DataSpell 2023.1: Support for Multiple Projects with Separate Environments, Notebook Productivity Boosters, and DataFrame Enhancements
DataSpell now enables you to organize your work into multiple, completely separate projects, each of which has its own virtual environment or Python interpreter.
Select the Projects option in the left pane of DataSpell’s Welcome screen to see the list of existing projects, open these projects, or create a new project. You can also create and manage projects from the File menu.
Alternatively, you can continue to use a single workspace with attached directories. The environment or interpreter configured for the workspace is inherited by the directories and projects you attach to the workspace by default.
To use DataSpell with a workspace, select the Quick Start option in the left pane of the Welcome screen, configure a default environment, and click Launch DataSpell.
Switching back and forth between Jupyter Notebooks and Python scripts is a common workflow in data science. You can now convert a Jupyter Notebook (.ipynb file) to a Python script (.py file) and vice versa in just a few clicks.
Since Jupyter Notebook cells are often executed out of order and some run for a long time, both the last time a code cell was executed and the duration of the execution are now displayed directly below the cell.
The ineffective code completion provided by Jupyter Notebooks has been disabled. Instead, enjoy new and improved DataFrame column name completion, autocompletion for dynamic classes, path completion for remote Jupyter servers, and more.
Several improvements are available for Markdown cells in Jupyter Notebooks and Markdown files, including an intention action to correct the formatting of tables, the Fill Paragraph editor action to break up long texts, and a Smart Keys settings page for Markdown files.
Creating a pandas DataFrame from the data in a CSV file is a common data science task. Drag and drop a CSV (.csv file) into a Jupyter Notebook and a pandas DataFrame will be automatically created from the contents of the file.
DataSpell displays the contents of pandas DataFrames in tabular form. To browse large DataFrame tables more comfortably, update the number of rows displayed per page to your preferred page size using the Change Default dialog.
The Python Packages tool window is the quickest way to manage packages and preview package documentation for a particular environment or Python interpreter. You can find it in the lower group of tool windows or open it from the main menu: Window | Tool Windows | Python Packages.
The interactive debug console can be used to send commands to the Jupyter Debugger and view outputs and error messages while debugging Jupyter Notebook cells.
You can add a new Python interpreter directly from the interpreter widget in DataSpell’s status bar. Open the widget, select the relevant directory, and then a popup will open with an option to add a new interpreter.
Visit this page to learn more about the new UI.
In 2022, JetBrains introduced a new UI for its IDEs designed to reduce visual complexity, provide easy access to essential features, and progressively disclose complex functionality.
The new UI has a simplified main toolbar, a new tool window layout, an updated icon set, new light and dark color themes, and more.
Enable the new UI via Settings/Preferences | Appearance & Behavior | New UI.