A Walkthrough of the “Complete Machine Learning and Data Science: Zero to Mastery” Course (Part 01)

I'm going through the Udemy course Complete Machine Learning and Data Science: Zero to Mastery. The course runs under the flag of Andrei Neagoie. Andrei is a popular instructor on Udemy, with almost 200.000 students, and top reviews. For this course, he has paired up with Daniel Bourke, a self-taught Machine Learning Engineer from Australia. In this blog post series, I will jot down my thoughts on the course, and what I've learned.
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Trying Out FastAPI

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Friday Picks 033

Here are 5 links for this Friday: How to create a simple REST API with Python and Flask in 5 minutes - a beginner-friendly Python & Flask tutorial What is Phoenix LiveView - a good overview about the new experimental feature in Elixir's web framework For a Good strftime - if you quickly want to look up how to format a string in Python Introduction to CSS - Youtube series about CSS A Recap of Frontend Development in 2019 - what happened in 2019?
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Friday Picks 031

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Month of Testdriven Python and React

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TIL: ASGI for Python

Today I learned about the ASGI specification for Python frameworks: ASGI (Asynchronous Server Gateway Interface) is a spiritual successor to WSGI, intended to provide a standard interface between async-capable Python web servers, frameworks, and applications. Python didn't have asynchronous execution until recently. Since Python 3.4 there's asyncio in the standard library. asyncio is singl-threaded, single-process - like JavaScript's event loop. ASGI is build on top of asyncio. So, basically, Python now has web servers and frameworks with async capacities.
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Flask Is Complicated

I'm currently creating some micro-service applications with Docker and Flask. Python is quite a beginner-friendly language, and Flask is easy to get started with. At the same time, it isn't straightforward to add more than basic features. For example, the tutorials use Flask-RESTful. Adding Swagger-UI to my “standard” Docker image is quite a hassle. You can use flask-swagger-ui, but then you have to figure out how to serve the static json file.
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Friday Picks 030

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2019 Week 50: A Look Back

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Create a Multi-Stage Docker Build for Python Flask and Postgres

A few days ago, I created a Docker build for Flask with PostgreSQL (both with Alpine Linux and with Debian Linux). Installing psypcopg-2 binary (required for Postgres) requires you to build the package from source. Now the Docker image grows in size, as it still contains the build artifacts. The solution? Multi-stage Docker builds. Let's say we have the following docker-compose.yml file. There are two services: a Flask API called users and a Postgres database called users-db.
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