quay.io/bgruening/docker-jupyter-notebook:2021-03-05 8888 ipython/lab $__history_id__ $__galaxy_url__ 8080 $__galaxy_url__ jupytool Start with a fresh notebook Load a previous notebook Dataset Multiple datasets Dataset collection Dataset collection (list) Dataset collection (paired) Dataset collection (list:paired) Text Integer Floating point Boolean Color selector Optional Dataset Optional Multiple datasets Optional Dataset collection Optional Dataset collection (list) Optional Dataset collection (paired) Optional Dataset collection (list:paired) Optional Text Optional Integer Optional Floating point Optional Boolean Optional Color selector

Welcome to the **JupyTool**! Here you can create, run, and share custom Galaxy tools based upon Jupyter Notebooks. The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more. Galaxy offers you to use Jupyter Notebooks directly in Galaxy accessing and interacting with Galaxy datasets as you like. A very common use-case is to do the heavy lifting and data reduction steps in Galaxy and the plotting and more `interactive` part on smaller datasets in Jupyter. You can start with a new Jupyter notebook from scratch or load an already existing one, e.g. from your colleague and execute it on your dataset. You can specify any number of user-defined inputs using the repeat input, providing `name` value, selecting the type of input, and then providing values. You can make the JupyTool reusable in a workflow, by allowing the user to specify input values for the defined input blocks. Inputs can be accessed by `name` from the automatically provided `GALAXY_INPUTS` dictionary. Outputs can be written automatically to the user's history by writing to the `outputs` directory for one individual file or to the `outputs/collection` directory for multiple files. Using collection tools, you can parse out the individual elements from the collection, as needed. For backwards compatibility, you can import data into the notebook via a predefined `get()` function and write results back to Galaxy with a `put()` function.