We start by creating a folder on named kafka-jupyter and navigating to it. Using Docker allows us to focus on learning without having to deal with software installation and configuration: a big win for productivity. ![]() ![]() JupyterLab can be started as Docker container. With JupyterLab it provides a solid web interface where it's possible to create and distribute notebooks written in a variety of languages (named kernels in Jupyter terms). One of the main actors in the notebook space is the Jupyter project. Language support and multi-window GUI: the case for JupyterLab If you want to browse a full ready-made solution instead, check out our dedicated github repository. This blog post aims to teach you the basics of Apache Kafka Producers and Consumers through building an interactive notebook in Python. Notebooks represent an excellence in this field by allowing people to share and use pre-built content which includes written descriptions, media and executable code in a single page. One of the best ways to learn a new technology is to try it within an assisted environment that anybody can replicate and get working within few minutes.
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