Python news wrap-up for January 2023
Meta AI, open-source contributions, AWS access key leak, and more!
Hello Grokking Python readers, and happy Thursday!
We have a lot of news to cover from January, so let’s jump right in!
Meta AI's new open source data science package

Meta AI, the researchers, scientists, and software engineers behind Meta's artificial intelligence efforts, have released a new Python package called "Balance." The package is still in beta and undergoing active development, but for now, it provides a simple workflow for addressing biased data samples.
Biased samples can frequently occur in survey statistics, polls, and other relatively small data sets, resulting in skewed or inaccurate results.
Balance aims to correct these biases and more:
Missing data (that is not completely random)
Treated vs. untreated groups (observational studies)
The best part about this package is that all of Meta AI's incredible research is open source. Balance is intended for any data professionals working in Python with potentially biased data. The documentation for the package states that Balance is intended for survey methodologists, demographers, UX researchers, market researchers, general data scientists, statisticians, and machine learning engineers.
Hyperfinity optimizes platform with Snowflake's Snowpark for Python

Hyperfinity is a SaaS decision science platform that uses machine learning, AI, and data science to make business decisions. Their data models can inform numerous pricing, supply chains, CRM/ERP, and content management optimizations. With this recent update, Hyperfinity streamlined its serverless architecture and simplified life for its developers.
Snowflake's data cloud solutions are ideal for a data-intensive company like Hyperfinity. The REST API, Snowpark, allows Hyperfinity to speed up compute times for array and matrix multiplication. Since a large chunk of the data Hyperfinity works with are customer decision trees, they can reduce cost and time investment.
Python's affinity for built-in libraries made the integration of Snowpark extremely simple. Snowflake is even partnering with the package manager, Anaconda, to make the development administration process as smooth as possible.
All of this is incredibly validating when it comes to seeing the power of Python in action, and great news for data scientists and AI researchers. You can check out Hyperfinity's write-up on the transition if you want to read more.
Live AWS keys found on PyPI
Reddit user u/Most-Loss5834 scanned every package on the Python Package Index (PyPI) and found 57 live, valid access keys. It's unfortunately very common for developers to accidentally leak their login credentials on sites like GitHub or PyPI. Still, most of the time, the keys are found and deprecated automatically. Seeing live keys, especially ones connected to big names in tech, comes as a surprise.
The live AWS keys were from a vast range of organizations:
Amazon themselves
Intel
Stanford, Portland University, and Louisiana University
The Australian Government
Terradata
Delta Lake
Top Glove
The oldest functioning key was over 10 years old! The circumstances that lead to these keys remaining live are unclear, and this discovery serves as another reminder to be extra careful when handling access credentials. Even if your professional organization has built-in automated detection and deprecation services, it is crucial to double-check your GitHub repositories and any other public-facing code to avoid leaving yourself or your employer vulnerable.
Below is just a small excerpt of the enormous regular expression used to find all of the keys.

If you're interested in learning more, the original blog documents the process used to scan PyPi and find these keys.
1st IndyPy meetup of 2023

The Indianapolis Python community recently hosted their first meetup of the year on January 10th! IndyPy was organized by the Python and cloud computing consulting company Six Feet Up. Mariatta Wijaya, a Senior Developer Relations Engineer at Google, notable Python Core developer, and PyCon 2023-24 Chair, discussed ways individuals can contribute to the Python community.
Contributing to an open-source community is an honored tradition in software development. It is a great way to give back and provide value to other engineers. Still, not everyone is familiar with best practices when making pull requests, standards for documenting code, and other nitty-gritty details when contributing to open-source projects. The open-source community is massive, and it's easy to feel overwhelmed or lost.
If you're interested in learning more about getting started in the Python's open source community, this post covers FAQs and Python projects in need of contributions.
Wijaya went over how individuals can find their niche in an open-source community, emphasizing that it's important not to try to solve every problem. Instead, try to maximize your impact by sticking to your strengths.
You can find her slide deck here: https://speakerdeck.com/mariatta/contributing-to-python
Additionally, you can follow Mariatta Wijaya on Twitter, Fosstodon, and LinkedIn.
PSF Diversity and Inclusion meeting

This was the first diversity and inclusion meeting that the Python Software Foundation (PSF) has held. If you missed it, don't worry, they are scheduled for once a quarter for the year. During this meeting, people in the Python community from around the world gather to discuss news, current events, and the inner workings of the PSF.
A registration link for the next meeting is currently unavailable, so we recommend following the Python Software Foundation on Twitter to stay updated on events like this.
Attendance is free! However, be sure to pay attention to your time zone if you plan on attending.
New Chemics package available
It's not just the data scientists who lucked out this month. There's something for chemists too! Chemics v23.1 is now available. This new version brings several improvements, the most notable of which is improved handling of Chemical Abstracts Service (CAS) numbers due to an updated gas viscosity function. This may not sound like a glamorous update to the average layperson, but this update is worth looking into for the gas geochemists out there.
The following example, taken from the Chemics PyPI project description, demonstrates the use of the rhog() function to calculate the density of a gas based on three parameters: molecular weight, temperature, and pressure.

Brand new Educative learning content
We're always adding new courses to the catalog, so we'd like to take the time to spotlight a brand-new course that is greatly relevant to our audience of Pythonistas.
Grokking Dynamic Programming: A Deep Dive using Python
If you've ever been interested in learning more about dynamic programming (DP), now is your chance. This brand-new course teaches DP from the very beginning. Dynamic programming is one of the more advanced optimization techniques for recursive software. Even if you have yet to encounter dynamic programming in your career, it could be worth learning for a future technical interview. Some of the most challenging coding interview problems rely on dynamic programming.
This course explains the basics and then breaks down five underlying patterns of DP. Each pattern is applied to multiple real-world scenarios to equip you with practical DP problem-solving skills.
More content is coming soon 👀
We hope you enjoyed this recap of all that happened in the Python world this January. We'll be highlighting some more excellent, fresh content later this month. If you want to learn to code in a new and engaging way, be sure to check out our forthcoming editions of Grokking Python.
In the meantime, happy learning!