Helix/bwVisu/JupyterLab - Revision history

S Fischer: icons looks different now

2026-08-18T08:41:23Z

icons looks different now

← Older revision		Revision as of 10:41, 18 August 2026
Line 55:		Line 55:

	<ol style="list-style-type: decimal;">		<ol style="list-style-type: decimal;">
	<li>Load the miniforge module by clicking first on the ~~blue~~ hexagon icon on the left-hand side of Jupyter's start page and then on the "load" button right of the entry for miniforge in the software module menu.		<li>Load the miniforge module by clicking first on the double hexagon icon on the left-hand side of Jupyter's start page and then on the "load" button right of the entry for miniforge in the software module menu.
	<li>Open a terminal.</li>		<li>Open a terminal.</li>
	<li>Create a new virtual environment:		<li>Create a new virtual environment:
Line 140:		Line 140:

	<ol><li>'''How can I use bwForCluster Helix software modules?'''</br>		<ol><li>'''How can I use bwForCluster Helix software modules?'''</br>
	First click on the ~~blue~~ hexagon icon on the left-hand side of Jupyter's start page. Then load a module by clicking on the "load" button next to the corresponding module entry.</li>		First click on the double hexagon icon on the left-hand side of Jupyter's start page. Then load a module by clicking on the "load" button next to the corresponding module entry.</li>
	<li>'''My virtual environment works on Helix but not in the bwVisu JupyterLab job.'''</br>		<li>'''My virtual environment works on Helix but not in the bwVisu JupyterLab job.'''</br>
	If the environment uses Helix modules, you have to load the modules in the bwVisu job first. For example, when you used the python 3.13 module for creating the environment, the path to this python version is saved in the environment. When the module is not loadedin bwVisu, the path is not available and you might get an error like "''[...]/bin/python: error while loading shared libraries: libpython3.13.so.1.0: cannot open shared object file: No such file or directory''"</li>		If the environment uses Helix modules, you have to load the modules in the bwVisu job first. For example, when you used the python 3.13 module for creating the environment, the path to this python version is saved in the environment. When the module is not loadedin bwVisu, the path is not available and you might get an error like "''[...]/bin/python: error while loading shared libraries: libpython3.13.so.1.0: cannot open shared object file: No such file or directory''"</li>

S Fischer: Typo

2026-08-18T08:34:05Z

Typo

← Older revision		Revision as of 10:34, 18 August 2026
Line 22:		Line 22:
	#*:[[File:BwVisu JuypterLab KernelPath.png\|In the JupyterLab job configuration form, a custom kernel path can be provided.\|right\|thumb\|x150px]]		#*:[[File:BwVisu JuypterLab KernelPath.png\|In the JupyterLab job configuration form, a custom kernel path can be provided.\|right\|thumb\|x150px]]
	#* If the kernel is saved somewhere else, the path can be provided in the "Kernel path" field when configuring the JupyterLab job (see image). For a kernel placed under <code>path_to_parent_dir/share/jupyter/kernels/my_kernel</code> the needed "Kernel path" would be <code>path_to_parent_dir/share/jupyter</code>.		#* If the kernel is saved somewhere else, the path can be provided in the "Kernel path" field when configuring the JupyterLab job (see image). For a kernel placed under <code>path_to_parent_dir/share/jupyter/kernels/my_kernel</code> the needed "Kernel path" would be <code>path_to_parent_dir/share/jupyter</code>.
	# When the kernel is used the first time, the file <code>notebook_secrets</code> is created automatically. It can be found under "Kernel path". For others to use the kernel, they must have read access to this file. The command <code>chmod 750 notebook_secrets</code> would for example allow the whole SDS@hd SV read access. For the access management in workspaces, please see [[Workspace#Setting_Permissions_for_Sharing_Files\| ~~Wokspace~~ Permissions]].		# When the kernel is used the first time, the file <code>notebook_secrets</code> is created automatically. It can be found under "Kernel path". For others to use the kernel, they must have read access to this file. The command <code>chmod 750 notebook_secrets</code> would for example allow the whole SDS@hd SV read access. For the access management in workspaces, please see [[Workspace#Setting_Permissions_for_Sharing_Files\| Workspace Permissions]].

	<u>Notes regarding the sharing of IPython kernels</u>		<u>Notes regarding the sharing of IPython kernels</u>

H Schumacher: Added hint to load modules first.

2026-05-07T14:32:03Z

Added hint to load modules first.

← Older revision		Revision as of 16:32, 7 May 2026
Line 141:		Line 141:
	<ol><li>'''How can I use bwForCluster Helix software modules?'''</br>		<ol><li>'''How can I use bwForCluster Helix software modules?'''</br>
	First click on the blue hexagon icon on the left-hand side of Jupyter's start page. Then load a module by clicking on the "load" button next to the corresponding module entry.</li>		First click on the blue hexagon icon on the left-hand side of Jupyter's start page. Then load a module by clicking on the "load" button next to the corresponding module entry.</li>
			<li>'''My virtual environment works on Helix but not in the bwVisu JupyterLab job.'''</br>
			If the environment uses Helix modules, you have to load the modules in the bwVisu job first. For example, when you used the python 3.13 module for creating the environment, the path to this python version is saved in the environment. When the module is not loadedin bwVisu, the path is not available and you might get an error like "''[...]/bin/python: error while loading shared libraries: libpython3.13.so.1.0: cannot open shared object file: No such file or directory''"</li>
	<li>'''How can I navigate to my SDS@hd folder in the file browser?'''</br>		<li>'''How can I navigate to my SDS@hd folder in the file browser?'''</br>
			Please see the instructions at the [[Helix/bwVisu/Usage#Files \| Usage]] page.</li>
	Open a terminal and set a symbolic link to your SDS@hd folder in your home directory. For example:</li>
	<pre>cd $HOME
	mkdir sds-hd
	cd sds-hd
	ln -s /mnt/sds-hd/sd16a001 sd16a001</pre>
	<li>'''I prefer VSCode over JupyterLab. Can I start a JupyterLab job and then connect with it via VSCode?'''</br>		<li>'''I prefer VSCode over JupyterLab. Can I start a JupyterLab job and then connect with it via VSCode?'''</br>
	This is not possible. Please start the job directly on Helix instead. You can find the instructions at the [[Development/VS_Code#Connect_to_Remote_Jupyter_Kernel \| VSCode page]].</li>		This is not possible. Please start the job directly on Helix instead. You can find the instructions at the [[Development/VS_Code#Connect_to_Remote_Jupyter_Kernel \| VSCode page]].</li>

H Schumacher: Added instructions for using Helix modules

2026-05-05T11:24:22Z

Added instructions for using Helix modules

← Older revision		Revision as of 13:24, 5 May 2026
Line 139:		Line 139:
	== FAQ ==		== FAQ ==

	<ol><li>'''My ~~conda~~ ~~commands~~ ~~are~~ ~~interrupted~~ ~~with~~ ~~message~~ ~~'Killed'.~~'''</br>		<ol><li>'''How can I use bwForCluster Helix software modules?'''</br>
			First click on the blue hexagon icon on the left-hand side of Jupyter's start page. Then load a module by clicking on the "load" button next to the corresponding module entry.</li>
⚫	Request more memory when starting Jupyter.</li>
	<li>'''How can I navigate to my SDS@hd folder in the file browser?'''</br>		<li>'''How can I navigate to my SDS@hd folder in the file browser?'''</br>
	Open a terminal and set a symbolic link to your SDS@hd folder in your home directory. For example:</li>		Open a terminal and set a symbolic link to your SDS@hd folder in your home directory. For example:</li>
Line 147:		Line 147:
	cd sds-hd		cd sds-hd
	ln -s /mnt/sds-hd/sd16a001 sd16a001</pre>		ln -s /mnt/sds-hd/sd16a001 sd16a001</pre>
⚫	<li>'''Jupyterlab doesn't let me in but asks for a password.'''</br>
⚫	Try using more memory for the job. If this doesn't help, try using the inkognito mode of your browser as the browser cache might be the problem.</li>
	<li>'''I prefer VSCode over JupyterLab. Can I start a JupyterLab job and then connect with it via VSCode?'''</br>		<li>'''I prefer VSCode over JupyterLab. Can I start a JupyterLab job and then connect with it via VSCode?'''</br>
	This is not possible. Please start the job directly on Helix instead. You can find the instructions at the [[Development/VS_Code#Connect_to_Remote_Jupyter_Kernel \| VSCode page]].</li>		This is not possible. Please start the job directly on Helix instead. You can find the instructions at the [[Development/VS_Code#Connect_to_Remote_Jupyter_Kernel \| VSCode page]].</li>
			<li>'''My conda commands are interrupted with message 'Killed'.'''</br>
		⚫	Request more memory when starting Jupyter.</li>
		⚫	<li>'''Jupyterlab doesn't let me in but asks for a password.'''</br>
		⚫	Try using more memory for the job. If this doesn't help, try using the inkognito mode of your browser as the browser cache might be the problem.</li>
	</ol>		</ol>

H Schumacher: fix for pip installations in shared envs

2026-03-19T09:33:23Z

fix for pip installations in shared envs

← Older revision		Revision as of 11:33, 19 March 2026
Line 43:		Line 43:
	<syntaxhighlight lang="bash">source <env_parent_dir>/<env_name>/bin/activate</syntaxhighlight></li>		<syntaxhighlight lang="bash">source <env_parent_dir>/<env_name>/bin/activate</syntaxhighlight></li>
	<li>Update pip and install packages:		<li>Update pip and install packages:
	<syntaxhighlight lang="bash">pip install -U pip		<syntaxhighlight lang="bash">pip install -U pip --no-user
			# when the environment is installed in home
⚫	pip install <packagename></syntaxhighlight></li>
			pip install <packagename>
			# when the environment is installed somewhere else and shall not have dependencies in home so that others can access it as well
		⚫	pip install <packagename> --no-user</syntaxhighlight></li>
	<li> [[#Create_an_IPython_Kernel \| Create an IPython kernel]]</li>		<li> [[#Create_an_IPython_Kernel \| Create an IPython kernel]]</li>
	</ol>		</ol>

H Schumacher: Added fourth step to the kernel sharing instructions to fix permission issues.

2026-03-02T15:02:00Z

Added fourth step to the kernel sharing instructions to fix permission issues.

← Older revision		Revision as of 17:02, 2 March 2026
Line 20:		Line 20:
	# Use the kernel within JupyterLab		# Use the kernel within JupyterLab
	#* By default new kernels are saved under <code>~/.local/share/jupyter</code> and this location is automatically detected. Therefore, new kernels are directly available.		#* By default new kernels are saved under <code>~/.local/share/jupyter</code> and this location is automatically detected. Therefore, new kernels are directly available.
	[[File:BwVisu JuypterLab KernelPath.png\|In the JupyterLab job configuration form, a custom kernel path can be provided.\|right\|thumb\|x150px]]		#*:[[File:BwVisu JuypterLab KernelPath.png\|In the JupyterLab job configuration form, a custom kernel path can be provided.\|right\|thumb\|x150px]]
	#* If the kernel is saved somewhere else, the path can be provided in the "Kernel path" field when configuring the JupyterLab job (see image). For a kernel placed under <code>path_to_parent_dir/share/jupyter/kernels/my_kernel</code> the needed path would be <code>path_to_parent_dir/share/jupyter</code>.		#* If the kernel is saved somewhere else, the path can be provided in the "Kernel path" field when configuring the JupyterLab job (see image). For a kernel placed under <code>path_to_parent_dir/share/jupyter/kernels/my_kernel</code> the needed "Kernel path" would be <code>path_to_parent_dir/share/jupyter</code>.
			# When the kernel is used the first time, the file <code>notebook_secrets</code> is created automatically. It can be found under "Kernel path". For others to use the kernel, they must have read access to this file. The command <code>chmod 750 notebook_secrets</code> would for example allow the whole SDS@hd SV read access. For the access management in workspaces, please see [[Workspace#Setting_Permissions_for_Sharing_Files\| Wokspace Permissions]].

	<u>Notes regarding the sharing of IPython kernels</u>		<u>Notes regarding the sharing of IPython kernels</u>

H Schumacher: fix typo

2026-01-16T15:34:15Z

fix typo

← Older revision		Revision as of 17:34, 16 January 2026
Line 17:		Line 17:
	#* [[#Add_packages_via_Conda_virtual_environments \| ...conda]] (choose this option if you want to install a different python version) or		#* [[#Add_packages_via_Conda_virtual_environments \| ...conda]] (choose this option if you want to install a different python version) or
	#* ...[https://docs.astral.sh/uv/getting-started/ uv] if you want to install a different python version but don't want to use conda.		#* ...[https://docs.astral.sh/uv/getting-started/ uv] if you want to install a different python version but don't want to use conda.
	# [[#~~Create_an_IPython_kernel~~ \| Create an IPython kernel]] from the virtual environment		# [[#Create_an_IPython_Kernel \| Create an IPython kernel]] from the virtual environment
	# Use the kernel within JupyterLab		# Use the kernel within JupyterLab
	#* By default new kernels are saved under <code>~/.local/share/jupyter</code> and this location is automatically detected. Therefore, new kernels are directly available.		#* By default new kernels are saved under <code>~/.local/share/jupyter</code> and this location is automatically detected. Therefore, new kernels are directly available.
Line 44:		Line 44:
	<syntaxhighlight lang="bash">pip install -U pip		<syntaxhighlight lang="bash">pip install -U pip
	pip install <packagename></syntaxhighlight></li>		pip install <packagename></syntaxhighlight></li>
	<li> [[#~~Create_an_IPython_kernel~~ \| Create an IPython kernel]]</li>		<li> [[#Create_an_IPython_Kernel \| Create an IPython kernel]]</li>
	</ol>		</ol>

Line 64:		Line 64:
	<li>Install your packages:		<li>Install your packages:
	<syntaxhighlight lang="bash">conda install <mypackage></syntaxhighlight></li>		<syntaxhighlight lang="bash">conda install <mypackage></syntaxhighlight></li>
	<li> [[#~~Create_an_IPython_kernel~~ \| Create an IPython kernel]]</li>		<li> [[#Create_an_IPython_Kernel \| Create an IPython kernel]]</li>
	</ol>		</ol>

H Schumacher: Added image for kernel path option (based on user feedback)

2025-11-23T17:55:11Z

Added image for kernel path option (based on user feedback)

← Older revision		Revision as of 19:55, 23 November 2025
Line 20:		Line 20:
	# Use the kernel within JupyterLab		# Use the kernel within JupyterLab
	#* By default new kernels are saved under <code>~/.local/share/jupyter</code> and this location is automatically detected. Therefore, new kernels are directly available.		#* By default new kernels are saved under <code>~/.local/share/jupyter</code> and this location is automatically detected. Therefore, new kernels are directly available.
			[[File:BwVisu JuypterLab KernelPath.png\|In the JupyterLab job configuration form, a custom kernel path can be provided.\|right\|thumb\|x150px]]
	#* If the kernel is saved somewhere else, the path can be provided in the "Kernel path" field when ~~submitting~~ the job. For a kernel placed under <code>path_to_parent_dir/share/jupyter/kernels/my_kernel</code> the needed path would be <code>path_to_parent_dir/share/jupyter</code>.		#* If the kernel is saved somewhere else, the path can be provided in the "Kernel path" field when configuring the JupyterLab job (see image). For a kernel placed under <code>path_to_parent_dir/share/jupyter/kernels/my_kernel</code> the needed path would be <code>path_to_parent_dir/share/jupyter</code>.

	<u>Notes regarding the sharing of IPython kernels</u>		<u>Notes regarding the sharing of IPython kernels</u>

H Schumacher: fixed kernel path

2025-09-12T12:49:00Z

fixed kernel path

← Older revision		Revision as of 14:49, 12 September 2025
Line 20:		Line 20:
	# Use the kernel within JupyterLab		# Use the kernel within JupyterLab
	#* By default new kernels are saved under <code>~/.local/share/jupyter</code> and this location is automatically detected. Therefore, new kernels are directly available.		#* By default new kernels are saved under <code>~/.local/share/jupyter</code> and this location is automatically detected. Therefore, new kernels are directly available.
	#* If the kernel is saved somewhere else, the path can be provided in the "Kernel path" field when submitting the job. For a kernel placed under <code>path_to_parent_dir/share/jupyter/kernels/my_kernel</code> the needed path would be <code>path_to_parent_dir</code>.		#* If the kernel is saved somewhere else, the path can be provided in the "Kernel path" field when submitting the job. For a kernel placed under <code>path_to_parent_dir/share/jupyter/kernels/my_kernel</code> the needed path would be <code>path_to_parent_dir/share/jupyter</code>.

	<u>Notes regarding the sharing of IPython kernels</u>		<u>Notes regarding the sharing of IPython kernels</u>

H Schumacher: Restructured page, improved explanation for sharing virtual environments

2025-08-28T18:38:43Z

Restructured page, improved explanation for sharing virtual environments

Show changes