PyDo

We're glad to share with you the latest projects we've been working on recently!

ℹ️ Our YouTube channel:
We have never been active on Youtube before, but we're now experimenting with a concept of a weekly short video series that we called "5 Minutes FAUN". We're trying to share as much useful information as possible in a short video. The idea is to be efficient and to the point in each video.

So far, we published around 20 short videos. You can find them here .

These are some series we started so far, more are coming soon:
👉 5 Minutes Golang
👉 5 Minutes Python
👉 5 Minutes DevOps
👉 5 Minutes CloudNative
👉 5 Minutes AI
👉 5 Minutes Kubernetes
👉 5 Minutes Programming
👉 5 Minutes AWS

In less than 2 weeks, we've got:
⭐ 30,000 views
⭐ 500 watch hours
⭐ 200 new subscribers

Some of the most popular videos are:
🔗 Why is Kubernetes Written in Go ?!
🔗 The Real Reason why Go is not so Popular
🔗 Highest Paying Programming Languages
🔗 YAML = Your Abstraction Master Language
🔗 and others!

That's a great start! We're looking forward to growing our Youtube channel and sharing more useful information with you.

Please subscribe to the channel . If there are any topics you'd like us to cover, simply reply to this email or leave a comment on the Youtube channel. We'll do our best to cover them in future videos.


ℹ️ Our Youtube live music stream:
We're also experimenting with a new concept of a live music stream. This month, we launched a new Lo-Fi music live stream on Youtube . Many people listen to this genre of music while coding, so we thought it would be a good idea to create a live stream for our developer community. We're adding new songs to the stream every week.

You can find the stream here .

Are there other music genres you'd like us to stream? Let us know by replying to this tweet .

We're looking forward to growing this stream and sharing more music with you. Please subscribe to the channel. If there are any topics you'd like us to cover, simply reply to this email or leave a comment on the Youtube channel. We'll do our best to cover them in future videos.


ℹ️ FAUN community subreddits:
In addition to the old subreddit /r/DevOpsLinks, we launched multiple others. These subreddits are a place for FAUNers who are also Redditors to share links and start discussions. This is the complete list of the subreddits we have today:

👉 DevOps : /r/DevOpsLinks
👉 CloudNative : /r/CloudNativeLinks
👉 DevSecOps : /r/DevSecOpsLinks
👉 Golang : /r/GolangLinks
👉 Monitoring/Observability : /r/MonitoringLinks
👉 Programming : /r/ProgrammingLinks
👉 Python : /r/PythonLinks
👉 AI/ML : /r/AILinks
👉 Kubernetes : /r/KubernetesLinks

Don't forget to join your favorite subreddits! Let's make them a place to share and discuss the latest news and trends in the DevOps, CloudNative, DevSecOps, Golang, Monitoring, Programming, Python, AI, and Kubernetes ecosystems.

More subreddits are coming soon!

ℹ️ Our coming soon FAUN Topics (Weekly Newsletter):
As you may know, we're working on new weekly FAUN Topics:

👉 Kala: AI Weekly Newsletter.
👉 Secra: Security Weekly Newsletter.

If you'd like to subscribe to these newsletters, head over to FAUN website, click on the top menu, then " Newsletters settings ". You can subscribe to any newsletter you like. You can also unsubscribe from any newsletter you no longer want to receive using the same page.

ℹ️ How to support FAUN?
If you'd like to support FAUN and future projects, you can subscribe or donate here .

Alternatively, follow us on our social media channels, subscribe to our Youtube channel, and share our content with your friends or share your feedback with us by replying to one of our weekly newsletters.

Learn about the platform targets of WebAssembly and how they affect the execution of code. Understand the difference between emscripten and WASI and how they are used as runtime targets for WebAssembly code in the browser and other environments.

This tutorial will walk you through the concept of a platform target triple and its importance in relation to the CPython interpreter and WebAssembly.

The author had experience with a CLI tool written in Bash that was increasingly difficult to maintain and decided to rewrite it in Python for its better readability, testing capabilities, and wider ecosystem of libraries and frameworks.

They chose Typer for building the CLI and Poetry for dependency management and packaging, but over time ran into issues with Poetry such as slow dependency resolution, unexpected updates, and breaking caching when building container images.

The author ultimately decided to switch to a more universal and less complicated alternative, citing James Bennett's "Boring Dependency Management" blog post. They express curiosity about the workflows where Poetry is a better choice, despite their negative experience.

A story describing how the author,Zac Denham, manipulated ChatGPT to get answers on topics the chatbot would never reply to.

It is important to note that while GPT-3 and other language models have the ability to generate a wide variety of text, they do not have the ability to perform actions in the real world.

Python 3.7 is reaching its end of life in June 2023, meaning it will no longer receive security or bug fixes. This can be a concern for those using older versions of Linux distributions that may not include more recent versions of Python.

Upgrading to a more recent version, such as 3.8 or 3.9, is recommended in order to continue receiving updates and security fixes for dependencies. It's important to note that upgrading should not be a one-time event, but an ongoing process.

This tutorial aims to provide an introduction to creating a simple Domain Specific Language (DSL) using Python.

DSLs are specialized programming languages that are used for specific applications or use cases, and can range from complex languages like regular expressions to simple, niche languages like the one we will create in this tutorial.

The tutorial will walk through the process of creating a DSL that allows users to call Python functions and pass arguments to them using a syntax that resembles assembly language.

Meta just released PyTorch 2.0, the latest version of its open-source machine learning framework. Pytorch 2.0 promises 100% backward compatibility. The new feature pushes PyTorch’s performance to new heights and moves some of the components of PyTorch from C++ back into Python.

Amazon SageMaker Feature Store is announcing SageMaker Python SDK support for its offline store. Amazon SageMaker Feature Store is a fully managed, purpose-built repository to store, update, search, and share machine learning (ML) features.

FAUN's Job Board offers an exceptional platform to connect with skilled developers, DevOps professionals, and software engineers who are eager to contribute to the success of your organization.

Post your job openings on FAUN's Job Board today and watch your talent pool grow.

Get started now .

👉 If you're a Developer or a maintainer of a widely adopted Open Source project and you think it's worth talking about it and your experiences in building it, join Humans Behind Code and get interviewed and published on faun.dev!

Meet developers where they are, not where you want them to be. Fill out the form and download our mediakit .

In this video, Federico Cardoso of Hummingbot talks about how to use Python to build high-frequency and market making trading strategies. He also introduces Hummingbot, an open-source tool that helps developers create and run automated trading strategies.

The conference covers topics such as quantitative finance, AI, trading automation, and smart contract development, and is aimed at introducing blockchain development to new developers. The conference has speakers from well-known blockchain organizations such as Ethereum Foundation, Hummingbot, and XRP Ledger.

Learning how to interact and automate with Linux is essential for millions of professionals. Python makes it much easier. With this book, you'll learn how to develop software and solve problems using containers, as well as how to monitor, instrument, load-test, and operationalize your software. Looking for effective ways to "get stuff done" in Python? This is your guide.

• Python foundations, including a brief introduction to the language
• How to automate text, write command-line tools, and automate the filesystem
• Linux utilities, package management, build systems, monitoring and instrumentation, and automated testing
• Cloud computing, infrastructure as code, Kubernetes, and serverless
• Machine learning operations and data engineering from a DevOps perspective
• Building, deploying, and operationalizing a machine learning project

Small Streamlit app to help with background removal on images

Easy and elegant parser combinators for Python. With awesome docs.

Python Random Graph Generator

A unified framework for machine learning with time series

A tool to keep AWS pentests efficient, organized, and stealthy.