{"id":8304,"date":"2021-03-31T11:19:39","date_gmt":"2021-03-31T19:19:39","guid":{"rendered":"https:\/\/devblogs.microsoft.com\/python\/?p=8304"},"modified":"2021-03-31T11:19:39","modified_gmt":"2021-03-31T19:19:39","slug":"jupyter-in-visual-studio-code-april-2021-release","status":"publish","type":"post","link":"https:\/\/devblogs.microsoft.com\/python\/jupyter-in-visual-studio-code-april-2021-release\/","title":{"rendered":"Jupyter in Visual Studio Code \u2013 April 2021 Release"},"content":{"rendered":"

We are pleased to announce that the\u00a0April\u00a02021\u00a0release of the\u00a0Jupyter\u00a0Extension for Visual Studio Code is now available.\u00a0If working with Python,\u00a0we recommend\u00a0installing the\u00a0<\/span>Python extension<\/span><\/a> directly from the extension gallery in Visual Studio Code. If you already have the Python or Jupyter extensions installed, you can also get the latest update by restarting Visual Studio Code. You can learn more about\u202f<\/span>Python support in Visual Studio Code<\/span><\/a>\u202fin the documentation.\u00a0<\/span>\u00a0<\/span><\/p>\n

This release of the Jupyter Extension includes an overhaul and new functionality of the Data Viewer, as well as some UI enhancements and multiselect support for Native Notebooks. <\/span>\u00a0<\/span><\/p>\n

If you\u2019re interested, you can check the\u00a0<\/span>full list of improvements in\u00a0our\u00a0<\/span>changelog<\/span><\/a>.<\/span>\u00a0<\/span><\/p>\n

Data Viewer Enhancements<\/span><\/span>\u00a0<\/span><\/h2>\n

\"Upgraded<\/a><\/p>\n

We\u2019ve added many improvements to our Data Viewer in the latest release. Firstly, we have added the ability to refresh the Data Viewer. If you\u2019ve made some changes or transformations to your data, rather than having to close and reopen the Data Viewer to view the changes, you can now click the refresh button in the top left to grab the most up-to-date data.<\/span>\u00a0<\/span><\/p>\n

Secondly, the\u00a0Data\u00a0Viewer now supports\u00a0viewing\u00a0both\u00a0PyTorch\u00a0and TensorFlow Tensor data types!<\/span>\u00a0<\/span><\/p>\n

Finally, we\u2019ve given the entire\u00a0Data\u00a0Viewer UI a visual update to make it\u00a0more aesthetically\u00a0pleasing. You can now find\u00a0the\u00a0filter box at the heading of each column.\u00a0You can also continue to click on any\u00a0column heading to sort\u00a0its\u00a0data ascending\/descending.\u00a0Lastly, you can now click into\u00a0individual\u00a0cells\u00a0in the Data Viewer\u00a0to copy out\u00a0their\u00a0contents.<\/span>\u00a0<\/span><\/p>\n

Data Slicing<\/span><\/span>\u00a0<\/span><\/h2>\n

\"Data<\/a><\/p>\n

The\u00a0<\/span>D<\/span>ata\u00a0<\/span>V<\/span>iewer now has support for slicing data.\u00a0<\/span>This will allow you to view any 2D slice of your higher dimensional data.\u00a0<\/span>If you have 3-dimensional\u00a0<\/span>or greater\u00a0<\/span>data<\/span>\u00a0(<\/span>numpy<\/span>\u00a0<\/span>ndarray<\/span>,\u00a0<\/span>PyTorch<\/span>\u00a0Tensor or TensorFlow\u00a0<\/span>EagerTensor<\/span>\u00a0types)<\/span>,\u00a0<\/span>you will now be able to view\u00a0<\/span>that\u00a0<\/span>multi-dimensional data in the Data Viewer and\u00a0<\/span>a new data\u00a0<\/span>slicing panel\u00a0<\/span>will open in the\u00a0<\/span>D<\/span>ata\u00a0<\/span>V<\/span>iewer by default<\/span>. In this panel, you will be able to either use\u00a0<\/span>an<\/span>\u00a0input box to programmatically specify your slice\u00a0<\/span>using Python slice syntax\u00a0<\/span>or use the\u00a0<\/span>interactive\u00a0<\/span>Axis and Index dropdowns to\u00a0<\/span>slice as well. Both will be in sync.<\/span>\u00a0<\/span><\/span>\u00a0<\/span><\/p>\n

VS Code Insiders \u2013 Native Notebooks<\/span><\/span><\/h2>\n

To try out Native Notebooks you\u00a0<\/span>need to download\u00a0<\/span><\/span>VS Code Insiders<\/span><\/span><\/a>\u00a0and\u00a0<\/span>make sure you have the\u00a0<\/span>Jupyter<\/span>\u00a0extension! Reminder that the Python extension comes with the\u00a0<\/span>Jupyter<\/span>\u00a0extension and when working with Python we recommend having both installed for the best Python experience.\u00a0<\/span><\/span>\u00a0<\/span><\/p>\n

Multiple Cell Selection is Here!\u00a0<\/span>\u00a0<\/span><\/h3>\n

Jupyter\u00a0Notebooks now have\u00a0support for selecting multiple\u00a0consecutive\u00a0cells using the mouse (Shift + Click) or the keyboard shortcut\u00a0(Shift + Arrow) when in cell selection mode.\u00a0<\/span>\u00a0<\/span><\/p>\n

\"Multiselect<\/a><\/p>\n

You can also select individual cells using the mouse\u00a0<\/span>(Ctrl + Click).\u00a0<\/span><\/span>\u00a0<\/span><\/p>\n

\"Multiselect<\/a><\/p>\n

Once the cells are selected, you can copy\/cut\/paste\/duplicate and even move selected cells by dragging and dropping them to your preferred location.\u00a0<\/span><\/span>\u00a0<\/span><\/p>\n

\"Moving<\/a><\/p>\n

Quick Collapse<\/span>\u00a0<\/span><\/h3>\n

You\u2019ll no longer need to\u00a0open the overflow menu in the cell toolbar\u00a0to collapse cell inputs or outputs! Simply hover over to the\u00a0left\u00a0of each cell and\u00a0double-click in order to collapse the elements of your cell.\u00a0<\/span> To reveal collapsed content, just click the collapsed icon as shown below.\u00a0<\/span><\/p>\n

\"Quick<\/a><\/p>\n

Customizable Diffing Experience<\/span>\u00a0<\/span><\/h3>\n

Users can now customize the type of information that is surfaced when diffing notebooks\u00a0and have the option to hide metadata and output differences!\u00a0 To customize your filters, simply open the overflow menu located in the top right of the rich diff text editor and select the sections on the notebook you would like included!\u00a0<\/span>\u00a0<\/span><\/p>\n

\"Customizable<\/a><\/p>\n

Other Changes and Enhancements<\/span>\u00a0<\/span><\/h2>\n

We have also added small enhancements and fixed issues requested by users that should improve your experience working with\u00a0Notebooks\u00a0in Visual Studio Code. Some notable changes include:<\/span>\u00a0<\/span><\/p>\n