Visual Merge for Jupyter Notebook, UX enhancements for working with cells, WSL support.
For both Jupyter Notebook cells and executable cells in your Python files, DataSpell is now equipped with cut, copy, and paste actions right in the editor toolbar. Use them to quickly manage the structure of your Python script or notebook.
With DataSpell 2022.2, you can resize image outputs by simply dragging their bottom borders.
Text outputs in the Python console are now displayed directly under their respective inputs, which makes them easier to read.
With DataSpell 2022.2, you can configure and use Python virtual environments inside the WSL.
You can set up a WSL-based interpreter without leaving the DataSpell workspace window. Just right-click on the attached directory and select Interpreter / Add interpreter. Or set a WSL interpreter by clicking on the Interpreter selector in the interpreter widget. Support for Conda environments in WSL is on the way.
Now it is easy to decide which changes should be merged in Jupyter notebooks.
With DataSpell 2022.2 you are able to see the changes to be merged, including ones made to plots, in a human-readable way. This new visual Merge view is a nice addition to the visual Diff view for Jupyter Notebook, which we introduced in DataSpell 2021.3.
There are two resolve modes for your SQL scripts in DataSpell 2022.2. In
Playground mode, DataSpell resolves objects according to the context
(which is the value in the schema chooser, the resolution scope, or, if neither
of those is set, the default database). In Script mode, the beginning
of the file is resolved to the context, but any
SET CURRENT SCHEMA
statements in the script change the context.
Use the drop-down toolbar to switch between the modes.
DataSpell 2022.2 allows you to import multiple CSVs into new or existing database tables. To do this, select multiple files in Project View and drag and drop them to a database schema or select Import to database from the context menu.
We’ve added 3 new databases to the basic support list: DuckDB, Mimer SQL, and Apache Ignite.