Do you want to take your knowledge in Python to the next level? We’ve collected all the best tutorials you need to do it. Learn how to build a WhatsApp Chatbot, how to code music recommendations like Spotify, dive into Domain Driven Design Patterns, Data Analysis, and much more! Don’t be left out of the hype, jump into Python and watch these tutorials to become a Pro.
Ever wonder if your WhatsApp was a bot that could perform automatic tasks such as sending birthday messages at exactly midnight or even more, sending you reminders about your day-to-day tasks? In this talk, you will learn how to create your own WhatsApp chatbot that can help you set and receive daily reminders via WhatsApp. We will make use of the Twilio’s WhatsApp API for communication, Python for development, Google Sheets as a database, and Heroku for deployment. Overall, you will understand a wide range of Python packages, such as Flask, gspread, APScheduler, datetime, pytz and many more.
Can simple open-source tools compete with the music recommendations provided by Spotify and other big names? This talk will look at how the open-source world can stay relevant in a world where music listening has become dependent on commercial streaming services and users expect an element of recommendations. Expect to see small-tech solutions for music recommendations based around GNOME’s Tracker search engine and the open, community-powered database Musicbrainz.
Domain-Driven Design (DDD) is an approach to software development that emphasizes high-fidelity modeling of the problem domain, and which uses a software implementation of the domain model as a foundation for system design. This approach helps organize and minimize the essential complexity of your software. DDD has been used with success within the traditional enterprise programming ecosystems of Java and .NET, but has seen only limited adoption in the Python community. In this talk Robert introduces Python programmers to the core tactical patterns of DDD and shows how they can be realized in idiomatic Python, freeing the most valuable parts of your system – the domain model – from onerous dependencies on particular databases or application frameworks.
This talk will cover different steps involved in getting a dataset ready for fitting a machine learning model using Python.
Unit tests are great, but they don’t catch all bugs because they don’t test features as a user. In addition, Web UI tests are complicated and notoriously unreliable. So, how can you write tests well? Never fear! Let’s learn how to write robust, scalable Web UI tests using Python, pytest, and Selenium WebDriver that cover the full stack for any Web app. You’ll learn how to write battle-hardened Web UI tests for any Web app, including Django and Flask apps.