Matt Rickard gives some Non-Obvious Docker Uses.
In many projects, the approach to dates is quite nonchalant. People do as they want. When on-premise systems were king, the common problem was that it was hard to know precisely when something happened. The consistency of the configuration depended on how meticulous ops people were. It wasn’t shocking to find out that the server had a different time zone, the application had a different one, and the user had a different time zone. At one point, the development community found a compromise that “maybe we would use the same time zone everywhere, for instance UTC”.
Source: Is keeping dates in UTC really the best solution?, an article by Oskar Dudycz.
In 2019, Netcraft found 74.2% of web-facing machines run Linux. During an IPv4-wide census in 2016, an OpenSSH banner was detected 75% of the time when there was a response on TCP port 22. It's safe to say OpenSSH is probably the world's most popular software for connecting to servers remotely. It's also one of the most prized attack vectors given the functionality offered to anyone able to connect.
Hardening the security aspects of an OpenSSH configuration is very challenging. It's even worse for teams that aren't focused on network security and can't justify the budget for consultants setting up bespoke systems.
Source: Hardening SSH, an article by Mark Litwintschik.
When your Celery tasks are too slow, and you want them to run faster, you usually want to find and then fix the performance bottleneck. It’s true, you can architect a solution where slow tasks don’t impact faster ones, and you may sometimes need to. But if you can manage to make all your tasks fast, that is ideal.
Source: Finding performance bottlenecks in Celery tasks, an article by Itamar Turner-Trauring.
n this post we’re going to see how we can stitch together a few libraries to make a unit-aware queryable data frame from a CSV using extensible records. By the end of this text, we’ll be able to parse a CSV of data from the periodic table, complete with the correct units, and able to quickly ask questions about our data set using the generated indices.
Source: Unit-aware data frames with composite, dimensional and ixset-typed., an article by Dan Firth.
In my time pretending to be an engineer and working with git at Twitter, I’ve seen an interesting behavior pop up intermittently. People start complaining about git-push being slow. This particular issue becomes hard to diagnose, especially since the pandemic because we can’t be certain of the quality of connection being used, and optimizations to
git-pushhas always taken a back seat to all the other changes we’ve done to git internally. But it has persisted long enough that it needed some deeper diving into, and the intermittent nature always fascinated me. Let’s talk about the problem a little more.
Source: Why Would Git Push a Larger than Necessary Pack, an article by Kiran Paul.
Yesterday, in the early evening, I noticed that the Chromatopelma cyaneopubescens I keep had molted. And today, because I could guide it carefully in a different position, I took a few photos.
In the photo above you can see why this tarantula has the common name green bottle blue tarantula or GBB for short.
Today we’ll look at ways of productionizing the toy program from the previous post. Our primary goal here is allowing the user to select various statistics, computing just what the user has selected to compute. We’ll try to do this in a modular and composable way, striving to isolate each statistic into its own unit of some sorts.
I've been working with Python typing annotation in the last few years as part of our main product at Flare Systems. I've found it to be a wonderful tool to support refactoring and make the code more readable. Lately, I explored how we can make API safer with the uses of types. I will specifically look about how we can use Python typing annotation to make
Source: Typing your way into safety, an article by Israël Hallé.
If you’re following the latest news on Kubernetes, you probably would have heard about Ephemeral Containers. Not sure? Fear not! In this blog post we will try to shed some light on this new feature soon to be stable1 in Kubernetes v1.25.
Source: Getting Started With Ephemeral Containers, an article by Mehul Arora.
Last year I came across an article on Hacker News advertising a new project called prettymaps. It's largely the work of Marcelo de Oliveira Rosa Prates and Christoph Rieke and allows you to specify a location by its name and, using some great default styles, will generate a map of that area in PNG format.
Source: Pretty Maps in Python, an article by Mark Litwintschik.
I decided to write this article after I thought about the arguments from both sides and then found what I think is an underrated visualization for SQL joins that I am calling the checkered flag diagram. 🏁
Source: You Should Use This to Visualize SQL Joins Instead of Venn Diagrams, an article by Andreas Martinson.
Anyone who’s seen a couple different production database environments is likely familiar with the “soft deletion” pattern – instead of deleting data directly via
DELETEstatement, tables get an extra
deleted_attimestamp and deletion is performed with an update statement instead.
A Git repository is an append-only filesystem. You can add snapshots of files and directories, but you can't modify or delete anything. Git commands sometimes purport to modify data. For example
git commit --amendsuggests that it amends a commit. It doesn't. There is no such thing as amending a commit; commits are immutable.
Source: Things I wish everyone knew about Git (Part II), an article by Mark Dominus.
- Dynamic analysis - using debugger to step through the code and observing it’s behaviour over time.
- Static analysis - performing source code analysis without running it, but parsing and analysing the code itself.
“Stacked PRs” is the practice of breaking up a large change into smaller, individually reviewable PRs which can depend on each other, forming a DAG.
Source: In Praise of Stacked PRs, an article by Ben Congdon.
Pop quiz: What is the maximum number of A records in a DNS round robin? Or the largest number of bytes in a TXT record? Maybe it's all the same, and we should ask what is the maximum size of a DNS response? Is it...
- 512 bytes
- 1232 bytes
- 65536 bytes
- "It depends."
Let's find out. The answer is, as all things involving the DNS, entertaining.
Source: DNS Response Size, an article by Jan Schaumann.
pandas is a powerful data analysis library with a rich API that offers multiple ways to perform any given data manipulation task. Some of these approaches are better than others, and pandas users often learn suboptimal coding practices that become their default workflows.
Source: 4 Pandas Anti-Patterns to Avoid and How to Fix Them, an article by Aidan Cooper.
Today we’re very excited to announce Pyston-lite, a JIT for Python that is easily installable as an extension module. We’ve taken the core technology of Pyston and repackaged it so that you can install it through your existing Python package manager, making it dramatically easier to use. Pyston-lite doesn’t contain all of the optimizations of regular Pyston, but it is roughly 10-25% faster than stock Python 3.8 depending on the workload and we are not done optimizing it.
Source: Announcing Pyston-lite: our Python JIT as an extension module, an article by Kevin Modzelewski.
Netcat, curl and socat for WebSockets.
Source: websocat, an article by Vitaly Shukela.
One of the major selling points of the Rust programming language is its low-level expressiveness and memory safety. Unlike programming languages that use garbage collectors like Haskell, Ruby, and Python, Rust provides express functionality for developers to use and manage memory as efficiently as they please in a unique fashion.
This article discusses the Rust borrow checker, Rust’s memory management in comparison to other languages like Go and C, and the drawbacks of the Rust borrow checker.
Source: How Rust manages memory using ownership and borrowing, an article by Ukeje Chukwuemeriwo Goodness.