There are many different integrated development environments (IDEs) to choose from for Python development. One popular option for data-focused work is Spyder, an open-source Python IDE geared toward scientists, engineers, and data analysts. Its name comes from Scientific PYthon Development EnviRonment.
Out of the box, it has powerful plotting, what-if, and profiling capabilities. It also integrates well with the data science ecosystem, is extensible with first- or third-party plugins, and has a relatively quick learning curve.
How does Spyder stack up against other Python IDEs? It depends on your use case. It’s not as powerful or customizable as VS Code, nor does it pretend to be. It does, however, excel for data science workflows:
Use Case
Pick Spyder
Pick an Alternative
Optimized for data science workflows
✅
—
Dedicated to Python
✅
—
Full-featured
—
VS Code
Supports interactive notebooks
✅ With a plugin
Jupyter, VS Code
If you’re focused on data science in Python, Spyder is a strong fit. For a more full-featured IDE or heavy notebook use, consider Jupyter or VS Code instead.
You can get a handy Spyder IDE cheat sheet at the link below:
Take the Quiz: Test your knowledge with our interactive “Spyder: Your IDE for Data Science Development in Python” quiz. You’ll receive a score upon completion to help you track your learning progress:
Test your knowledge of the Spyder IDE for Python data science, including its Variable Explorer, Plots pane, and Profiler.
Start Using the Spyder IDE
You can install Spyder in a few ways: as a standalone program, through a prepackaged distribution, or from the command line. You can also try out Spyder online.
To install Spyder as a standalone application, go to the Spyder download page. When you visit the site, it detects your operating system and offers the appropriate download. Once you download your install file, open it and follow the directions.
You can also install a Python distribution tailored to data science, such as Anaconda or WinPython. Both of these choices include Spyder in their base installations.
You’ll likely want to install dependencies and useful data libraries in addition to Spyder. In this case, first create a Python virtual environment, then use this command:
For more information on installing Spyder, refer to their install guide.
Out of the box, the Spyder interface consists of three panes:
The Spyder IDE Interface
On the left, you see code in the Editor pane. In the bottom right, you’ll find the IPython Console. Here, you can run code and check past commands using the History tab. The top-right area includes tabs such as Help, Debugger, Files, Find, and Code Analysis. You’ll learn about the Variable Explorer, Plots, and Profiler in the upcoming sections.
Back in 2015, Microsoft announced Windows Continuum, a feature that could transform Windows 10 Mobile phones into full-blown desktops, complete with a desktop-like interface, full-screen apps, and support for keyboards and mice. The catch was that Continuum was impressive on paper, but not in practice.
https://photos5.appleinsider.com/gallery/66992-140732-ipadmacos2-xl.jpgThe MacBook Neo proves that macOS can run on an iPhone processor. More than that, it shows how Apple now has all of the elements to make a device that’s transformative in every sense.
macOS doesn’t work on iPad, but imagine if it did.
Imagine only ever needing to carry around your iPhone, regardless of whether you were working with macOS or not. Imagine connecting your iPad to a Magic Keyboard, and firing up macOS.
Either would be one single device that works like an iPhone in your hand, or an iPad on your lap, but a Mac when you connect it to the right input and output devices.
The DBStan package provides detailed analysis and insights into your database schema for Laravel applications. It helps identify structural issues, missing indexes, normalization problems, nullable column risks, foreign key inconsistencies, and performance concerns.
It is an essential tool for debugging, optimizing, reviewing, and maintaining a healthy database architecture in Laravel projects.
Important Notice: Configure Database Before Using This Package
Before using this package, ensure your database connection is properly configured in your Laravel application.
If the database is not configured correctly, DBStan will not be able to analyze your schema.
Make sure your .env file contains valid database credentials.
Security Warning
This package exposes detailed database schema analysis.
It is intended for admin and development use only.
Do NOT expose this tool publicly in production without proper access restrictions, as schema details may reveal sensitive structural information.
Windows comes loaded with software to meet most of your needs out of the box, but if you like free and open-source projects, or if you just want alternatives, there are plenty of great options out there.
Most of us set up MySQL, run our migrations, and never think about the database configuration again.
And honestly, that works fine for many apps.
But MySQL ships with defaults tuned for minimal hardware, not for a production Laravel app handling real traffic.
Settings like innodb_buffer_pool_size, flush behavior, and I/O thread counts are all set conservatively out of the box.
I came across a great article on Laravel News that walks through the InnoDB settings most likely to affect your app’s performance.
It’s not a deep dive into the MySQL manual.
It’s a practical overview of what to look at, why it matters, and what tools can help you figure out the right values for your setup.
For example, the buffer pool size alone can make a huge difference.
The default is far too small for most production apps, and bumping it up based on available RAM lets MySQL keep more data in memory instead of hitting disk repeatedly.
The article also highlights some handy tools like MySQLTuner and Percona Toolkit that analyze your running database and suggest specific changes.
Much better than guessing.
Not everyone reads the MySQL manual cover to cover, so articles like this are a great way to pick up practical knowledge without a huge time investment.
Here to help,
Joel
P.S. If your app is sluggish, and you’re not sure where to start, we can help you find the bottleneck. Schedule a call and let’s figure it out together.
The Super Mario Galaxy Movieis nearly upon us, as the hotly-anticipated sequel arrives in theaters on April 1. Nintendo recently dropped the final trailer for the film, which is filled with quick visual gags and nods to the source material.
There aren’t too many actual reveals in this footage, as it covers a lot of the same ground as previous trailers. However, it does show that fan favorite Lumalee is returning as a prison guard of some sort, reversing the storyline from the original film in which the cheerfully nihilistic creature was trapped in a cage.
Nintendo also released a larger presentation that featured the aforementioned trailer, but also included interviews with actors and franchise creator Shigeru Miyamoto. We did get some news in this video.
It was revealed that the long-tongued dinosaur Yoshi will be voiced by Donald Glover. So it’s likely the dino will be saying a lot more than "Yoshi" over and over. Actor Luis Guzman will also be playing Wart, the primary antagonist from Super Mario Bros. 2. Issa Rae will be on hand to voice Honey Queen, the gigantic bee character from the Super Mario Galaxy games.
It was even confirmed by lead actors Chris Pratt and Charlie Day that Luigi would be on hand for the entire adventure this time, and not confined to a cage-based subplot. I didn’t realize Luigi’s role in the first film was enough of a controversy to warrant this kind of mention, but here we are.
Illumination CEO Chris Meledandri also appeared in the video, assuring viewers that there are still "some big surprises" waiting in the actual film. To that end, there’s been a rumor floating around that Fox McCloud from the Starfox franchise would be showing up. Is this the start of a Nintendo cinematic universe that will culminate in 10 years with a Super Smash Bros. movie? Stranger things have happened.
This article originally appeared on Engadget at https://www.engadget.com/entertainment/tv-movies/heres-the-final-trailer-for-the-super-mario-galaxy-movie-181819593.html?src=rssEngadget
A couple of months ago, Eindhoven-based designer Paul Staal was thinking about a new project: a smart dashboard for his home office. His idea was to integrate the dashboard into a 3D-printed shell that paid homage to Lego’s classic 2×2 sloped computer brick, a piece that’ll be instantly recognizable to anyone who has spent any time with vintage Space Lego sets.
Eventually, Staal tells Gizmodo, he decided to combine the dashboard into a case for his Mac Mini: “[I thought], ‘Why would I add another device to my desk? Why not just make it large enough for my [computer] instead?’”
The original design stuck closely to that of the Lego brick, but Staal found the result “bland and boring”: without the detailing on the front of the brick, the case was essentially just a large right-angled triangle. But then inspiration struck: why not combine the Lego silhouette with the aesthetics of another 1980s design icon?
The result was the M2x2, a case that takes its inspiration from both Lego’s classic console brick and the original Apple Macintosh. It’s 3D printed with a filament that’s an absolute dead ringer for the latter’s beige plastic shell, and equipped with a 7” touch screen, multiple USB-C ports, an SD card reader, and a handle for portability.
The design is full of clever touches: for example, the two large studs atop the case are both functional, with one serving as a volume knob for Staal’s Bluetooth speaker and the other as a wireless charger for his AirPods and Apple Watch. (They’re also adorned with actual Lego studs that can accommodate a mini-figure—or, indeed, one of the bricks that served as the design’s inspiration.) Anyone else using the design can customize the functionality to their liking: “I made the design for this case modular,” Staal explains, “so if anyone wants to make one, they can choose what they want to use the studs for.”
The touchscreen, meanwhile, is essentially self-contained: “It offer[s] quick access to some controls on my Home Assistant dashboard.” Staal says that if he makes another version of the device, he’d perhaps replace it with an iPad Mini to take advantage of that device’s integration with macOS. “Maybe I’ll work on that in the future,” he says, “perhaps even pairing it with a Mac Studio instead of a Mac mini.”
For now, though, he has a couple of other projects on the go: “I have a couple of other projects that I still want to document/finalise and share on my website… One of them is a new dock for my Nintendo Switch 2, [which] I hope to finish somewhere in the upcoming weeks, so stay tuned.”
In a new “breaking news” sit-down on The Four Boxes Diner, constitutional litigator and Second Amendment historian Stephen P. Halbrook joins host Mark W. Smith to walk viewers through a question gun owners have debated for decades: does federal law actually forbid the registration of post-May 19, 1986 machine guns for ordinary Americans—or did ATF “fill in the blanks” with regulation and judicial deference that no longer holds up?
This is a lawyer-to-lawyer conversation about statutory text, agency overreach, and the post-Chevron legal landscape—plus a developing strategy in places like West Virginia and Kentucky that could force a clean test of ATF’s long-standing interpretation.
Below is what Halbrook and Smith argued, why it matters, and what gun owners should understand before the “legalize machine guns” headlines run away with the story.
The core fight: what 18 U.S.C. § 922(o) says vs. what ATF does
The so-called Hughes Amendment lives at 18 U.S.C. § 922(o). The key structure is simple:
(o)(1): “Except as provided in paragraph (2), it shall be unlawful for any person to transfer or possess a machinegun.”
(o)(2)(A) then carves out an exception for “a transfer to or by, or possession by or under the authority of, the United States… or a State… or political subdivision thereof.”
(o)(2)(B) preserves lawful possession of machine guns lawfully possessed before the effective date.
Smith’s argument, echoed by Halbrook’s earlier litigation history, is that the statutory phrase “under the authority of” reads like permission/authorization, not “for the benefit of government” or “government use only.”
That distinction matters because ATF’s implementing regulation took a very different path.
The regulation that changed everything: “for the benefit of government.”
ATF’s machine gun regulation, 27 C.F.R. § 479.105, is where the “government use” concept becomes explicit. It states that applications to make/register machine guns after May 19, 1986 will be approved only when made “for the benefit of” a federal/state/local governmental entity, backed by specific information and (in practice) a government request/on-behalf-of showing.
Smith and Halbrook argue this is the pivot point: the statute’s text doesn’t contain “for the benefit of government,” yet the regulation effectively adds it. In their telling, that add-on hardened into “common knowledge” because courts spent decades deferring to agency interpretation.
Which brings us to the big modern change.
The post-Chevron landscape is significant because the Loper Bright decision effectively removes the policy of judicial deference.
Halbrook points to the Supreme Court’s 2024 decision in Loper Bright Enterprises v. Raimondo, which overruled the Chevron doctrine that frequently pushed courts to defer to agencies on ambiguous statutes.
Their thesis: if ATF’s position became entrenched largely through deference-era judging, that foundation is weaker now. Courts are supposed to decide the best reading of the statute themselves—not default to “ATF says so.”
That doesn’t automatically mean gun owners win. But it does mean older “we defer to ATF” opinions aren’t the trump card they once were, especially if a case tees up the statutory language cleanly.
Halbrook’s front-row history lesson: the Hughes Amendment’s messy birth
Halbrook describes watching the 1986 House debate where Rep. William Hughes introduced the machine gun amendment late in the process, amid chaos, and it was adopted without the kind of clean, deliberate record you’d expect for a ban this sweeping. (That political history doesn’t override the statutory text—but it matters when courts look for clarity.)
He also notes that the ban took effect after a delay, during which manufacturers produced/registerable machine guns before the cutoff, a well-known quirk of how the “registry freeze” era began.
The case that shaped the modern status quo: Farmer v. Higgins
Halbrook recounts his early challenge involving a would-be maker application denied after Hughes. The dispute is closely associated with Farmer v. Higgins in the Eleventh Circuit, which rejected the district court’s more permissive reading and sided with ATF’s position.
Smith’s point is blunt: Farmer became a “leapfrog precedent”—one circuit cites another, and soon the ATF interpretation is treated as settled law without fresh analysis.
Halbrook agrees that this is a recurring disease in gun jurisprudence: once a court writes “government wins,” other courts copy-paste.
The Commerce Clause pressure point: Lopez and Alito’s Rybar dissent
A second major thread in the video is constitutional: even if ATF’s reading stands, does § 922(o) have a solid Article I hook?
Halbrook highlights the Supreme Court’s Commerce Clause decision in United States v. Lopez (1995), which struck down the Gun-Free School Zones Act because it criminalized mere possession without a sufficient commerce nexus.
Smith then ties that logic to machine guns. In United States v. Rybar (3d Cir. 1996), then-Judge Samuel Alito dissented, calling § 922(o) the “closest” relative to the law struck in Lopez and arguing Congress hadn’t shown the required substantial effect on interstate commerce.
You don’t have to accept every step of their reasoning to see the strategic value: if a court rejects the “under the authority of” statutory argument, the fallback becomes a renewed constitutional attack—Commerce Clause and, in today’s environment, likely Second Amendment arguments as well.
The practical plan discussed is not “buy a machine gun tomorrow.” It’s a litigation-minded approach:
A state sets up a program where a state entity (often discussed as a division within state police) acquires/holds machine guns.
The state then authorizes transfers/possession under state authority, with a process for qualified citizens.
Applicants file the relevant federal paperwork, and if ATF denies on the “government use only” theory, that denial becomes the injury for a direct legal challenge.
Halbrook’s point is tactical: clean plaintiffs and clean facts matter. Civil litigation with ordinary, law-abiding citizens is very different from a criminal appeal with ugly fact patterns.
What gun owners should take away?
1) The statutory text really does contain a government/State carveout. The words “under the authority of” are there, and they do work in other legal contexts.
2) ATF’s regulation explicitly adds a “for the benefit of government” framework. That’s the gap the video targets.
3) The legal environment changed after Loper Bright. Agency deference is no longer the automatic shield it once was.
4) There are two lanes of attack—statutory and constitutional. Lopez and Alito’s Rybar dissent show why some lawyers think § 922(o) is vulnerable even apart from ATF’s interpretation.
5) None of this is “done.” Even a strong legal theory has to survive hostile circuits, political pressure, and a federal bureaucracy that has spent nearly 40 years treating the registry freeze as untouchable.
Halbrook and Smith are making a provocative—but legally literate—argument: the post-’86 machine gun ban as enforced today may rest on an ATF gloss that goes beyond Congress’s words, preserved for decades by judicial deference that’s now been repudiated.
If West Virginia/Kentucky (or another state) can tee up a clean denial case, it could force courts to answer the question they’ve dodged for a generation: does “under the authority of a State” mean what normal English says it means or what ATF wrote into a regulation?
And if courts won’t take the statutory off-ramp, the constitutional cliff edge—Commerce Clause and Second Amendment—still looms.
Most people, when asked what a database does, say something like: “it stores data.”
That’s like saying a restaurant “stores food.”
Technically true. Completely misses the point.
A restaurant has to cook fast, serve many tables at once, and not poison anyone. Fail any one of those three and it doesn’t matter how good the kitchen looks. A database has the same problem — except the stakes are your production system at 2am.
A few years ago I gave a talk at Percona Live in Denver where I tried to answer this properly. Not from a features list. Not from a vendor slide deck. From first principles: what does a database have to do?
Three things. Everything else — every configuration parameter, every architecture decision, every incident you’ve ever fought — falls into one of them.
Execute Queries
A restaurant has one core job: take an order and bring food to the table. Fast, correct, and for as many tables as possible simultaneously.
A database has the same job. Answer questions about data. Record changes. As fast as possible, as many as possible, without corrupting anything in the process.
That last part is the one that gets sacrificed first when you’re optimizing for speed. InnoDB’s entire machinery — the buffer pool, the redo log, the doublewrite buffer — exists to make sure “fast” and “correct” happen at the same time. ACID isn’t a marketing term. It’s the contract the database makes with every query it executes.
The tension is real. Disabling foreign_key_checks before a bulk load makes the operation faster. It also removes a correctness guarantee while it’s disabled. That tradeoff isn’t inherently wrong — but you can only make it deliberately if you understand what you’re trading. If you’re curious about the hidden consequences of foreign keys, I covered one particularly dangerous scenario in the ON DELETE CASCADE blind spot in MySQL’s binary log.
When a query is slow, the reflex is to reach for indexes. Sometimes that’s right. But a query can also be slow because lock contention is serializing execution, because the working set stopped fitting in the buffer pool, or because something upstream is flooding the connection pool. Same symptom, completely different root causes, completely different solutions. Knowing the responsibility narrows the search. Understanding InnoDB semaphore contention is one way to tell lock contention apart from other causes.
Relationships
No database is an island.
Think of it like a person who has three very different kinds of relationships in their life — and does a bad job with any one of them at their own peril.
With users, the relationship is trust and boundaries. Who gets in, what they can see, what they can touch. MySQL’s account model — hosts, privileges, roles — is the entire machinery for this. When someone asks why the application can’t just run as root, this is why. The database has a responsibility to protect data from people and systems that shouldn’t have it. That responsibility doesn’t disappear because setting it up is inconvenient.
With other databases, the relationship is coordination. A replica trusts that the primary is sending it a faithful copy of reality. A PXC node trusts that the other nodes in the cluster will agree on the same writes. When wsrep_local_recv_queue starts climbing, the cluster is telling you a relationship is under stress — one node can’t keep up with what the others are sending. It’s a relationship problem before it’s a performance problem. Treating it as a performance problem first is how you end up chasing the wrong metric.
With dev and ops teams, the relationship is communication. Logs, status variables, Performance Schema — this is how the database talks. When you skip configuring the slow query log because it adds overhead, you’re choosing silence. You’ll regret that choice during the next incident, when you’re flying blind trying to reconstruct what happened. Tools like PMM Query Analytics exist precisely to bridge this communication gap.
A database that executes queries correctly but can’t communicate its state, can’t cooperate with peers, and can’t enforce who has access — is a ticking clock.
Survive
This is the one nobody talks about at conferences, and it’s the one that kills you.
A database doesn’t run in the cloud. It runs on a machine. A machine with a CPU that can be saturated, memory that can be exhausted, and a disk that fills up and then — not slowly degrades, but stops. Full disk doesn’t slow MySQL down. It stops it cold.
Think of it like a tenant who has to know the rules of the building they live in. The landlord — the OS — controls memory allocation, file descriptors, I/O scheduling. The tenant can push their luck, but only so far before the landlord intervenes. An OOM kill at 3am is the landlord evicting a tenant who was using more than their share.
innodb_buffer_pool_size is the most important negotiation a MySQL server has with its host machine. Too low and you’re leaving performance on the table. Too high on a box running other processes and you’re gambling that the OS won’t reclaim that memory mid-write. That configuration parameter isn’t a performance knob. It’s a survival decision.
Disk is more insidious. A table that grows 100MB per day doesn’t look dangerous today. In six months it’s 18GB. The database won’t warn you. It will just stop one day. The monitoring that watches disk growth trends and alerts before the cliff — that’s not operational overhead. That’s the database fulfilling its responsibility to survive the physical world it lives in. Setting up smart alerting with dynamic thresholds is how you catch these slow-moving threats.
Backups live here too. A database that can’t be recovered after a failure didn’t survive. Full stop.
Why This Framework Matters
These three categories won’t tell you how to fix anything. They’re not a checklist. What they give you is a way to locate a problem before you start solving it — and that matters more than most people admit.
Replica falling behind? Three possible zip codes:
Execute Queries — the primary is running queries so heavy that the replica can’t replay them fast enough
Relationships — the network between primary and replica can’t carry the replication stream
Survive — the replica’s disk I/O is the bottleneck
Same symptom. Three completely different tools. If you go straight to tuning queries when the real problem is disk throughput on the replica, you will waste hours.
The framework doesn’t solve the problem. It tells you which drawer to open first.
Every decision you make as a DBA is in service of one of these three things. Execute queries correctly and fast. Manage relationships with users, peers, and teams. Survive the physical constraints of the machine it runs on.
That’s the whole job.
I first presented this framework at Percona Live in Denver. The talk was aimed at DBAs, but I’ve always believed that database fundamentals should be explainable to anyone — and that explaining them clearly forces a deeper understanding than talking only to specialists.
The Spyder IDE Interface
