Destroyer of worlds
Some background on how 8chan got started.
Public
What happened to Evernote
Article that investigates where and how Evernote lost its way
G Suite + ChromeOS: Account Blocked notification & Gmail App Not Syncing *SOLUTION*
This has been a problem for me recently, plus I've have a related issue with WearOS. I think this actually solves both issues.
BTrDB: Berkeley Tree Database
Berkeley Tree DataBase provides very fast storage of scalar-valued timeseries data.
Switching back to Emacs causes the warning "recentf mode: Non-character input-event". · Issue #5554 · syl20bnr/spacemacs
While I don't use Spacemacs myself (this isn't actually a Spacemacs issue), I'm getting this a lot on my iMac and Macbook; especially when I've woken them from sleep.
Dark Patterns at Scale: Findings from a Crawl of 11K Shopping Websites
Interesting site/paper detailing instances of "dark patterns" in online retail. Instances of website design that seek to manipulate the customer into doing things they may not have wanted or intended.
Building Standalone Python Applications with PyOxidizer
Blog post about a newly-released project that aims to make it easier to build and deploy standalone Python applications.
A Byte of Vim
Book that provides an introduction to vim. Comes in free electronic version and commercial hard copy version.
Emacs officially named in November 1976
Little tweet thread of emails that record the naming of Emacs.
No Ageism In Tech
Website dedicated to fighting agism in the tech industry, and to promoting companies and positions that are open to older developers.
Rate Limiting
The API rate limits for Benchling.
Palindromic Sequence
Description of palindromic sequences in DNA.
Towards a Cleaner Emacs Build – Random Thoughts
Blog post about the cleaning up of lots of warnings in the compilation of Elisp code in Emacs itself.
Mezzano
Operating system written in Common Lisp. Even runs DooM and Quake!
What happens when software developers are (un)happy | Elsevier Enhanced Reader
The growing literature on affect among software developers mostly reports on the linkage between happiness, software quality, and developer productivity. Understanding happiness and unhappiness in all its components – positive and negative emotions and moods – is an attractive and important endeavor. Scholars in industrial and organizational psychology have suggested that understanding happiness and unhappiness could lead to cost-effective ways of enhancing working conditions, job performance, and to limiting the occurrence of psychological disorders. Our comprehension of the consequences of (un)happiness among developers is still too shallow, being mainly expressed in terms of development productivity and software quality. In this paper, we study what happens when developers are happy and unhappy while developing software. Qualitative data analysis of responses given by 317 questionnaire participants identified 42 consequences of unhappiness and 32 of happiness. We found consequences of happiness and unhappiness that are beneficial and detrimental for developers’ mental well-being, the software development process, and the produced artifacts. Our classification scheme, available as open data enables new happiness research opportunities of cause-effect type, and it can act as a guideline for practitioners for identifying damaging effects of unhappiness and for fostering happiness on the job.
The reduce ({...spread}) anti-pattern - RichSnapp.com
Interesting article about the potential pitfalls of using reduce and spread for cool JavaScript one-liners. I don't think I'm in the habit of using this particular pattern, but I should probably keep an eye out for it.
Benchling API
Documentation for the Benchling API.
Use __main__.py in Python | shaneoneill.io
For some reason I'd not picked up on this since getting back into Python. Could be seriously handy.
vim/neovim security vulnerability
Write-up of the rather amazing vulnerability in vim/neovim.
www.pythonanywhere.com
This could be useful for hosting of personal apps, or at least for experimenting with Python Web applications.
A Failed Experiment with Python Type Annotations – Musing Mortoray
Blog post that does a good job of outlining some of the issues I have too with type checking in Python.
See the following for some correction of what's said: https://news.ycombinator.com/item?id=20159153
Loopy
Neat site that can be used to investigate and demonstrate the relationship of things in a sort of feedback loop approach.
Beyond appendChild: Better convenience methods for HTML - DEV Community
Short article about some handy DOM manipulation methods and idioms in JavaScript.
BADA55.io - CSS hex color words for web developers
Amusing, and not always sfw, resource for colours with "interesting" names.
Move fast and migrate things: how we automated migrations in Postgres
How Benchling manage their Postgres migrations.
Rust Your Own Lisp
A translation of Build Your Own Lisp into Rust. Should be a handy read to get to know some Rust concepts.
Software Engineering for Machine Learning: A Case Study
Abstract—Recent advances in machine learning have stimulated widespread interest within the Information Technology sector on integrating AI capabilities into software and services. This goal has forced organizations to evolve their development processes. We report on a study that we conducted on observing software teams at Microsoft as they develop AI-based applications. We consider a nine-stage workflow process informed by prior experiences developing AI applications (e.g., search and NLP) and data science tools (e.g. application diagnostics and bug reporting). We found that various Microsoft teams have united this workflow into preexisting, well-evolved, Agile-like software engineering processes, providing insights about several essential engineering challenges that organizations may face in creating large-scale AI solutions for the marketplace. We collected some best practices from Microsoft teams to address these challenges. In addition, we have identified three aspects of the AI domain that make it fundamentally different from prior software application domains: 1) discovering, managing, and versioning the data needed for machine learning applications is much more complex and difficult than other types of software engineering, 2) model customization and model reuse require very different skills than are typically found in software teams, and 3) AI components are more difficult to handle as distinct modules than traditional software components — models may be “entangled” in complex ways and experience non-monotonic error behavior. We believe that the lessons learned by Microsoft teams will be valuable to other organizations.
if-let, when-let, thread-first and thread-last
Good little introduction to flow control macros that were introduced in Emacs 25.1.
Various intersphinx mappings for Python libraries.
Handy list of intersphinx mappings for various popular Python libraries.
Gridrunner++ by llamasoft_ox
Windows version of the classic Vic20 and CBM64 game.