{"metadata":{"image":[],"title":"","description":""},"api":{"url":"","auth":"required","results":{"codes":[]},"settings":"","params":[]},"next":{"description":"","pages":[]},"title":"JupyterLab quick reference","type":"basic","slug":"editor-quick-reference","excerpt":"","body":"JupyterLab is one of the two available editors in Data Cruncher, where the actual code editing and execution takes place. This document provides a brief description of the JupyterLab environment and its commonly used commands. If your preferred editor is RStudio, please see the [RStudio quick reference](doc:rstudio-quick-reference).\n\n## The interface\n\nWhen you open JupyterLab, you see the Launcher screen that allows you to select one of the available options:\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/0620a68-jupyterlab-quick-reference-1.png\",\n        \"jupyterlab-quick-reference-1.png\",\n        695,\n        845,\n        \"#f5f5f5\"\n      ]\n    }\n  ]\n}\n[/block]\nChoose one of the options in the **Notebook** section, depending on the programming language you want to use.\n\nThe editor screen showing a notebook and a terminal console open at the same time will look like this:\n[block:image]\n{\n  \"images\": [\n    {\n      \"image\": [\n        \"https://files.readme.io/e814fc4-editor-quick-reference-1a.png\",\n        \"editor-quick-reference-1a.png\",\n        1435,\n        693,\n        \"#b5b1ab\"\n      ]\n    }\n  ]\n}\n[/block]\nThe main elements of the editor are:\n1. **Notebook** - The document that contains the code and outputs of an interactive analysis, as well as additional markdown or raw text that accompanies the code, but is not meant for execution.\n\n2. **Cell** - A single section of a notebook where you can enter code, markdown or raw text.\n\n3. **Toolbar** - Allows you to quickly perform the most common actions within a notebook, by clicking on an icon:\n * <img src=\"https://files.readme.io/519377b-save.png\" width=\"auto\" align=\"inline\" style=\"margin:1px\"/> Saves the current content of the notebook.\n * <img src=\"https://files.readme.io/2af6e1f-add.png\" width=\"auto\" align=\"inline\" style=\"margin:1px\"/> Adds a new cell below the selected one.\n * <img src=\"https://files.readme.io/f84c5cc-cut.png\" width=\"auto\" align=\"inline\" style=\"margin:1px\"/> Cuts the currently selected cell(s).\n * <img src=\"https://files.readme.io/64e7f6b-copy.png\" width=\"auto\" align=\"inline\" style=\"margin:1px\"/> Copies the currently selected cell(s).\n * <img src=\"https://files.readme.io/9bcbfde-paste.png\" width=\"auto\" align=\"inline\" style=\"margin:1px\"/> Pastes the copied cell(s).\n * <img src=\"https://files.readme.io/463bd79-run.png\" width=\"auto\" align=\"inline\" style=\"margin:1px\"/> Executes the code in the current cell and moves to the next cell.\n * <img src=\"https://files.readme.io/6ddbef9-stop.png\" width=\"auto\" align=\"inline\" style=\"margin:1px\"/> Stops the execution.\n * <img src=\"https://files.readme.io/a8c41ca-reload.png\" width=\"auto\" align=\"inline\" style=\"margin:1px\"/> Restarts the kernel.\n * <img src=\"https://files.readme.io/6957353-type.png\" width=\"auto\" align=\"inline\" style=\"margin:1px; border: 1px solid #000;\"/> Defines the cell type. Can be **code**, **markdown** or **raw**.\n\n4. Left-hand panel with the following tabs:\n * **Files** - Displays files that are created or added (uploaded or downloaded) within the analysis itself, including the Jupyter notebooks (**.ipynb** files). These files are also known as **analysis files**. To save a file to the project within which the analysis is being executed, right-click it and selecting **Save To Project**. The files that are saved to the project will be available under the **Files** tab in the project dashboard.\n * **Project Files** - Lists all files from the project in which you are executing your analysis. To use a project file in your analysis, you need to reference it in the code using its full path. Clicking a file in the list will copy the path to the clipboard, which you can then paste in your code.\n * **Running** - Displays the kernel sessions that are currently running. One kernel session corresponds to one open notebook.\n * **Commands** - Shows a list of commands that can be used within the editor, along with their keyboard shortcuts. To execute a command, click it in the list.\n5. **Terminal console** - This is a JupyterLab Terminal extension equivalent to a Linux shell.\n6. **Code console** - Enables you to run code interactively in a kernel.\n7. Analysis control buttons:\n * **Stop Analysis** - Allows you to stop the analysis directly from the editor.\n * **Go To Analysis** - Takes you to the analysis details page.\n\n## Commonly used text commands\n\nBesides execution of Python, R or Julia code, you can also run the following types of commands directly in your notebook:\n\n* **Magic commands** - a set of predefined functions that you can call with a command line style syntax. Magic commands can begin with a single `%` symbol, in which case they take the rest of the line as an argument. If you prefix a magic command with a double `%` symbol (`%%`), it will take the rest of the cell as its argument. Learn more about [magic commands](http://ipython.readthedocs.io/en/stable/interactive/magics.html) or type `%magic` in a blank cell and execute it.\n* **Linux shell commands** - You can also run any system shell command by prefixing it with an exclamation mark (`!`), for example `!ls`. You can even combine shell commands with the rest of the code in your notebook, for example:\n[block:code]\n{\n  \"codes\": [\n    {\n      \"code\": \"myfiles = !ls\",\n      \"language\": \"python\"\n    }\n  ]\n}\n[/block]\n This line of code will assign the list of files returned by the `ls` command to the `myfiles` variable.\n\nFind out more about functionalities related to [text commands](http://ipython.readthedocs.io/en/stable/interactive/tutorial.html).","updates":[],"order":2,"isReference":false,"hidden":false,"sync_unique":"","link_url":"","link_external":false,"_id":"594ced741dcef4001c8a8603","project":"5773dcfc255e820e00e1cd4d","version":{"version":"1.0","version_clean":"1.0.0","codename":"","is_stable":true,"is_beta":false,"is_hidden":false,"is_deprecated":false,"categories":["5773dcfc255e820e00e1cd51","5773df36904b0c0e00ef05ff","577baf92451b1e0e006075ac","577bb183b7ee4a0e007c4e8d","577ce77a1cf3cb0e0048e5ea","577d11865fd4de0e00cc3dab","578e62792c3c790e00937597","578f4fd98335ca0e006d5c84","578f5e5c3d04570e00976ebb","57bc35f7531e000e0075d118","57f801b3760f3a1700219ebb","5804d55d1642890f00803623","581c8d55c0dc651900aa9350","589dcf8ba8c63b3b00c3704f","594cebadd8a2f7001b0b53b2","59a562f46a5d8c00238e309a","5a2aa096e25025003c582b58","5a2e79566c771d003ca0acd4","5a3a5166142db90026f24007","5a3a52b5bcc254001c4bf152","5a3a574a2be213002675c6d2","5a3a66bb2be213002675cb73","5a3a6e4854faf60030b63159","5c8a68278e883901341de571","5cb9971e57bf020024523c7b","5cbf1683e2a36d01d5012ecd","5dc15666a4f788004c5fd7d7","5eaff69e844d67003642a020","5eb00899b36ba5002d35b0c1","5eb0172be179b70073dc936e","5eb01b42b36ba5002d35ebba","5eb01f202654a20136813093","5eb918ef149186021c9a76c8","5f0839d3f4b24e005ebbbc29"],"_id":"5773dcfc255e820e00e1cd50","__v":34,"createdAt":"2016-06-29T14:36:44.812Z","releaseDate":"2016-06-29T14:36:44.812Z","project":"5773dcfc255e820e00e1cd4d"},"category":{"sync":{"isSync":false,"url":""},"pages":[],"title":"Data Cruncher","slug":"data-cruncher","order":27,"from_sync":false,"reference":false,"_id":"594cebadd8a2f7001b0b53b2","project":"5773dcfc255e820e00e1cd4d","version":"5773dcfc255e820e00e1cd50","createdAt":"2017-06-23T10:21:33.309Z","__v":0},"user":"575e85ac41c8ba0e00259a44","createdAt":"2017-06-23T10:29:08.653Z","githubsync":"","__v":0,"parentDoc":null}