![]() Executed notebooks can be shared via a number of tools. The nbconvert tool will convert a notebook into various output formats. Jupyter notebook ipynb viewer software#ĭepending on which software packages are installed in the environment, notebooks can be rendered in html, PDF, LaTeX, and other formats. It can also execute a notebook from the command line, without a server running, but it isn’t intended for interactive use. The resulting converted notebooks can be sent to others for viewing using whichever tool they prefer, like a web browser or PDF viewer. The nbviewer web site is another option for sharing notebooks. Think of it as a web based nbconvert tool. Other services (like GitHub)Ī number of services support rendering notebooks as web pages. For example, GitHub will render your notebooks for you if a. ipynb file is a part of a repository that you are browsing. How do you run or execute a Jupyter notebook? For example, I put many of my articles in GitHub, and some of them render right in the browser. OK, enough about viewing notebooks, if we want to actually create new notebooks or execute already created notebooks, what are our options? To work with a notebook, you need a notebook server running. The notebook server will launch the necessary kernel, provide you with a user interface via your web browser (or other authoring tool), and send data back and forth to the kernel for execution. Let’s look at four different options for executing notebooks. Your first option is to run one of the standard Juypyter notebooks servers. You can do this by installing the server in your Python environment, and then running the server and connecting to it via a browser. Jupyter notebook ipynb viewer software#.
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