Authorize ShinyApps In Rstudio - r

I am trying to authorize my shinyapps account on my Rstudio console, but when I run the setAccountInfo() , i get the following error
Failed to connect to api.shinyapps.io port 443: Connection refused
I am under a proxy connection in my college.although i have run the following code to work under proxy and it used to work for installing packages from github etc. but to authorize its still not working
library(httr)
set_config(
use_proxy(url="10.3.100.207", port=8080)
)
i have even enabled internet2. but all the attempts are futile. any help ?

If you're running behind a proxy server, you'll want to configure the shinyapps package to use your proxy server. Checkout the docs in ?shinyapps::shinyappsProxies for more information, but in short you'll likely want to do:
Sys.setenv(http_proxy = "http://username:password#proxy.example.com:8080")
It can be helpful to put this command in your .Rprofile so its runs everytime you launch R.

Related

Swagger UI does not show up in JupyterLab

I have saved one R script with name MC_APIv1.1-Prod.R in Jupyterlab and when I run the following code in R Console of Jupyterlab :
plumber::plumb("MC_APIv1.1-Prod.R")$run(host = "0.0.0.0", port = 5763,swagger = TRUE)
It gives the following message:
Running plumber API at http://0.0.0.0:5763
Running swagger Docs at http://127.0.0.1:5763/__docs__/
But I can't see the swagger UI while kernel is still running. When I run this code in RStudio then I can see the swagger window and it shows the plot in the browser window but it is not working in my case.
Can anyone please explain what is happening here and how to resolve this issue. Any help would be appreciated.
Complete code for the mentioned R file is here.
Maybe check this direction:
https://stackoverflow.com/questions/1694144/can-two-applications-listen-to-the-same-port#:~:text=Yes.,whichever%20one%20they%20need%20to.
The message you're receiving might imply that the port cannot be occupied by both simultaneously. By showing you plumber and swagger being at 5763.
The docs endpoint is only open for access from the local machine as the url is 127.0.0.1.
The swagger argument is deprecated according to docs https://www.rplumber.io/reference/Plumber.html?q=swagger#method-run-
try with
plumber::plumb("MC_APIv1.1-Prod.R")$run(host = "0.0.0.0", port = 5763, docs="swagger")
or
plumber::plumb("MC_APIv1.1-Prod.R")$set_docs("swagger")$run(host = "0.0.0.0", port = 5763)

jupyterhub fails to spawn server with systemdspawner

I am trying to run jupyterhub on an Ubuntu 20.04 LTS server. My idea is to run python/jupyterhub in a conda virtual environment as a system service. As I want to be able to limit the resources available to individual users I installed the systemdspawner.
After installing everything and starting the jupyterhub service I can login through my web browser. However, when trying to start the server the spawner stucks and after a while I get an error message saying "Spawn failed: Timeout"
in journalctl I can see the following messages:
User logged in: me 302 POST /hub/login?next= -> /hub/spawn (me#::ffff:[my IP address]) 59.42ms
Adding role server to token: <APIToken('93c8...', user='me', client_id='jupyterhub')
Creating oauth client jupyterhub-user-me
pam_loginuid(login:session): Error writing /proc/self/loginuid: Operation not permitted
pam_loginuid(login:session): set_loginuid failed
pam_unix(login:session): session opened for user me by (uid=0)
Failed to open PAM session for me: [PAM Error 14] Cannot make/remove an entry for the specified session
Disabling PAM sessions from now on. user:me
Unit jupyter-me-singleuser in a failed state. Resetting state.
Disclaimer: My Jupyter/Python installation is replacing an former installation that was setup by someone else and got messed up a bit during time. I tried to remove everything related and start with a clean installation from scratch. However, as I had very little documentation about the old setup there is a certain risk that there might be some left-overs of the previous installation that may cause trouble.
Any ideas?
Solved it out myself. In the end the PAM related messages seem to be non-critical and were not related to the timeout at all. Instead I found a mistake in /etc/systemd/system/jupyterhub.service, where the PATH variable was not including the bin directory of my miniconda installation.

Installing a package from private GitLab server on Windows

I am struggling with installing a package from a GitLab repository on a Windows computer.
I found different hints but still have problems to install my package from GitLab. First of all, I generated a public and private key with puttygen.exe. The files need to be changed afterwards, I had to remove comments and stuff so they look like my the file on my Unix system. So now, both public and private key files have just a single line.
I tried to install my package via devtools::install_git which takes very long and I get the error message
Error: Failed to install 'unknown package' from Git:
Error in 'git2r_remote_ls': Failed to authenticate SSH session: Unable to send userauth-publickey request
And with devtools::install_gitlab I get a different error message and I somehow have the feeling, the link which gets generated doesn't fit to my GitLab server.
Error: Failed to install 'unknown package' from GitLab:
cannot open URL 'https://gitlab.rlp.net/api/v4/projects/madejung%2FMQqueue.git/repository/files/DESCRIPTION/raw?ref=master'
My complete code to test at the moment is
creds <- git2r::cred_ssh_key(publickey="~/.ssh/id_rsa_gitlab.pub",
privatekey="~/.ssh/id_rsa_gitlab")
devtools::install_git(
url='git#gitlab.rlp.net:madejung/MQqueue.git',
quiet=FALSE,
credentials=creds)
devtools::install_gitlab(
repo='madejung/MQqueue.git',
host='gitlab.rlp.net',
quiet=FALSE,
credentials=creds
)
My id_rsa_gitlab.pub file looks like this and is just a single line:
ssh-rsa AAAA....fiwbw== rsa-key-20200121
The id_rsa_gitlab file has just the code:
AAABA.....3WNSIAGE=
Update
On my Mac system it works as expected after installing the libssh2 library via homebrew and and recompiling git2r with install.packages("git2r", type = "source").
So the working code on my machine is:
creds <- git2r::cred_ssh_key(publickey="~/.ssh/id_rsa_gitlab.rlp.net.pub",
privatekey="~/.ssh/id_rsa_gitlab.rlp.net")
devtools::install_git(
url='git#gitlab.rlp.net:madejung/MQqueue.git',
quiet=FALSE,
credentials=creds
)
For some strange reason, the devtools::install_git call needs about a minute to fail in the end. I have no idea where the problem here is.
After struggling for almost a day, I found a solution I can live with...
I first created a PAT (Personal Access Token) in my gitlab account and granted full API access. For some reason the read_only access didn't worked and I am now tired to figure out what the problem is.
After this I had still problems to install my package and for some reason, the wininet setting for downloading doesn't work.
I used the command capabilities("libcurl") to check if libcurl is available on my windows, which was and tried to overwrite wininet to libcurl by using method='libcurl' in the install function. Somehow, this was not enough so I overwrote the options variable download.file.method directly.
options("download.file.method"='libcurl')
devtools::install_gitlab(
repo='madejung/MQqueue',
auth_token='Ho...SOMETHING...xugzb',
host='gitlab.rlp.net',
quiet=FALSE, force=TRUE
)

install.keras() in RStudio fails with http connection error

I've been trying to install and run keras in RStudio (Windows) in vain.
i installed keras package using normal package "keras"
(didn't use github)
I've installed latest python (3.6) and Anaconda.
then i use
> library(keras)
> install.keras()
and i get this error:
Creating r-tensorflow conda environment for TensorFlow installation...
Fetching package metadata ... CondaHTTPError: HTTP 000 CONNECTION
FAILED for url
https://repo.continuum.io/pkgs/main/win-64/repodata.json.bz2
Elapsed: -
An HTTP error occurred when trying to retrieve this URL. HTTP errors
are often intermittent, and a simple retry will get you on your way.
ConnectTimeout(MaxRetryError("HTTPSConnectionPool(host='repo.continuum.io',
port=443): Max retries exceeded with url:
/pkgs/main/win-64/repodata.json.bz2 (Caused by
ConnectTimeoutError(, 'Connection to repo.continuum.io timed out.
(connect timeout=9.15)'))",),)
Error: Error 1 occurred creating conda environment r-tensorflow In
addition: Warning message: running command
'"C:\PROGRA~3\ANACON~1\Scripts\conda.exe" "create" "--yes" "--name"
"r-tensorflow" "python=3.6"' had status 1
I've looked up everywhere on the web and can't figure out how to install keras and tensorflow properly. Using latest version of R (3.4.2)
Every method fails somewhere.
just to add to misery, i've also tried:
> devtools::install_github("rstudio/keras")
and i get this error:
Installation failed: Timeout was reached: Connection timed out after
10015 milliseconds
I am not behind any authenticated proxies. So, after multiple failure, i just downloaded the zip file from github and manually installed it using the zip file.
i also tried install.packages("keras") and that didn't give me any error either.
when i call the library i don't get any errors (as shown above)
UPDATE: I was able to install and use the package very easily on another computer that doesn't have python/anaconda installed on it already.
UPDATE 2: my proxy does not need authentication and there is no https_proxy either.
OK,, FINALLY found a solution.
Turns out RStudio uses a lot of default proxy settings, so i needed to change all that and set up my own proxy settings.
First step:
Rstudio --> Tools --> Global Options --> packages --> uncheck both "Use secure download method for HTTP" and "Use Internet Explorer librayr/proxy for HTTP"
Second step, in RStudio type:
> file.edit('./.Renviron')
Either an empty file or some file with already existing proxy settings will open. (Mine was empty). Then I included the following two:
http_proxy=http://myusename:password#proxy.server.com:port/
https_proxy=http://myusename:password#proxy.server.com:port/
(a few notes: I didn't have a https_proxy setting but I still needed to use the http_proxy details for my https_proxy setting. This was one of the culprits for my issue. Also, I needed to include the username:password even though my proxy doesn't need secure authentication. Same thing goes with the port. Port number had to be included, otherwise it wouldn't work.
Step 3:
Saved the new changes in .Renviron file and restarted RStudio.
I checked my proxy settings in RStudio after restart by typing:
> Sys.getenv("http_proxy")
> Sys.getenv("https_proxy")
The first few times i did this i realised that the proxy settings were not being changed in RStudio because i was editing the wrong .Renviron file. So, it's best to use file.edit('~/.Renviron') in step 2 to make sure it's the right file.
After all this, when i ran install.keras(), it installed successfully, including installing Tensorflow. Again, initially i had skipped step 1 so keras started being installed but it failed at installing tensorflow.
It was only going through all the steps that i was able to install both keras and tensorflow successfully over a proxy. Hope this helps.
Uninstalling Anaconda3 and installing Anaconda2 (i.e. Python 2.7) did the trick for me: https://www.anaconda.com/download/

OpenCPU admin opencpu.demo

I am recieveing an error when I run the
admin app on my OpenCPU Server
Error Message :
Not Found
The requested URL /Radmin/call/opencpu.demo/install.opencpu/json was not found on this server.
I have the R folder of the opencpu repo and the package installed yet I dont know where the install.opencpu function file is
I'm not sure where you found the /Radmin/ url, but that feature never made it into opencpu. Try to stick with the stuff from the manual page: www.opencpu.org.

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