DataSpell 2022.2

Adds Visual Merge for Jupyter Notebooks, UX enhancements for working with cells and WSL support.
September 21, 2022 - 9:52
New Version

Features

  • Editor
    • New actions on the toolbar for copy-pasting cells - 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.
    • Resizable image outputs - With this release, you can resize image outputs by simply dragging their bottom borders.
  • Console
    • Convenient display of text outputs in the Python console - Text outputs in the Python console are now displayed directly under their respective inputs, which makes them easier to read.
  • Microsoft Windows Subsystem for Linux (WSL)
    • Support for WSL interpreter in venv - With this release, 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.
  • VCS
    • Merge view for Jupyter notebooks - It is now easy to decide which changes should be merged in Jupyter notebooks. With this release you are able to see the changes to be merged, including ones made to plots, in a human-readable way.
  • Database Management
    • Playground and Script resolve modes - Added two resolve modes for your SQL scripts in this release. 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.
    • Import multiple CSV files - Added the ability to import multiple CSVs into new or existing database tables.
    • Basic DB support for DuckDB, Mimer SQL and Apache Ignite - Added 3 new databases to the basic support list: DuckDB, Mimer SQL, and Apache Ignite.
  • Copy-paste directories between the local machine and the remote Jupyter server - You can now copy-paste both files and directories from your local machine to remote Jupyter servers, and vice versa.
  • Markdown and HTML tables - The Jupyter notebook editor in DataSpell allows you to create and edit both Markdown and HTML tables in Markdown cells. With this release, the way these tables are rendered, as well as the look of the tables that are displayed in interactive outputs has been significantly improved.
  • Python interpreter selector - DataSpell has an Interpreter selector in the bottom right-hand corner of the IDE that helps you see and change the Python interpreter you are currently working with. In this release an Interpreter selector is also sensitive to the context of the Workspace tool window, so it is easy to see which interpreter is used for each directory directly from the Workspace tool window. You can change the interpreter via the context menu in the Workspace tool window.
  • Code completion for pandas.DataFrame - The pandas package is a cornerstone for exploratory data analysis, but writing pandas code can be a cumbersome task. To simplify it, DataSpell provides code completion and code insight for the pandas package, the same way it does for other libraries. With this release, autocompletion for lambdas inside pandas functions has been improved. Completion results now include the list of dataframe columns, just like they do for many other types of pandas-related code.
  • Update on working with external Jupyter notebooks - Reworked the way DataSpell handles metadata from Jupyter notebooks. The Git history now stays clean when you edit notebooks created elsewhere.
New actions on the toolbar for copy-pasting cells

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