5 Packages that Python Devs Use Everyday

As a Python developer, our life lives and revolves around the packages we use. For every problem we have, there is a package in Pypy that would lend its helping hand. Out of them, the following are some of the libraries that developers use every day. These packages are so special that it gets mentioned in almost every interview, there is a rich community around each of them


Anytime someone talks about data manipulation or data analytics, Pandas is your way to go. It has a rich set of features that would help you in the Data Science world and the web world. I have found Pandas almost useful in anything from data transformation to data streaming across various data points.

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The moment you want to build a web application, Flask or Django would be your go-to options. Django comes with many pre-defined modules that get you up and running without a lot of effort. If you have customization and unique functionalities in your web app, flask might be a better option. Both serves it’s purpose well and has rich features


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Another common use case of Python other than building web apps and APIs is consuming existing APIs. Requests library had made it real simple for developers with just 4 key functions. Requests rules the API consumption spectrum of Python despite having urllib in its stdlib

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Pytest is gaining popularity because of its ease of use and makes writing test-cases a pleasurable experience. Just like requests, despite having the unittest built-in in Python library, Pytest has proven to be an efficient and effective way of writing test cases

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SQLAlchemy is one of the richest python packages. Every time a Python developer thinks of databases, they will think of SQLAlchemy. People often think SQLAlchemy is all about ORMs for non-Django people, but that’s not the case. SQLAlchemy provides a developer complete control over how they want to play with DBs. Want to run raw queries? You got it. Want to use a complete object-driven approach? You got it. Got a DB already and want to build on top of it, reflect the DB into objects and proceed

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As a Python Developer, I never start a project without one of these libraries. All the libraries come with rich documentation, so what are you waiting for? Fire up your code editor, pip install, and start experimenting with their examples.