Buckle up, Guys. Jupyter Notebook version 5.3.0 is here!
Jupyter Notebook, the popular language-agnostic HTML notebook application for Project Jupyter, is now available in version 5.3.0. The Notebook is an open-source web application for creating and sharing documents that contain live code, equations, visualizations and narrative text. It can be used for data cleaning and transformation, data visualization, and machine learning to name a few.
The new version includes a myriad of bug fixes and changes, most notably terminal support for Windows. It also includes support for OS trash. So now the files deleted from the notebook dashboard are moved to the OS trash as opposed to being deleted permanently. Other changes include:
- A restart and run all button to the toolbar.
- Programmatic copy to clipboard is now allowed.
- DOM History API can be used for navigating between directories in the file browser.
- Translated files can now be added to folder(docs-translations).
- Token-authenticated requests cross-origin allowed by default.
- A “close” button is displayed on load notebook error.
- Action is added to command palette to run CodeMirror’s indentAuto on selection.
- A new option is added to specify extra services.
- Shutdown trans loss is now fixed.
- Finding available kernelspecs is now more efficient.
- The new version uses requirejs vs. require.
- It also fixes some ui bugs in firefox.
- It can now compare non-specific language code when choosing to use arabic numerals.
- Save-script deprecation is fixed.
- Moment locales in package_data are now included.
- The new version now has Use /files prefix for pdf-like files.
- The feature of adding a folder for document translation is now available.
- Users can now set the password, when login-in via token.
Other minor changes can be found in the changelog.
Users can upgrade to the latest release by pip install notebook –upgrade or conda upgrade notebook.
It is recommended to upgrade to version 9+ of pip before upgrading notebook.
|Fun Fact: Jupyter is a loose acronym meaning Julia, Python, and R. These programming languages were the first target languages of the Jupyter application, but nowadays, the notebook also supports many other languages.|