![]() ![]() Jupyter supports many different programming languages in addition to Python. JupyterLab looks like more complete development environment, giving you also text editor for Python scripts, through-the-browser terminal access, and more.NET Languages in Notebooks With Miniconda, initial distribution is only around 50 Mb, while Anaconda is close to 500 Mb in size.Īfter installing Miniconda, you would need to install Jupyter: While most people recommend Anaconda, which includes a large collection of Python libraries, I would rather start with barebone installation of Python, and install those packages that are really required. The easiest and most compact way to install Python is to use Miniconda distribution. Running Python locally is probably a good idea anyway, because in the modern software development world you are likely to need it at some point. If you work in the area of AI, ML or Data Science, you would probably have Python distribution already installed on your machine. We will consider only free compute options later in this post. However, you do not need to set anything up locally, and can be running the notebook in minutes. In the second case you need to use somebody else’s servers, and that often comes for free with some limited computing abilities, allowing you to purchase more computing power when needed. In first case you keep complete control of the environment and all files, and also of computing resources.
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