FAQ - RWTHjupyter
- Yes, we currently provide each user container with a maximum of 64 GiB RAM, 32 CPU cores and a 4 GiB of persistent storage space for your home directory.
last changed on 09/08/2023
How did this content help you?
- Please consult the Terms of Use for details.
last changed on 09/08/2023
How did this content help you?
This is only possible to a limited extent. We encourage all instructors and professors to apply for a customized profile for their course.
Students who wish to use RWTHjupyter outside of their courses should use one of the generic kernel profiles. These generic profiles can be customized by installation of additional packages via pip and conda. By default, added packages are not persistent and only available until the next spawn of your Jupyter container. As a workaround, packages can be installed in your home directory:
pip install --user pandas You can also add this line into a Jupyter Notebook cell by prefixing it with an exclamation mark:
!pip install --user pandas It is currently not possible to load custom conda environemnts.
last changed on 09/08/2023
How did this content help you?
Please visit the following site and select your profile to trigger a new build of the Docker image which is used to spawn single user containers:
- Note: You need to hold the manager role of the profile which you want to rebuild. Please contact us, if you dont have the role yet.
last changed on 09/08/2023
How did this content help you?
- Please have a look at the following dedicated page: Shared Folders
last changed on 09/08/2023
How did this content help you?
- Please have a look at the following dedicated page: Links
last changed on 09/08/2023
How did this content help you?
- Yes. Please use the RWTH Partner-Manager to sponsor a RWTH partner account.
- You can then share your Jupyter Notebooks with your external partners.
- Partner accounts can access RWTHjupyter but might have reduced privileges and/or priorities.
last changed on 09/08/2023
How did this content help you?
- Please have a look at the following dedicated page: Links
last changed on 09/08/2023
How did this content help you?
- We host most of our code, configuration and more on the RWTH GitLab instance.
- Please feel free to contribute by submitting merge requests.
- We are also looking for HiWi's to support us in improving this service. Feel free to get in touch with us.
last changed on 09/08/2023
How did this content help you?
- The RWTHjupyter infrastructure was created in collaboration between the Institute for Automation of Complex Power Systems (ACS) and the IT Center of RWTH Aachen University.
last changed on 09/08/2023
How did this content help you?
- We use a Jupyter extension called nbgitpuller to sync Jupyter Notebooks. nbgitpuller uses an "automatic merging behaviour" to sync changes between your local home directory and the upstream Git repo. Please consult the nbgitpuller documentation for details about this merging behaviour.
last changed on 09/08/2023
How did this content help you?
- Currently, GPUs are only available to selected courses. Please contact us if you wish to use GPU resources.
last changed on 09/08/2023
How did this content help you?
- When creating the Git repository, it is important to note that users only have a quota of 4GiB at their disposal.
- Large files should therefore be avoided. If this is not possible, please ask your profile request to create a folder with the required data in our dataset share.
This share can be accessed by all users and serves to optimize storage usage so that not every student needs all datasets in their home directory.
last changed on 07/18/2024
How did this content help you?