{"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"],"_id":"5773dcfc255e820e00e1cd50","__v":33,"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":26,"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}

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JupyterLab quick reference

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). ## The interface When you open JupyterLab, you see the Launcher screen that allows you to select one of the available options: [block:image] { "images": [ { "image": [ "https://files.readme.io/0620a68-jupyterlab-quick-reference-1.png", "jupyterlab-quick-reference-1.png", 695, 845, "#f5f5f5" ] } ] } [/block] Choose one of the options in the **Notebook** section, depending on the programming language you want to use. The editor screen showing a notebook and a terminal console open at the same time will look like this: [block:image] { "images": [ { "image": [ "https://files.readme.io/e814fc4-editor-quick-reference-1a.png", "editor-quick-reference-1a.png", 1435, 693, "#b5b1ab" ] } ] } [/block] The main elements of the editor are: 1. **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. 2. **Cell** - A single section of a notebook where you can enter code, markdown or raw text. 3. **Toolbar** - Allows you to quickly perform the most common actions within a notebook, by clicking on an icon: * <img src="https://files.readme.io/519377b-save.png" width="auto" align="inline" style="margin:1px"/> Saves the current content of the notebook. * <img src="https://files.readme.io/2af6e1f-add.png" width="auto" align="inline" style="margin:1px"/> Adds a new cell below the selected one. * <img src="https://files.readme.io/f84c5cc-cut.png" width="auto" align="inline" style="margin:1px"/> Cuts the currently selected cell(s). * <img src="https://files.readme.io/64e7f6b-copy.png" width="auto" align="inline" style="margin:1px"/> Copies the currently selected cell(s). * <img src="https://files.readme.io/9bcbfde-paste.png" width="auto" align="inline" style="margin:1px"/> Pastes the copied cell(s). * <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. * <img src="https://files.readme.io/6ddbef9-stop.png" width="auto" align="inline" style="margin:1px"/> Stops the execution. * <img src="https://files.readme.io/a8c41ca-reload.png" width="auto" align="inline" style="margin:1px"/> Restarts the kernel. * <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**. 4. Left-hand panel with the following tabs: * **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. * **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. * **Running** - Displays the kernel sessions that are currently running. One kernel session corresponds to one open notebook. * **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. 5. **Terminal console** - This is a JupyterLab Terminal extension equivalent to a Linux shell. 6. **Code console** - Enables you to run code interactively in a kernel. 7. Analysis control buttons: * **Stop Analysis** - Allows you to stop the analysis directly from the editor. * **Go To Analysis** - Takes you to the analysis details page. ## Commonly used text commands Besides execution of Python, R or Julia code, you can also run the following types of commands directly in your notebook: * **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. * **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: [block:code] { "codes": [ { "code": "myfiles = !ls", "language": "python" } ] } [/block] This line of code will assign the list of files returned by the `ls` command to the `myfiles` variable. Find out more about functionalities related to [text commands](http://ipython.readthedocs.io/en/stable/interactive/tutorial.html).