GB.UTF-8/en_GB.UTF-8/C/en_GB.UTF-8/en_GB.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
loaded via a namespace (and not attached):
[1] Rcpp_1.0.6 bookdown_0.22 digest_0.6.27 later_1.2.0 R6_2.5.0
[6] jsonlite_1.7.2 magrittr_2.0.1 evaluate_0.14 blogdown_1.3.2 rlang_0.4.11
[11] rstudioapi_0.13 promises_1.2.0.1 rmarkdown_2.9 tools_4.1.0 servr_0.22
[16] httpuv_1.6.1 xfun_0.24 yaml_2.2.1 compiler_4.1.0 htmltools_0.5.1.1
[21] knitr_1.33
This is the website link and you can find the Github repo here.
You should remove the quotes on interactive(). It should be
servr.daemon = interactive()
instead of
servr.daemon = "interactive()"
Actually servr.daemon = interactive() is the default, so you don't really need to set it explicitly (i.e., you can remove this setting).
I recently updated to R 4.03 and since doing so I have had difficulty uploading csv files in R studio. This is true whether trying to import with code or when manually importing using the tab Environment -> "Import Dataset." The error message I receive is "Error in if (num_colors < 256) { : missing value where TRUE/FALSE needed."
Here is the code I am using:
library(readr)
df <- read_csv("df.csv")
Error in if (num_colors < 256) { : missing value where TRUE/FALSE needed`
I thought this may have something to do with the package "crayon" but loading this library does not seem to make a difference.
Furthermore, when I save "df.csv" as an excel file "df.xlsx" I am able to load the dataset without issue using the following code
library(readxl)
df <- read_excel(df.xlsx)
I don't encounter this problem when using R 4.0.2 on a different machine, so I suspect this issue may be related to the upgrade.
Any insights are appreciated.
Update:
Newish R user and I appreciate everyone's interest in this question. I believe the session is clean. Per Ben's request:
find("read_csv")
[1] "package:readr"
sessionInfo()
R version 4.0.3 (2020-10-10)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows >= 8 x64 (build 9200)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 LC_MONETARY=English_United States.1252 LC_NUMERIC=C
[5] LC_TIME=English_United States.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] dplyr_1.0.3 crayon_1.4.1 readxl_1.3.1 plyr_1.8.6 readr_1.4.0
loaded via a namespace (and not attached):
[1] Rcpp_1.0.6 rstudioapi_0.13 magrittr_2.0.1 hms_1.0.0 tidyselect_1.1.0 lattice_0.20-41 R6_2.5.0 rlang_0.4.10 fansi_0.4.2
[10] tools_4.0.3 grid_4.0.3 utf8_1.1.4 DBI_1.1.1 cli_2.3.0 ellipsis_0.3.1 assertthat_0.2.1 tibble_3.0.5 lifecycle_0.2.0
[19] Matrix_1.2-18 purrr_0.3.4 vctrs_0.3.6 glue_1.4.2 compiler_4.0.3 pillar_1.4.7 cellranger_1.1.0 generics_0.1.0 pkgconfig_2.0.3
I'd suggest updating RStudio to the latest version as well as R.
That did the trick for me.
Edit
In view of Ben's request below.
R version: 4.0.4;
RStudio version: 1.4.1103
thanks for checking out my very first post. please bear with my formatting.
Issue summary: I have been using tdplyr to access teradata database with no issue until I tested another package called dplyr.teradata for potential performance enhancement. However I can no longer connect to the database due to the following error messages:
Error: package or namespace load failed for 'tdplyr':.onLoad failed
in loadNamespace() for 'tdplyr', details:
call: parent.env(from)
error: argument is not an environment
so I deleted the dplyr.teradata package, thought that would allow my original tdplyr to work, but I still get the same error message above. then I deleted the tdplyr package without backup, trying to reinstall using the original script below:
install.packages('tdplyr',repos=c('https://teradata-download.s3.amazonaws.com','https://cloud.r-
project.org'))
but fail to install because of the same error again. Hope someone could advise on fix.
My sessioninfo is below:
sessionInfo()
R version 4.0.3 (2020-10-10)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 16299)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C
[5] LC_TIME=English_United States.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] rlang_0.4.10 teradatasql_17.0.0.8 odbc_1.3.0 dplyr_1.0.2
[5] dbplyr_2.0.0 digest_0.6.27 DBI_1.1.0 hms_0.5.3
[9] bit64_4.0.5 bit_4.0.4
loaded via a namespace (and not attached):
[1] Rcpp_1.0.5 rstudioapi_0.13 magrittr_1.5 tidyselect_1.1.0 R6_2.4.1
[6] blob_1.2.1 tools_4.0.3 xfun_0.20 tinytex_0.28 ellipsis_0.3.1
[11] assertthat_0.2.1 tibble_3.0.4 lifecycle_0.2.0 crayon_1.3.4 zip_2.1.1
[16] purrr_0.3.4 vctrs_0.3.6 glue_1.4.2 openxlsx_4.2.3 stringi_1.5.3
[21] compiler_4.0.3 pillar_1.4.6 generics_0.0.2 pkgconfig_2.0.3
found the answer myself. Pasting the answer below.
The Teradata R package is incompatible with dbplyr v2.0.0 and its later versions, which introduced some breaking changes. To use tdplyr, the version of dbplyr package must be v1.4.4. tdplyr should be installed using the following commands from your Terminal (for Linux and Mac) or Command Prompt (for Windows), till a new version that is compatible with dbplyr v2.0.0 and its later versions is released:
Install dbplyr v1.4.4 first. There are various ways to install a specific version of a R package. Teradata recommends using the following command:
Rscript -e "remotes::install_version('dbplyr',version='1.4.4',repos='https://cloud.r-project.org')"
Note: To run this above command, the R package remotes should be present on the client machine.
Next to download and install tdplyr and dependencies automatically, if minimum required versions are not met, specify the Teradata R package repository and CRAN in the repos argument for install.packages.
Rscript -e "install.packages('tdplyr',repos=c('https://teradata-download.s3.amazonaws.com','https://cloud.r-project.org'))"
I've successfully installed Lime (and glmnet) in R but when I try loading it i receive an error:
> require(lime)
Loading required package: lime
Error: package or namespace load failed for ‘lime’:
object ‘coef.cv.glmnet’ is not exported by 'namespace:glmnet'
Searched online and can't seem to find a solution for this.
This is my sessioninfo()
> sessionInfo()
R version 3.6.1 (2019-07-05)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 17763)
Matrix products: default
locale:
[1] LC_COLLATE=English_Australia.1252 LC_CTYPE=English_Australia.1252 LC_MONETARY=English_Australia.1252 LC_NUMERIC=C
[5] LC_TIME=English_Australia.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] glmnet_3.0 Matrix_1.2-17
loaded via a namespace (and not attached):
[1] Rcpp_1.0.3 rstudioapi_0.10 magrittr_1.5 tidyselect_0.2.5 munsell_0.5.0 colorspace_1.4-1 lattice_0.20-38 R6_2.4.0 rlang_0.4.1
[10] foreach_1.4.7 dplyr_0.8.3 tools_3.6.1 grid_3.6.1 gtable_0.3.0 iterators_1.0.12 lazyeval_0.2.2 assertthat_0.2.1 tibble_2.1.3
[19] crayon_1.3.4 purrr_0.3.3 ggplot2_3.2.1 codetools_0.2-16 shape_1.4.4 glue_1.3.1 compiler_3.6.1 pillar_1.4.2 scales_1.0.0
[28] pkgconfig_2.0.3
I've updated all my packages.
glmnet loads successfully
> library(glmnet)
Loaded glmnet 3.0
The recent major update of glmnet (which now does not export coef.cv.glmnet anymore) appears to have broken lime. You can see errors with the same cause in the CRAN tests. You can expect a fix by the package maintainer soon (or the package will be archived by CRAN). See also this bug report and the answer by the maintainer:
This is due to a recent breaking change in glmnet—lime will be updated soon to fix this