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🔔 Announcement

We're thrilled to announce Humans Behind Code!

Humans Behind Code (HBC) is a project by FAUN, where developers meet other developers and learn about the people behind the tools, libraries, frameworks, and other projects they use to build their applications.

We interview developers and ask them about their projects, their motivations, their struggles, and their successes. It's about sharing knowledge and helping each other grow.

👉 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!

Best,
Aymen from FAUN.

If you have any questions, just hit the reply button!

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Funnel analysis is a way for businesses to analyze the chain of events that customers traverse through on their way to completing a desired goal of the business.

For example, say we run an online store. For any user that visits our site, they can also view items, add items to their cart, and purchase items from their cart.

In this case, visits, items viewed, items added to the cart, and items purchased are all milestones within the chain of events leading up to a successful purchase.

As a business, our primary goal is to maximize the number of purchases per customer. Funnel analysis can help us understand what factors might be preventing customers from reaching this final step in the process.

See how to perform tracking user events, actions, and drop-offs using Python.

There are plenty of ways to measure the speed of your code. Writing Faster Python series showcases some of them.

Trying out the Rust programming ecosystem as a 10+ years Python developer. How to do common programming tasks and how the tooling looks like.

Inline caching is a technique to make programs run faster. It stores information about what has been run before so it can be run faster the next time.

This post is about the inline caching implementation in Skybison, a relatively complete Python 3.8 runtime originally developed for use in Instagram.

It nicely showcases all of the fun and sharp edges of the Python object model and how you can solve hard problems.

In short, you can now write Python code directly into your HTML code, and the Python code will run in your browser.

This opens up lots of possibilities for creating cool things in Python that can be used in your browser.

Python 3.9.x and 3.10.x through 3.10.8 on Linux allows local privilege escalation in a non-default configuration.

• The Python multiprocessing library, when used with the forkserver start method on Linux, allows pickles to be deserialized from any user in the same machine local network namespace, which in many system configurations means any user on the same machine.
• Pickles can execute arbitrary code. Thus, this allows for local user privilege escalation to the user that any forkserver process is running as.
• Setting multiprocessing.util.abstract_sockets_supported to False is a workaround.
• The forkserver start method for multiprocessing is not the default start method.
• This issue is Linux-specific because only Linux supports abstract namespace sockets.

Python 3.12.0a2 is released with new features and bug fixes.

• Modules from the standard library are now potentially suggested as part of the error messages displayed by the interpreter when a NameError is raised to the top level.
• The new version improves the error suggestion for NameError exceptions for instances.
• It adds Python support for the Linux perf profiler through the new environment variable PYTHONPERFSUPPORT, the new command-line option -X perf, as well as the new sys.activate_stack_trampoline(), sys.deactivate_stack_trampoline(), and sys.is_stack_trampoline_active() APIs.
• It improves modules such as asyncio, array, pathlib, dis, os, shutil, sqlite3, sys and threading.
• The team deprecated typing.Hashable and typing.Sized aliases for collections.abc.Hashable and collections.abc.Sized and made other depreciations.
• Previously deprecated APIs and modules will be removed in 3.13.

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.

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GALACTICA is a general-purpose scientific language model.

It is trained on a large corpus of scientific text and data. It can perform scientific NLP tasks at a high level, as well as tasks such as citation prediction, mathematical reasoning, molecular property prediction and protein annotation.

A demo is available at galactica.org.

High availability implementation of AWS NAT instances.

Pretty simple Discord bot to get the active developer badge

Shira is a terminal-based application for exploring Python objects.