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Python Monthly 💻🐍

Andrei Neagoie
Andrei Neagoie
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19th issue! If you missed the previous ones, you can read the previous issues of my monthly Python newsletter here.

If it’s your first time here… (otherwise, skip this part)

Being a Python developer is a fantastic career option. Python is now the most popular language with lots of growing job demand (especially in the fields of Web, Data Science and Machine Learning). You have many job opportunities, you can work around the world, and you get to solve hard problems.

One thing that is hard, however, is staying up to date with the constantly evolving ecosystem. You want to be a top-performing python developer, coder, programmer, software developer, but you don’t have time to select from hundreds of articles, videos and podcasts each day.

This is the best Python newsletter for you if you want to keep up to date with the industry and keep your skills sharp, without wasting your valuable time.

I curate and share the most important articles, news, resources, podcasts and videos of the month.

Think Tim Ferriss and the Pareto Principle (80/20 rule) meeting the Python world. What’s the 20% that will get you 80% of the results?

Let's dive in. Here's what you missed in June 2021 as a Python Developer…

Bitcoin With Python 💰

Everyone is talking about Bitcoin these days so this is a timely article. In the spirit of “what I cannot create I do not understand”, this article helps you to create, digitally sign, and broadcast a Bitcoin transaction in pure Python, from scratch, and with zero dependencies. In the process you’re going to learn quite a bit about how Bitcoin works.

Nuitka ⚙

This is really cool: Nuitka is a Python compiler written in Python. It's fully compatible with Python 2.6, 2.7, 3.3, 3.4, 3.5, 3.6, 3.7, 3.8, and 3.9. You feed it your Python app, it does a lot of clever things for optimizations, and spits out an executable or extension module.

Weekend Project Idea 🎏

Here is an insane list of 70+ possible Python projects including tutorials and step-by-step code. Pick one of these this weekend and add it to your Github!

FastAPI and Pydantic 🎈

FastAPI, using Pydantic, was included for the first time in the last Python Developer Survey, and despite being the first year in it, it was already ranked as the 3rd most popular web framework, after Flask and Django. This shows that it's being useful for many people. This article covers some important updates and changes. You should also read it to understand why it is becoming more and more popular.

Fullstack Project 🪜

In my opinion, one of the best ways to learn is to see how a full project is built from the ground up and all of the tools/systems in place to make everything work. Check out this article for the breakdown: Detecting deforestation from satellite images. You do not need to fully understand the details, but just the overview of how things are pieced together to build something useful. Enjoy!

Conda All The Way 🐉

When it comes to building for different environments, Conda is the way to go (and it's what we use in our Machine Learning courses here at ZTM). Here is a definitive guide on how to use Conda for virtual environments.

PEP654 🦤

The purpose of this PEP, which is in draft stage, is to help Python users handle unrelated exceptions. Right now, if you're dealing with several unrelated exceptions, you can:

  • Raise one exception and throw away the others, in which case you're losing exceptions
  • Return a list of exceptions instead of raising them, in which case they become error codes rather than exceptions, so you can't handle them with exception-handling mechanisms
  • Wrap the list of exceptions in a wrapper exception and use it as a list of error codes, which still can't be handled with exception-handling mechanisms

PEP 654 proposes:

  • A built-in exception type that wraps other exceptions
  • New syntax with except* to handle exception groups

Pynguin 🐧

Another really cool Python project to check out! Testing software is a tedious task so Pynguin is a tool that allows developers to generate unit tests automatically... sounds too good to be true right? Check it out here.

Gooey 🍯

A lot of cool Python packages in the newsletter this month. This time around, we have Gooey. Turn (almost) any Python command line program into a full GUI application with one line.

Data Science, Python and Excel 🪚

The world of data science is awash in open source: PyTorch, TensorFlow, Python, R, and much more. But the most widely used tool in data science isn’t open source, and it’s usually not even considered a data science tool at all.

It’s Excel, and it’s running on your laptop. Python is the new and better Excel.

The State Of Serverless 🧱♂️

Serverless has gained traction among organizations of all sizes, from cloud-native startups to large enterprises. With serverless, teams can focus on bringing ideas to the market faster — rather than managing infrastructure — all while paying for only what they use. In this report, they examined millions of functions run by thousands of companies to understand how serverless is being used in the real world.

Key takeaways:

  • Azure Functions and Google Cloud Functions are gaining on AWS Lambda
  • Python is the most popular Lambda runtime followed by Node.js
  • Lambda invocations are much shorter today than a year ago

Practical SQL for Data Analysis 💡

Pandas is a very popular tool for data analysis. It comes built-in with many useful features, it's battle tested, and widely accepted. However, Pandas is not always the best tool for the job. Sometimes you want to work directly with SQL. In this article you will learn how to use SQL to perform fast and efficient data analysis.

News Around the World 🗺

Big Tech News 🏢

Completely useless to your career but still great 🙃

Best Resource of the Month 🥽

Do not feed the thought leaders . This was my favourite article from this past month. It contains some valuable lessons. My favourite one was, Ignore Universal Solutions:

"Software development is full of confident forecasters. We are a pretty new field, and yet everyone seems so sure that they have the best solution to whatever problem is at hand. I’d like to hear more people saying things like, “in this specific context, test-coverage seem like an important metric,” or “StopLang is great if you can afford the GC, but if you can’t, then you should look at IronOre.” A great tool is not a universal tool it’s a tool well suited to a specific problem."

Trick of the Month 🎩

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See you next month everyone!

By the way, I teach people how to code and get hired in the most efficient way possible as the Lead Instructor of Zero To Mastery Academy. You can see a few of my courses below or see all ZTM courses here.

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Machine Learning Monthly 💻🤖 preview
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