Frequently asked questions¶
On this page:
What is on-premises Notebooks?¶
Jupyter notebooks allow data scientists to explore data, train models, and test hypotheses. Being able to run Jupyter is crucial for data science workflows, but individually configuring Jupyter on every workstation can create headaches around authentication, collaboration, and running big jobs.
On-prem Notebooks, available as an add-on to Anaconda’s on-premises repository (Anaconda Server), solves this problem through centrally-administered Jupyter notebooks. Authentication, shared environments, storage, and access to computing resources are all set up for you during implementation. Additionally, notebooks are automatically configured to use the secure and trusted packages from your Anaconda Server instance, so your users can focus on business needs instead of installation and configuration.
On-prem Notebooks also includes ongoing maintenance and support, ensuring your team gets all the benefits of centralized notebooks without the IT burden of maintaining JupyterHub.
What do I get with on-prem Notebooks?¶
On-prem Notebooks provides you with a method of managing a JupyterHub instance using the tools that power Anaconda Server. You can create and manage groups of users, assign them roles, and supply them with custom channels populated with safe, Anaconda-curated packages, based on their specific needs.
Is on-prem Notebooks different from JupyterHub?¶
On-prem Notebooks is JupyterHub combined with the added authentication, security, and management capabilities of Anaconda Server, all in one centralized location.
How do I access on-prem Notebooks?¶
You can log in to your on-prem Notebooks by using your Anaconda Server credentials. Get the web address for your on-prem Notebooks from your IT administrator. If you do not have Anaconda Server credentials, ask your Anaconda Server administrator.
How do I upload a notebook to the service?¶
In the JupyterLab interface, click Upload files in the File Browser to browse for a local
.ipynb file. Then, click Open. The notebook will appear in the left-hand menu.
You can also drag and drop a notebook from a folder on your system to the file browser to upload it.
How do I save my notebooks?¶
Like most IDEs or editors, JupyterLab has the standard “Save” and “Save As…” functions that saves a notebook in your directory on the remote server. You can also download a notebook file from the File menu to save it locally on the machine where your browser is running.
Where are my packages coming from?¶
The packages available to your JupyterHub users are supplied by your instance of Anaconda Server. If you need any additional packages, you must contact the administrators of your Anaconda Server instance.
Can I upload new packages or create custom environments in Anaconda Notebooks?¶
It is possible to upload packages and environments for your JuypterHub users. For more information, see the official Anaconda Server documentation.
My notebook is trying to import a package, but I’m getting an error¶
The most common cause of errors is a lack of required package(s) installed in your environment. The packages available to you are provided through your Anaconda Server channel. If the packages you need are unavailable, talk to your Anaconda Server administrator to mirror the packages you need to your channel. You must create a custom environment prior to installing packages.
Here are a couple of steps to help resolve this:
Make sure you have the right kernel/environment selected
Separate environments are represented as “kernels” in JupyterLab. You can view and switch between available kernels by clicking the kernel name in the upper-right corner of the content pane.
List the packages available in an environment
You can view which packages are available in your current environment from the terminal by running the
conda list command. If you want to view the packages of a specific environment, run the command
conda list -n <ENV_NAME>. If you need to see a list of available environments, you can run the
conda env list command. An asterisk will appear next to your current active environment.
You can run those commands directly in a code cell within your notebook just by adding a “!” to the front of the command (e.g.
!conda env list).