JetBrains DataSpell

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. This new IDE brings to the table functionality that is meant to streamline exploratory data analysis and machine learning. The JetBrains team prides itself in creating an ergonomic environment where users can take advantage of the smart coding tools in PyCharm and the interactive Jupyter notebooks.

JetBrains DataSpell relies on the Python interpreter, while providing support for Conda, Markdown and the R language. It features debugging tools, a dataset and virtualization explorer, a package manager and reliable coding assistance.

As you might expect from a JetBrains products, the IDE features an elegant look, with a generous editing area. 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.

Working with Python scripts in JetBrains DataSpell allows you to access all the Python scientific libraries. 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.

One of its most noticeable features is the Jupyter integration. You can initiate connections to local Jupyter notebooks or remote ones, to JupyterLab and JupyterHub.

DataSpell allows you to work with both the command mode and the editor mode. 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.

Aside 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.

Version control allows you to manage your Git projects, commits and changes like a professional. The terminal facilitates working with the command console, while the database tools help you access and query databases from the IDE.

JetBrains DataSpell was designed to be an IDE oriented towards working with data, while PyCharm is also geared towards development, while also providing data science functionality. In other words, JetBrains DataSpell is suitable for professional data scientists more than developers.