The terminal facilitates working with the command console, while the database tools help you access and query databases from the IDE. Version control allows you to manage your Git projects, commits and changes like a professional. Version control, a terminal and database toolsĪside from the particularities above, JetBrains DataSpell comes with features that are usually available in major IDEs, such as version control, a built-in terminal and database tools. It comes with support for all the standard Jupyter shortcuts and generates interactive outputs, while the IDE allows code completion and quick error checking to ease your work. You can initiate connections to local Jupyter notebooks or remote ones, to JupyterLab and JupyterHub.ĭataSpell allows you to work with both the command mode and the editor mode. One of its most noticeable features is the Jupyter integration. Support for local and remote Jupyter notebooks Python scripts can be split into code cells and run separately like in Jupyter, while the built-in Python console displays the output in real-time. Working with Python scripts in JetBrains DataSpell allows you to access all the Python scientific libraries. ![]() Whether you work with Python scripts or access Jupyter notebooks, you will enjoy a development environment with line numbering, code completion, smart suggestions and syntax highlighting. It features debugging tools, a dataset and virtualization explorer, a package manager and reliable coding assistance.Īs you might expect from a JetBrains products, the IDE features an elegant look, with a generous editing area. JetBrains DataSpell relies on the Python interpreter, while providing support for Conda, Markdown and the R language. Compatible with Python and other languages ![]() The JetBrains team prides itself in creating an ergonomic environment where users can take advantage of the smart coding tools in P圜harm and the interactive Jupyter notebooks. This new IDE brings to the table functionality that is meant to streamline exploratory data analysis and machine learning. We invite you to get in touch with us on Twitter or Slack and encourage you to post your bug reports in our bug tracker.Rising up to the standards set by its developer, JetBrains DataSpell provides an integrated development environment that can cater to the needs and requirements of professional data scientists. Lastly, when cloning a repo from Git or launching a new Jupyter server, DataSpell will now suggest a better default path inside the DataSpell Projects directory where you can store it. You can also triple-click to select the last line in a cell. The outputs and cell boundaries will not be. ![]() When selecting text in a cell, only the text itself will be highlighted. We improved the text selection experience in the DataSpell Jupyter notebook. ![]() To easily find necessary files in your workspace, you can adjust the appearance of the workspace tree for remote Jupyter notebooks – sorting it by type or setting it to display folders always on top.ĭataSpell now implements the Contents API, allowing you to use non-default Jupyter storage backends like s3contents. We also fixed a number of bugs in Jupyter remote servers so the overall experience is now more fluid. You can now connect to Jupyter servers that have paths in their URLs – a setup that is quite common from self-hosted servers to supercomputers. When there are multiple outputs, they will now appear without delay, and outputs will no longer be resized on text selection. You can download the build from the website, update via the Toolbox App, apply a patch (go to DataSpell | Check for Updates), or use a snap package (for Ubuntu).įor Jupyter notebooks, we concentrated on multiple issues involving the display of cell outputs. With DataSpell 2022.1.1, we have worked hard to improve the overall DataSpell user experience.
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