I’m a PyCharm user and I saw that JetBrains has launched DataSpell, an IDE focused on data science. The setup appears to emphasize conda. I’m accustomed to using pip/venv. Is conda good? Is it great? I’ve never tried it before.
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They are essentially the same thing. Conda manages virtual environments and installs packages. People choose Conda because it comes preconfigured with a large number of important data science tools.
Conda is widely recognized and valued in the data science community for managing packages and environments effectively. Unlike pip and venv, which are specific to Python packages and virtual environments, Conda is a package and environment management tool that supports multiple languages and libraries, making it versatile for data science projects that may involve different dependencies beyond Python. It simplifies the installation and management of complex libraries and dependencies, which can be particularly advantageous when working with data science frameworks like TensorFlow or PyTorch, which often have intricate dependencies. Conda’s ability to manage both Python and non-Python packages in the same environment adds flexibility, but it’s essential to understand its workflow and how it integrates with your development environment, especially if you’re used to pip and venv. Overall, many data scientists find Conda to be a powerful tool that streamlines setup and ensures reproducibility across different computing environments.
Actually not better, but different. Conda manages whole environments, including dependencies, which can be helpful for complex data science projects. Pip/venv are good for simpler projects.
In my experience, Conda tends to be more packaged as a product, at least historically. It typically includes ready-to-run versions of almost everything and offers options to incorporate components outside of Python (like npm) for comprehensive environments.
Moreover, Conda is particularly geared towards facilitating data science tasks, making it the convenient choice for quickly setting up such workflows.