I am running two pipeline stages on my GitLab cl (homemade Docker contatiner with R-base on Ubuntu:16.04). The only track of the error is in the codecov step (while R check is successful). This is the error message and command (on GitLab):
$ Rscript -e 'covr::package_coverage(type="tests", quiet = FALSE)'
(...)
* DONE (mypkg)
Running specific tests for package ‘mypkg’
Running ‘testthat.R’
Error: Failure in `/tmp/RtmpGgElCC/R_LIBS94b18abb4/mypkg/mypkg-tests/testthat.Rout.fail`
As usual, I can not replicate this error locally. No other message related to the error is shown. Moreover, I can not find a way to retrieve that log file. Is it possible?
Use a Codecov token:
# your .gitlab-ci.yml, ending with:
- apt-get install —yes git
- R -e 'covr::codecov(token = "yourtoken")'
Get your token from https://codecov.io/your_name/your_project/settings.
See my own implementation at https://gitlab.com/msberends/AMR :)
Related
The nuclio desktop is showing exit status 1 and not showing any functions that we deploy using nuctl deploy. Nuclio is showing as orphan container though docker ps shows a port assigned to it.a Also nuctl get functions is giving error as below
/nuclio/pkg/cmdrunner/shellrunner.go:96
Failed to execute command: /bin/sh -c "/bin/cat /etc/nuclio/store/functions/nuclio/*"
/nuclio/pkg/platform/local/store.go:408
Failed to run cat command
/nuclio/pkg/platform/local/store.go:335
Failed to get functions
/nuclio/pkg/platform/local/store.go:253
Failed to read functions from local store
/nuclio/pkg/platform/local/store.go:217
mlusers#annotate-clone:~/cvat$
_
Link for the issue on github: https://github.com/opencv/cvat/issues/4866#issue-1352210392
I am trying to build and deploy this bookdown project with GitHub Actions. One of the chapters uses the keras R package, which means I need to install Conda (or set up a virtual environment). At the end of the Miniconda installation command, there is an error when trying to collect metadata.
2020-06-24T04:47:59.7495480Z * Miniconda has been successfully installed at '/Users/runner/Library/r-miniconda'.
2020-06-24T04:47:59.7496060Z [1] "/Users/runner/Library/r-miniconda"
2020-06-24T04:48:00.3909040Z * Project '~/runners/2.263.0/work/drake/drake' loaded. [renv 0.10.0]
2020-06-24T04:48:00.7964920Z * The project and lockfile are out of sync -- use `renv::status()` for more details.
2020-06-24T04:48:00.7968340Z Warning message:
2020-06-24T04:48:00.7969190Z Project requested R version '3.6.0' but '4.0.1' is currently being used
2020-06-24T04:48:05.2408080Z Collecting package metadata (current_repodata.json): ...working... failed
2020-06-24T04:48:05.2410390Z
2020-06-24T04:48:05.2410820Z NotWritableError: The current user does not have write permissions to a required path.
2020-06-24T04:48:05.2411080Z path: /usr/local/miniconda/pkgs/cache/b89cf7bf.json
2020-06-24T04:48:05.2411230Z uid: 501
2020-06-24T04:48:05.2411350Z gid: 20
2020-06-24T04:48:05.2411430Z
2020-06-24T04:48:05.2411690Z If you feel that permissions on this path are set incorrectly, you can manually
2020-06-24T04:48:05.2411940Z change them by executing
2020-06-24T04:48:05.2412010Z
2020-06-24T04:48:05.2412260Z $ sudo chown 501:20 /usr/local/miniconda/pkgs/cache/b89cf7bf.json
2020-06-24T04:48:05.2412330Z
2020-06-24T04:48:05.2413470Z In general, it's not advisable to use 'sudo conda'.
2020-06-24T04:48:05.2413570Z
2020-06-24T04:48:05.2414250Z
2020-06-24T04:48:05.2886400Z ##[error]Error: Error 1 occurred creating conda environment r-reticulate
2020-06-24T04:48:05.2890770Z Execution halted
2020-06-24T04:48:05.3050700Z ##[error]Process completed with exit code 1.
The full job log is here.
Depending on how R is set up, this post might be helpful for you. You might need to configure the .Renviron file.
Unable to change python path in reticulate (R)
I am trying to install mlflow in R and im getting this error message saying
mlflow::install_mlflow()
Error in mlflow_conda_bin() :
Unable to find conda binary. Is Anaconda installed?
If you are not using conda, you can set the environment variable MLFLOW_PYTHON_BIN to the path of yourpython executable.
I have tried the following
export MLFLOW_PYTHON_BIN="/usr/bin/python"
source ~/.bashrc
echo $MLFLOW_PYTHON_BIN -> this prints the /usr/bin/python.
or in R,
sys.setenv(MLFLOW_PYTHON_BIN="/usr/bin/python")
sys.getenv() -> prints MLFLOW_PYTHON_BIN is set to /usr/bin/python.
however, it still does not work
I do not want to use conda environment.
how to I get past this error?
The install_mlflow command only works with conda right now, sorry about the confusing message. You can either:
install conda - this is the recommended way of installing and using mlflow
or
install mlflow python package yourself via pip
To install mlflow yourself, pip install correct (matching the the R package) python version of mlflow and set the MLFLOW_PYTHON_BIN environment variable as well as MLFLOW_BIN evn variable: e.g.
library(mlflow)
system(paste("pip install -U mlflow==", mlflow:::mlflow_version(), sep=""))
Sys.setenv(MLFLOW_BIN=system("which mlflow"))
Sys.setenv(MLFLOW_PYTHON_BIN=system("which python"))
Just ran across this, and the accepted answer by #Tomas was very helpful. I added a comment above but, for some additional context, I wanted to create a more thorough response if any other Enterprise Databricks R users run across this post trying to use the MLflow package for R on Databricks.
The Databricks MLflow quickstart guide will tell you that you need to run the following:
library(mlflow)
install_mlflow()
However, for Enterprise Databricks users, the install_mlflow() function will fail if your cluster doesn't have outside connectivity privileges (as most probably don't) and can't connect to the Anaconda repo to download the necessary packages. You'll likely get an error like this:
CondaHTTPError: HTTP 000 CONNECTION FAILED for url https://conda.anaconda.org/conda-forge/linux-64/current_repodata.js
The good news is that MLflow should already be installed on your Databricks runtime. So you can reference that install instead, and then as #Tomas mentioned, use it to set your R environment variables for MLFLOW_BIN and MLFLOW_PYTHON_BIN. From there, the R MLflow API works as specified (in my experience, but ymmv).
The only catch from the above solution is that when you use the system()function in R, you need to set intern=TRUE in order capture the output of the command. The default behavior of the system() function is intern=FALSE. Thus if you do not explicitly set intern=TRUE, then the exit code 0 will be returned from your system() call (or perhaps another exit code upon an error) and Sys.setenv() will set the environment variable to 0!
### intern=True missing ###
Sys.setenv(MLFLOW_BIN=system("which mlflow"))
Sys.setenv(MLFLOW_PYTHON_BIN=system("which python"))
Example output (you can see the the environment variables did not get set correctly):
s <- Sys.getenv()
s[grep("MLFLOW", names(s))]
MLFLOW_BIN 0
MLFLOW_CONDA_HOME /databricks/conda
MLFLOW_PYTHON_BIN 0
MLFLOW_PYTHON_EXECUTABLE
/databricks/python/bin/python
MLFLOW_TRACKING_URI databricks
However, when intern=TRUE, you'll get the correct environment variables:
### intern=True set ###
Sys.setenv(MLFLOW_BIN=system("which mlflow", intern=TRUE))
Sys.setenv(MLFLOW_PYTHON_BIN=system("which python", intern=TRUE))
Example output:
s <- Sys.getenv()
s[grep("MLFLOW", names(s))]
MLFLOW_BIN /databricks/python3/bin/mlflow
MLFLOW_CONDA_HOME /databricks/conda
MLFLOW_PYTHON_BIN /databricks/python3/bin/python
MLFLOW_PYTHON_EXECUTABLE
/databricks/python/bin/python
MLFLOW_TRACKING_URI databricks
Note: This was using Databricks runtime 9.1 LTS ML. This may or may not work on other Databricks runtime configurations.
I am trying to add Codecov support via library(covr) to my personal R package sesh.
When I check locally the coverage tests run and report without incident:
covr::package_coverage()
sesh Coverage: 68.75%
R/executeDevtoolDocument.R: 0.00%
R/sesh.R: 69.23%
But when it runs on Travis it encounters an error for missing token:
$ Rscript -e 'covr::codecov()'
Error in if (nzchar(token)) { : argument is of length zero
Calls: <Anonymous>
Execution halted
The R CMD check runs successfully on Travis.
The contents of my .travis.yml:
language: R
matrix:
include:
- r: release
after_success: Rscript -e 'covr::codecov()'
r_github_packages:
- r-lib/covr
And a link to the most recent Travis report.
I have tried to faithfully follow the covr README for getting set up. And the README says Travis is supported without needing CODECOV_TOKEN, so I have not tried to pass one yet.
What am I missing here?
Following is my .travis.yml
language: r
cache: packages
script:
- R CMD build .
- R CMD check *tar.gz
r_github_packages:
- r-lib/covr
after_success:
- Rscript -e 'covr::codecov()'
Adding the repository upload token to codecov.yml avoids the error and successfully runs the coverage report.
codecov:
token: a1c53d1f-266f-47bc-bb23-3b3d67c57b2d
The token is found in the 'Settings(tab) >>> General(sidebar)' menu on the Codecov page for the repo (which is only visible once you are logged in).
I just reported the following issue to the hadley/ggplot2-book repository:
When i press STRG+SHIFT+B in RStudio to build the book as described in the Readme I get this error:
mkdir -p book/tex
mkdir -p book/tex/_figures
mkdir -p book/tex/diagrams
cp book/ggplot2-book.tex book/tex/ggplot2-book.tex
Rscript book/render-tex.R data-manip.rmd
Error in rmarkdown::pandoc_options(to = "latex", from = "markdown_style", :
could not find function "pandoc_latex_engine_args"
Calls: <Anonymous> -> <Anonymous> -> structure -> <Anonymous>...
I have R 3.2.2, Rtools 3,2,x , pandoc 1.15.2 and installed all the dependencies as well as the inconsolata font. I have MikTeX 2.9 and also updated all packages that where updatable.
When I try ?pandoc_latex_engine_args (which presumably causes the error) the help page opens so this function should be available to R. I tried on 2 different computers (Windows 10 and Windows 7) and reran the complete installation process on each without any change. I also tried to manually build the book using the Cygwin terminal but this gives the same error.
Has anyone trying to build the book had the same problem or even better: does anyone know how to fix this?