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Python Programming

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  • Python API Tutorial: Getting Started with APIs

    In this tutorial on working with APIs using Python, we’ll learn how to retrieve data for data science projects. There are millions of APIs online which provide access to data. Websites like Reddit, Twitter, and Facebook all offer certain data through their APIs.

    To use an API, you make a request to a remote web server, and retrieve the data you need.

  • Performance of numpy and pandas - comparison

    There seems to be no data science in Python without numpy and pandas. (This is also one of the reason why Python has become so popular in Data Science). However, dumping the libraries on the data is rarely going to guarantee the peformance. So what’s wrong?

  • Conveying Build and Test Information with Repository Badges

    When you check out a repository on github, sometimes theres a little bit of flare at the top of the project that catches your eye.

    This bit of flare is called a badge and can be used to indicate build status, test coverage, documentation generation status, version support, software compatibilty statements or even community links to gitter or discord where you can find more help with the project.

    I used to think that badges were fancy fluff people added to their projects to make them seem more professional. But after working with them in my own projects and experiencing their usefulness, my opinion has changed slightly. I now think of them as fancy fluff that adds useful info and functionality. They can work with any software project, be it a small webapp, to even a collection of multi-stage microservices.

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