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Interface section and minor fixes
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.DS_Store | ||
.venv/ | ||
.vscode | ||
site/ |
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# Using the Jupiter Notebook Interface | ||
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![Screenshot](img/tabs.png) | ||
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The Jupyter notebooks are easy to use yet powerful. The interface, for example, allows to: | ||
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* Easily navigate the **file system**, to create, upload, download and manage files and directories. | ||
* Have multiple tabs, that can be arranged and *snapped* to a corner, to a side, bottom or top of the "snapping area". | ||
* Tabs can be: | ||
* One or more **terminal** tabs, to run commands and scripts. | ||
* One or more **notebook** tabs, to write and run code, and to create and manage documents. | ||
* One or more **text editor** tabs, to write and edit text files. You can directly edit the text (and save it) from the interface. | ||
* Built in preview for HTML files (for example, MultiQC reports), tables (csv, tsv, etc.), and images. | ||
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The interface consists of four main components: | ||
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![Notebook panel](img/tabs2.png) | ||
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1. The **menu bar**, where you can access settings (including font size etc.), and manage the notebook. | ||
2. The side bar will allow you to select the appropriate side tab. | ||
3. The **side area**, which is by default set to the **File Browser**. From here you can navigate directories and upload/download files. You can quickly upload a file by dragging it from your computer and dropping it in the file browser. | ||
1. Right-clicking to a file will allow you to download it, rename it, or to "open it" with the appropriate application. | ||
4. The **snapping tabs area**, where you can place all your open tabs, and arrange them as you like. | ||
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## Common tasks | ||
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### Quickly upload some files to the Notebook | ||
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1. Use the side bar (File Browser) to navigate to the appropriate location. Remember that your home directory is not a safe place for storage, and that you should use the `shared-team` directory for your data. | ||
2. If appropriate, create a new sub directory (e.g. right click in the white area of the file browser and select "New Folder", then type a name for it) | ||
3. On your local computer, open the directory with the files you want to upload. | ||
4. Drag the files from your local computer and drop them in the file browser of the notebook interface. | ||
5. If the file size is relevant you will get a warning. For very large uploads, you should consider using the S3 storage instead. | ||
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### Edit a file and save it | ||
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1. Use the side bar (File Browser) to navigate to the appropriate location. | ||
2. Some files will open in an editor automatically, otherwise right click on the file and select **"Open with" -> "Editor"**. | ||
3. When you edit the file, a dot (⚫️) will appear in the tab, indicating that the file has been modified. | ||
4. Use `Ctrl + S` to save the file (or `Cmd + S` on macOS), or click the save button in the editor. | ||
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### Live preview of a (supported) file | ||
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1. Use the side bar (File Browser) to navigate to the appropriate location. | ||
2. Right click on the file and select **"Open with" -> "Editor"**. | ||
3. Now right-click again on the file and select **"Open with" -> "CSV Previe"** (or other supported preview: like Markdown, HTML...). | ||
4. When you edit and **save** the file with the editor, the preview will update automatically. | ||
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💡 You can use a similar arrangement to keep, for example, a script editor on your left and a terminal to run the script on your right. | ||
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### Using the Python notebook with custom libraries | ||
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1. Open a terminal tab. | ||
2. Create a new environment with the requested libraries plus `ipykernel`, using `conda create -n EnvName ... ipykernel`. Suppose you want to create an environment called `dataexplorer` with Pandas, Seaborn, and Matplotlib, you would use `conda create -n dataexplorer pandas seaborn matplotlib ipykernel`. | ||
3. Open the launcher, and you will see a new icon with the environment name under the Python Icon. Click on it to create a new notebook with the new environment. | ||
4. From that notebook you will be able to `import pandas as pd`, for example. | ||
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See: [Using Jupyter](using-jupyter.md) for more details. |
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