Topic Archive

Data

  • From SQL to SQLModel: A Cleaner Way to Work with Databases in Python

    Ahmed Lemine

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    17 min read

    SQLModel is a library that lets you interact with databases through Python code with Python objects and type annotations instead of writing direct SQL queries. Created by the same author of the extremely popular framework FastAPI, it aims to make interacting with SQL DBs in Python easier and elegant, with data validation and IDE support, without the need to learn SQL. It’s an ORM (Object-Relational Mapper), meaning: it translates between classes/objects and SQL. In this article, I will cover why you would use SQLModel over plain SQL queries, what benefits it brings to the table and the basics of using…

  • NLP Made Easy: How We Prioritize Exercise Improvements with a Few Lines of Code

    Bob Belderbos

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    5 min read

    We highly appreciate user feedback for continuous improvement. With hundreds of Bite exercises and thousands of reviews, it’s easy to get overwhelmed by the data. 😱 How do you uncover insights from this sea of feedback? Use code! 😎 Enter TextBlob, a Python library that abstracts away the complexities of Natural Language Processing (NLP). This article walks you through a practical example: analyzing the sentiment of Bite reviews to identify which exercises need the most immediate attention and which ones delight people the most (perhaps to highlight these more on social media …) Using TextBlob alongside SQLAlchemy’s automap feature, we’ll…

  • A Practical Example of the Pipeline Pattern in Python

    Juan José Expósito González

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    5 min read

    What is this pattern about? The Pipeline design pattern (also known as Chain of Command pattern) is a flexible way to handle a sequence of actions, where each handler in the chain processes the input data and passes it to the next handler. This pattern is commonly used in scenarios involving data processing, web scraping, or middleware systems. In this blog post, I’ll walk you through a specific example that leverages Python’s powerful functools.reduce and partial functions, along with the BeautifulSoup library for parsing HTML content. This code showcases the Pipeline pattern applied to HTML table extraction and processing. What…

  • OpenStreetMap, Overpass API and Python

    Judith Vockenroth

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    7 min read

    OpenStreetMap (OSM) is known for being an open source project that allows people to browse the world map and to plan routes. However it is more than that. Among others it provides a read-only API that allows users to query for very diverse map data: Overpass API Data structure of OSM To understand the structure of the queries, we first need to understand how OSM saves its data. OSM uses basic data structures: node, way, and relation. Each element can have multiple tags, which consist of a key-value pair and they help specify the features of each element. Nodes also…

  • Using Python in Excel with PyXLL

    PyBites Team

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    1 min read

    In this podcast episode we talk with Tony Roberts, creator of PyXLL (pronounced “pixel”).  Listen here: Also released on our YouTube channel: We dive into the backstory of this Python Excel Add-in, why he built it, features, success stories, the business side of things, and also how it compares to Microsoft’s recently announced Python in Excel integration. And of course as always there are wins + books 🎉 Get ready for the fascinating world of Python + Excel integration … Chapters:00:00 Intro snippet and music00:44 Guest intro and background02:40 Wins of the week05:06 PyXLL backstory08:50 Market validation10:44 Main features and…

  • Meet Will Raphaelson: From Script to Production Flow With Prefect & Marvin AI

    PyBites Team

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    1 min read

    This week Robin Beer – one of our coaches – interviews Will Raphaelson, Principal Product Manager at Prefect. 😍 They talk about his use of Python, Prefect as a tool and its philosophy, open source + business and Marvin AI. 🐍 💪 And of course they share cool wins and books they are reading. 💡 All in all an insightful chat that hopefully will leave you inspired to go check out these cool new Python tools … 😎 Listen here: Or watch on YouTube: Chapters:00:00 Intro snippet00:11 Intro music00:31 Introduction guests + topics01:32 Welcome Will, do you have a win…

  • Making plots in your terminal with plotext

    Bob Belderbos

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    2 min read

    In this blog post a quick script to plot the frequency of our blog articles in the terminal. It’s good to see that we’re getting back on track 🙂 The code gist is here. First we import the libraries we are going to use. As always we separate Standard Library modules from 3rd party ones as per PEP8: Then I define some constants: I defined a year month generator. Why? Because some months we have not posted, yet I still want to show them on the graph. Then the wokhorse function that calculates the amount of posts per month. We…

  • Data engineering involves more Python than you might think!

    PyBites Team

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    1 min read

    Listen here: This week we have Christo back on the show to talk about his experience in the data engineering field. He shares some valuable tips how to become a more effective data engineer which, surprisingly or not, increasingly requires a well-rounded Python developer skill set. Enjoy and feel free to reach out to Christo below … Christo’s website: https://www.christoolivier.com Christo is a PDM coach now, check it out: https://pybit.es/catalogue/the-pdm-program/Previous episode Christo was on:https://www.pybitespodcast.com/1501156/8005574-013-the-mindset-of-a-developerHe is also in our Slack community:http://pybit.es/community/

  • Case study: How to parse nested JSON

    Michael Aydinbas

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    10 min read

    I was asked to help parse a JSON file that is delivered by the iTunes Store Customer Reviews API JSON endpoint. It is not so important how this API works or if there are better APIs for this. Instead, let’s assume that we found our favorite API to work with and that our request makes perfect sense and now we have to deal with the API’s response, JSON in this case. This article will guide you through the necessary steps to parse this JSON response into a pandas DataFrame. I will focus heavily on the concepts and code development and…