Does anyone know how to set custom.css in for a conda environment?
I created a new environment using
conda create -n myenv
But it doesn't use the same custom.css I created in the default environment.
Any idea where I should put the custom.css file to get Jupyter to use it?
I'm using Windows 7.
See the docs here for info on where paths are located by default (for conda you'd probably be looking at the {sys.prefix}/etc/jupyter path).
Or you could just run jupyter --paths in your conda environment shell to find out where it is looking for custom files.
Related
Problem
I have a conda environment with an R installation. My issue is that the conda R will run ~/.Rprofile during startup. This is breaking the expectation that conda environments are self-contained. Specifically, I am loading packages in my ~/.Rprofile that are not installed in the conda R (I am using require(), so just warnings). The process works the following way:
The first .Rprofile file found on the R startup search path is processed. The search path is (in order): (i) Sys.getenv("R_PROFILE_USER"), (ii) ./.Rprofile, and (iii) ~/.Rprofile. Source: startup package vignette
Goal
Ideally, I would like to alter the third path to a location within the environment directory and somehow do this in the environment yaml during setup, such that I can easily replicate the setup on another device. I realize that this might not work, so a solution that permanently sets R_PROFILE_USER to an environment-specific location would also be appreciated.
Edit:
Since I am using R through rpy2 I don't think I can use the --no-init-file flag.
Quoting from ?.Rprofile, which invokes the man page for Startup,
unless --no-init-file was given, R searches for a user profile, a file
of R code. The path of this file can be specified by the
R_PROFILE_USER environment variable (and tilde expansion will be
performed). If this is unset, a file called ‘.Rprofile’ is searched
for in the current directory or in the user's home directory (in that
order). The user profile file is sourced into the workspace.
I wrote a bash script to solve this issue. Run it in the project directory containing the environment.yml. It prompts for a name of the newly created conda environment, then creates and activates it. Subsequently an empty .Rprofile is created in the environment directory and R_PROFILE_USER is set to this location. Finally, the environment is reactivated for the change to take effect. Thus, any time R is run from this environment, the newly created .Rprofile is used.
It should be noted that an .Rprofile in R_PROFILE_USER takes precedence over an .Rprofile in the project directory. This might lead to confusion if the user wants to create use such a file and is unaware of the setup.
echo What name do you want to give to the conda environment?
read input
conda env create -n $input -f environment.yml
conda activate $input
touch $CONDA_PREFIX/.Rprofile
conda env config vars set R_PROFILE_USER=$CONDA_PREFIX
conda activate $input
I downloaded someone else's project and the structure is as follows:
project/
notebooks/
notebook_a.ipynb
notebook_b.ipynb
library/
Manifest.toml
Project.toml
src/
test/
In the notebooks I would like to import library, and install its dependencies within its own evironment.
Following the sugestions here, I can do
using Pkg
Pkg.activate("../library/")
but I wonder if I could install a kernel that has the project directory specified and automatically activates the library environment. What should I pass to IJulia's installkernel? "--project=..." what?
I use conda regularly and this confused me because I thought that running notebook once the environment is activated in the command line would have the right environment in the notebook, but this was not the case.
IJulia starts its own Julia process and hence is not using environment settings from its master.
By default IJulia sets the environment (Project.toml) from the folder it was started. The most convenient thing would be to move the notebooks folder to be subfolder of library and then just run:
notebook(dir="/path/to/project/library")
If you do not want to change the folder structure you still need to run:
notebook(dir="/path/to/project/notebooks")
Once in the notebook you need to run:
using Pkg
pkg"activate /path/to/project/library"
After seeing this post on how to set the start-up folder for Jupyter Notebooks, I looked for how to do so for specific conda environments and haven't found an answer.
Is there a way to open up a Jupyter notebook in a location that is different depending on which conda environment within which you're activating it? I'm looking for a solution like the one above, where I could change c.NotebookApp.notebook_dir = '/the/path/to/home/folder/', but in some environment-specific config file.
I guess an alternative would be to set some macro to activate the environment, cd to the desired folder location for this environment, then run jupyter notebook from that location.
I was able to generate a DOSKEY macro to do the job. I combined this answer which shows how to set persistent aliases (macros) in command prompt, with this answer which shows how to use multiple separate commands in a DOSKEY macro. As a summary here (mostly from Argyll's answer in the above persistent macro/DOSKEY post):
Create a file called something like alias.cmd
Insert the macro to automatically activate a conda environment, change file locations, and run a jupyter notebook from that location:
doskey start_myEnv = conda activate myEnv $T cd C:\Users\user\path\to\my\notebooks\ $T jupyter notebook
Run regedit and go to HKEY_LOCAL_MACHINE\SOFTWARE\Microsoft\Command Processor
or HKEY_CURRENT_USER\Software\Microsoft\Command Processor if not on Windows 10.
Add a String entry with the name AutoRun with the value set as the full path to the alias.cmd file.
Anytime you open the command prompt, executing start_myEnv will now activate myEnv, change to the folder that relates to that environment, and start a jupyter notebook.
Is there some way to tell jupyter notebook what the default conda env should be when creating new notebooks? Launching it on AWS Deep Learning AMI's gives me a pretty long list, but I really only care about one specific env.
If you go to your terminal first and activate the virtual environment:
$ source venv/bin/activate
or
$ conda activate venv
for conda environment.
And after that step, do the following:
$ jupyter notebook
And when you make a new script it should give you the option for chosing python3/python2, chose the one that solves your purpose. And this script will be using the activated environment. You can check it by importing a libraray specific to that environment.
I use anaconda to install jupyter
Following is my command
$ activate demo ....demo is my environment name
$ conda install jupyter
$ jupyter notebook
and then it will get following error message
[C 10:39:17.591 NotebookApp] Bad config encountered during initialization:
[C 10:39:17.594 NotebookApp] Could not decode 'C:\Users\\xbeG\xa8|\xa5\xe0\.jupyter' for unicode trait 'config_dir' of a NotebookApp instance.
I think my path under C: has chinese, so it can't decode properly.
I also see some similar issue https://github.com/jupyterlab/jupyterlab/issues/5345
but this solution is no help to me, because I use window, I also tried to use
chcp in CMD to change language. It doesn't work too.( I have tried chcp950 ,chcp65001,chcp436)
Are there anyone have idea about my problem?
I also have another problem is that when I conda install jupyter , it seems
to be installed in C: automatically, I want to know are there any method install it to specific path? If it can achieve, I think there is no decode problem because path under D: didn't have chinese.
Thanks all of your help.
my environment:
Python 3.6.5
conda 4.6.11
Not sure if it'll fix your problem but you can install conda packages to a different directory by creating a different environment.
conda create --prefix D:\my_conda python=3.7
activate D:\my_conda
I think you can create .condarc file inside the root of this new conda environment and it'll override the one in your home directory.