Pointer to array is not only type-safe, it is also objectively correct and should have always been the syntax used when passing in the address of a known, fixed size array. This is all a artifact of C automatically decaying arrays to pointers in argument lists when a array argument should have always meant passing a array by value; then this syntax would have been the only way to pass in the address of a array and we would not have these warts. Automatic decaying is truly one of the worst actual design mistakes of the language (i.e. a error even when it was designed, not the failure to adopt new innovations).
I wrote this before I left GitHub and how I’d like to see Microsoft invest in this area, but it was too futuristic, considering how the market has evolved today, I decided to make this public.
If you want to know more about what I’m doing next www.autohand.ai
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1. Are tied to processes. They are not first-class values. (The processes are, and the mailboxes go with them.)
2. Can receive messages out of order using pattern matching. This is critically used all over the place for RPC simulations; you send a message out to some other process, and then receive the reply by matching on the mailbox. You may receive other messages in the meantime in that mailbox, but the RPC process is safe because the block waiting for the answer will keep waiting for that message, and the rest will stay there for later reception.
3. Are zero-or-one delivery. Messages going to the same OS process are reliable enough to be treated as reliable exactly-once delivery but you are not really supposed to count on that. (This is one of the ways you can write an Erlang system and you accidentally make it so it can't run on a cluster.) Messages going across nodes may not arrive because the network may eat them. If you're really excited you can examine a process ID to see if it's local but you're generally not supposed to do that.
As part of this, mailboxes are fundamentally asynchronous. You can not wait on "the message has arrived at the other end" because in a network environment this isn't even a well-defined concept. The only way to know that a message arrived is to be explicitly sent an acknowledgement, an acknowledgement that may itself get lost (Byzantine general problem).
4. Send Erlang terms, only Erlang terms, and exactly Erlang terms. Erlang terms are an internal dynamically-typed language with no support for user-defined types. This is important because this is how Erlang is built around upgradeability and having multiple versions of things in the same cluster. Since there are no user-defined types, you never have problems with having mismatched type definitions. (You can still have mismatched data, of course; if a format changes, it changes. But the problem is at least alleviated by not supported complicated user defined types. It is, arguably and in my opinion, a throwing the baby out with the bathwater situation, but I do admit against interest (as the lawyers say) that practically it works out reasonably well. Especially since the architect of the system really ought to know this is how it works up front.)
Because of the dynamically-typed nature, they are effectively untyped. Any message can be sent to a mailbox.
5. Are many-to-one communication, across an entire Erlang cluster. A given mailbox is only visible to one Erlang process; it is part of that process. Again, the process ID is a first-class value that can be passed around but the mailbox is not.
6. There are debug mechanisms that allow you to look into a mailbox live, on the cluster's shell. You can see what is currently in there. You really shouldn't be using these debug facilities as part of your system, but you can use them as a devops sort of thing. (As hard as I've been on Erlang, the devops story is pretty powerful for fixing broken systems. That said, the dynamic types means I had to fix more broken systems live than I ever have for Go; I haven't missed this because my Go systems generally don't break. Still, if they are going to break, Erlang has a lot of tools for dealing with it live.)
Go channels:
1. Are first-class values not tied to any goroutine. One goroutine may create a channel and pass it off to two others who will communicate on it, and they may further pass it around.
2. Are intrinsically ordered, at least in the sense that receivers can't go poking along the channel to see what they want to pull out of it.
However, an aspect of Go channels is that with a "select" statement, a single goroutine can wait on an arbitrary combination of "things I'm trying to send" and "things I'm trying to receive". This is entirely unlike pattern matching on a mailbox and is probably a really good example of the way you need solutions to certain communication problems, but they don't have to be the exact Erlang solution in order to work. Complicated communications scenarios that Erlang might achieve with selective matching can be done in Go with multiple channels multiplexed with a select. There are tradeoffs in either direction and it isn't clear to me one dominates the other at all.
3. Are synchronous exactly-once delivery. This further implies they only work on a single machine, and in Go they only work within a single process. This further implies that there is no such thing as a "network channel" in Go. You can, of course, have all sorts of things that sort of look like channels that work over a network, but it is fundamentally impossible to have a channel (of the "chan" type that can participate in the "select" statement) that goes over the network because no network can maintain the properties required for a Go channel.
It is also in general guaranteed that if you proceed past a send on a channel, that some other goroutine has received the value. This makes it useful for synchronization.
(There are buffered channels that can hold a certain fixed number of values without having actually been sent, but in general I think they should be treated as exceptions precisely because losing this property is a bigger deal that people often realize. A lot of things in Go are built on it. Contrary to popular belief, unbuffered channels are not asynchronous, because they are fixed size. They're just asynchronous, up to a certain point. Erlang mailboxes are asynchronous, until you run out of memory, which is not unheard of or impossible but isn't terribly common, especially if you follow the normal OTP patterns.)
4. Are typed. Each channel sends exactly one type of Go value, though this value can be an interface value meaning it can theoretically send multiple concrete types. (Generally I define the channel with the type I want though there is the occasional use case where I have a channel with a closed interface that basically uses the interface value like a sum type. I am still not sure whether this is better or worse that having a channel per possible type, and I've been doing this for a long time. I'm still going back and forth.)
5. Are many-to-many communication, isolated to a single OS process. It is perfectly legal and valid to have a single channel value that has dozens of producers and dozens of consumers. Performance implications are related to the rate these goroutines are trying to communicate over; if, for instance, at low rates it's no problem at all.
6. Are completely opaque, even within Go. There is no "peek", which would after all break the guarantee that if an unbuffered channel has had a "send" that there has been a corresponding "receive".
Contra another comment I see, no, you can not implement one in terms of the other. You can get close-ish, but there are certain aspects of them that simply do not cross, notably their sync/async nature, their differing network transparencies, and the inability of an Erlang mailbox to be "many-to-many", particularly in the way the "many-to-many" still guarantees "exactly once" delivery. (You can set up certain structures in Erlang that get close to this, but no matter what you do, you can not build any abstraction on a zero-or-one delivery system to create an exactly-one delivery system.)
You can solve almost any problem you have with either of these. You can use either to sort of get close to the other, but in both directions you'll sacrifice significant native capabilities in the process. It's really an intriguing study in how the solution to very similar problems can almost intertwine like an Asclepius staff, twisting around the same central pole while having basically no overlap. And again, it's not clear to me that either is "better"; both have small parts of the problem space where they are better than the other, both solve the vast bulk of problems you'll encounter just fine.
When we make game-playing AI (which is all AI, depending on your analogy comfort), one of the most promising techniques is Tree Search, which ranks moves based on the descendant moves. In games where you could reach the same state in many ways, much memory might be wasted to re-record the same state node on different branches.
This article is a nice exploration of an approach called Graph Search, which essentially trades compute for memory by doing extra compute work (hashing the game states) to check to see if the nodes are already visited. That saves us from re-recording nodes we already saw, and consequently converts trees (free of cycles) into directed acyclic graphs.
This forces some tinkering with the tree search to get correct results, specifically it demands a focus more on edges (actions or moves) as the unit of optimization, rather than on vertices (states). It’s a well written technical essay in literate programming written by someone who understands their subject.
I've started using worktrees recently and I have nothing but praise for it. It's especially useful to me because I work on multiple features and want to reduce friction from context switching. I basically have a structure like `/worktrees/<project>/<worktree>`. I use it alongside direnv and have my .envrc in the top-level project. That essentially allows me to set up project-specific environments for all of my worktrees. This works neatly with emacs projectile mode and lets me switch between different projects/features seamlessly. My head feels a lot lighter not having to worry about my git branch state, stashing changes, and all that jazz. I think it's a great tool to have in your repertoire and to use depending on your needs.
I recently found the Zed editor that looked very nice but I uninstalled it the moment I saw it had a GPT-4 console. I want nothing to do with AI. I want to do things with my own mind, the help of other human beings, and I'll try my best not to support AI even though it's encroaching on everything.
Certain systems can best be understood as black boxes. You put some commands in and magic happens. Git was not designed to be such a system and early users of git know this.
During the last 5 years, many GUIs have filled in this gap, making it increasingly likely to find people completely stuck because they miss knowledge of the foundations.
Git is a utility to manage an append-only repository of tree-objects, blobs and commits. To help humans, git adds
- human-readable pointers (branches, HEAD, stash)
- an method to incrementally add changes (staging/index/working area)
- a method to append tree-objects, blobs and commits from repository to another
- some commands which alleviate steps in common tasks
These last set of commands cause pain, as users without foundational knowledge, do not realize these commands are compounding many small steps.
Haven't watched the full video, but this looks similar ImHex (https://imhex.werwolv.net/), which also includes a pattern language thing to describe the structure of data. I used it once for a project, and it was useful when it worked, although I ran into some limitations when trying to model container formats.
Maybe it could do that and I just couldn't figure it out at the time, but if you have say a zip file with different file formats, you couldn't tell the language to switch between different structures based on like an index or a header that tells you the format of a subsection. It was a limitation of the pattern language.
I wonder if GNU poke is more advanced in that regard? A tool like this would be super useful for debugging custom binary formats, but some formats can get pretty complex.
* Geometry and the imagination by Hilbert and Cohn-Vossen
* Methods of mathematical physics by Courant and Hilbert
* A comprehensive introduction to differential geometry by Spivak (and its little brothers Calculus and Calculus on manifolds)
* Fourier Analysis by Körner
* Arnold's books on ODE, PDE and mathematical physics are breathtakingly beautiful.
* The shape of space by Weeks
* Solid Shape by Koenderink
* Analyse fonctionnelle by Brézis
* Tristan Needhams "visual" books about complex analysis and differential forms
* Information theory, inference, and learning algorithms by MacKay (great book about probability, plus you can download the .tex source and read the funny comments of the author)
And finally, a very old website which is full of mathematical jewels with an incredibly fresh and clear treatment: https://mathpages.com/ ...I'm in love with the tone of these articles, serious and playful at the same time.
> The author keeps building up to this massively different, otherworldly system, and then just finishes without ever answering.
Yes, it's a weak article.
So, what do mainframes have that microcomputers don't?
- Much more internal checking.
Everything has parity or ECC. CPUs have internal checking. There are interrupts for "CPU made a mistake", and OSs which can take corrective action.
- Channels.
Mainframes have channel controllers. These connect to devices on one end, and the main CPUs and memory on the other. They work in a standardized way, independent of the device. The channel controllers control what data goes to and from the devices. Sometimes they even control what a program can say to a device, so that an application can be given direct device access with access restrictions. This would, for example, let a database talk to a disk partition without going through the OS, but limit it to that partition. The channel controllers determine where peripherals put data in memory. Mainframes have specific I/O instructions for talking to the channel controllers. Drivers in user space have been around since the 1960s.
Minicomputers and microcomputers, on the other hand, once had peripherals directly connected to the memory bus. Programs talked to peripherals by storing and loading values into "device registers". There were no specific I/O instructions built into the CPU.
Some devices accessed memory themselves, called "direct memory access", or DMA. They could write anywhere in memory, a security and reliability problem.
Microcomputer CPUs haven't worked that way for decades. Not since the era of ISA peripherals. But they still pretend to. Programs use store instructions to store into what appears to the CPU is a memory block. But that's really going to what's called the "southbridge", which is logic that sends commands to devices. Those devices offer an interface which appears like memory, but is really piping a command to logic in the device. On the memory access side, the program stores into "device registers" which tell the "northbridge" to set up data access between devices and memory. Sometimes today there's a memory management unit between peripherals and main memory, to control where they can store.
The end result is something more complicated than a mainframe channel, but without the architectural advantages of isolating the devices from the CPU. Attempts have been made to fix this. Intel has tried various types of I/O controllers. But the architecture of Unix/Linux isn't channel-oriented, so it just adds a layer of indirection that makes drivers more difficult.
(Then came GPUs, which started as peripheral devices and gradually took over, but that's a whole other subject.)
- Virtual machine architecture
The first computer that could virtualize itself was the IBM System 360/67, in the 1960s. This worked well enough that all the System/370 machines had virtual machine capability. Unlike the mess in x86 world, the virtual machine and the real machine look very similar. Similar enough that you can load an OS intended for raw hardware into a virtual machine. This even stacks; you can load another copy of the OS inside a VM of the first OS. I've heard of someone layering this 10 deep. The way x86 machines do virtualization required adding a special layer in hardware underneath the main layer, although, over time, it's become more general in x86 land. Arm AArch64 considered virtualization from the start, and may be saner.
This article is informative. I have found that databases in general tend to be less sexy than the front-end apps...especially with the recent cohort of devs. As an old bastard, I would pass on one thing: Realize that any reasonably used database will likely outlast the applications leveraging it. This is especially true the bigger it gets, and the longer it stays in production. That said, if you are influencing the design of a database, imagine years later what someone looking at it might want to know if having to rip all the data out into some other store. Having migrated many legacy systems, I tend to sleep better when I know the data is well-structured and easy to normalize. In those cases, I really don't care so much about the apps. If I can sort out (haha) the data, I worry less about the new apps I need to design. I have been known to bury documentation into for-purpose tables...that way I know that info won't be lost. Export the schema regularly, version it, check it in somewhere. And, if you can, please, limit the use of anything that can hold a NULL. Not every RDBMS handles NULL the same way. Big old databases live a looooong time.
> A few years ago that seemed to start to change. From my perspective, some of the features added to the language to support SwiftUI - specifically property wrappers and function builders - very much felt rushed and forced into the language based on external deadlines.
Yep. If anyone had doubts that the language was no longer the one Lattner designed, SwiftUI should've put the nail in that coffin.
Swift is an imperative, statement-oriented, language. In fact, I get kind of frustrated when writing Swift after spending some time with Rust: I just love writing `let x = if foo { 1 } else { 2 }` or `let x = match foo { ... }`, and it's ugly as hell to try to assign a variable from a switch statement in Swift, etc. BUT, that's okay- I'm almost sure that zero programming languages were written with my opinion in mind, and Swift is Swift.
But, SwiftUI is declarative, which just doesn't work with literally the entire rest of the language. So they added result builders and these weird, magical, annotations just so we can have a UI DSL.
Error handling is now inconsistent and annoying, too. The original approach was to use this quasi-checked-exception syntax where you mark a function as `throws`, and all callers are forced to handle the possibility of failure. The difference between this and Java's checked exceptions is that the specific error type is not part of the signature and therefore the caller only knows that they might get an Error, but not what specific type of Error.
They even have a mechanism for higher-order functions to indicate that they don't throw any of their own errors, but will re-throw errors thrown by function arguments. Clever.
Okay, fine. Pros and cons to that approach, some like it, some don't, etc, whatever. Except then they realized that this approach falls flat in some scenarios (async/promises), so we really just need to go back to returning error values. So they stabilized a Result type.
So, now we need to figure out when we're writing a function if we want to return a Result or make it throw. And, even more annoyingly, Result has a specifically-typed error variant! It's actually a Result<T, E>. Which is it, Swift team? Should immediate callers care about specific error types or not?
Just recently, they landed the async and Actors stuff. Async is fine and great, and is consistent with the imperative syntax and semantics of the language, and it even supports `throws`, IIRC. But Actors? What the hell is that? That's totally out of left field for the rest of the language.
I used to really enjoy Swift in the 2.x to 3.y days, but it really seems like it doesn't even know what it wants to be as a language anymore, which is a real shame- it had a real shot to take the wind out of Rust's sails, IMO (The number one "scary" part of Rust is lifetimes and borrow checker. Swift has CoW structs and auto-ref-counted classes, instead, which can be seen as more appropriate for higher level tasks than writing system libs, etc).
"792 sponsors are funding Homebrew’s work." on github alone, and there are more on the Patreon and donating directly.
Your name is not in the README, so you are on the bottom 4 tiers, they get at most $30/month from you.
For $30 (or less) a month, I don't think it is reasonable to expect them to do extra work to support an a 4th OS version. This is less than half an hour of work at commercial company rates, probably much less.
If they have limited resources, I'd rather them improve support for the modern OSs, instead of spending them on old stuff.
It's hard to store. It leaks away. It has poor energy density by volume (and much of the energy simply goes to compress the damn stuff) - only 3x li-ion, for your trouble. It has a crappy round-trip efficiency - only 50% for water -> electrolysis -> fuel cell. It's just a shitty battery.
The only thing it's got going for it is that it's a way of greenwashing fossil fuels.
> would sqlite really be worse today if you hadn't done your own VCS.
Yes. Fossil is not only the VCS for SQLite, Fossil is also built around SQLite. SQLite is a core component of Fossil. Thus, when I am working on Fossil, I am forced to interact with SQLite as a "user" instead of as a "developer". In geek-speak, it forces me to "eat my own dog food". This, in turn, prompts me to add needed features to SQLite and more generally to make the SQLite interfaces friendlier to application-developers.
One recent example: SQLite version 3.34.0 added the ability to include two or more recursive terms in a Recursive Common Table Expression. (See item 2 in https://www.sqlite.org/releaselog/3_34_0.html and subsequent links.) This feature was added specifically so that I could more easily write SQL statements that would walk the Fossil version history DAG, as described by the https://www.sqlite.org/lang_with.html#rcex3 link.
I did not develop Fossil with this "dogfooding" idea in mind. It was an unanticipated benefit of Fossil. But in the end, I think it might have been the most important benefit of using Fossil instead of some other VCS.
One final lesson that one might be tempted to take is that the kernel is running a terrible risk of malicious patches inserted by actors with rather more skill and resources than the UMN researchers have shown. That could be, but the simple truth of the matter is that regular kernel developers continue to insert bugs at such a rate that there should be little need for malicious actors to add more.
Postgres is better in the I-need-concurrency case -- I think it's the greatest RDBMS that's ever been made and would like someone to prove me wrong some day.
SQLite's amazing too though, when you don't need concurrency (and most websites don't really -- especially the ones that should be scaling vertically instead of horizontally).
> “But nobody writes production applications with SQLite, right?"
We've been doing it for 5 years now. Basic tricks we employ are:
Use PRAGMA user_version for purposes of managing automatic migrations, a. la. Entity Framework. This means you can actually do one better than Microsoft's approach, because you don't need a special unicorn table to store migration info. A simple integer compared with your latest integer and executing SQL in the range is all it takes.
Use PRAGMA synchronous=NORMAL alongside PRAGMA journal_mode=WAL for maximum throughput while supporting most reasonable IT recovery concerns. If you are running your SQLite application on a VM somewhere and have RTO which is satisfied by periodic hot snapshots (which WAL is quite friendly to), this is a more than ideal way to manage recovery of all business data while also giving good throughput to writers. If you are more paranoid than we are, then you can do FULL synchronous for a moderate performance penalty. This would be more for situations where your RTO requires the exact state of the system be recoverable the moment it lost power. We can afford to lose the last few minutes of work without anyone getting yelled at. Some modern virtualization technologies do help a lot in this regard. Running bare metal you need to be a little more careful.
For development & troubleshooting, being able to copy a .db file (even while its in use) is tremendously powerful. I can easily patch up a QA database I mangled with a bad migrator in 5 minutes by stopping the service, pulling the .db local, editing, and pushing it back up. We can also ask our customers to zip up their entire db folder so we can troubleshoot the entire system state.
Being able to use SQLite as our exclusive data store also meant that our software delivery process could be trivialized. We use zero external hosts, even localhost, for our application to be installed or started. We don't even require a runtime exist on the base operating system. Unzip our latest release build to a blank Win2019 server, sc.exe the binary path, net start the service, and it just works. Anyone can deploy our software because it's literally that simple. We didn't even bother to write a script because its a bigger pain in the ass to set powershell execution mode.
So, its not just about the core data storage, but also about the higher-order implications of choosing to use a database solution that can be wholly embedded within your application. Because of decisions like these, we don't have to screw around with things like Docker or Kubernetes.
> I guess I need to go back to doing things the hard way.
The moral of this story is clear but third-party developers for Apple devices don't want to face it. With a few exceptions, most Apple frameworks and application software are proprietary. If Apple's internal source code is deemed to be central to their business, outside developers will probably never get to see it. And if they can't see it, they can't fix and improve it.
If you write application software for Apple devices, you have made a Faustian bargain. You are at the mercy of the whims of Apple Software Engineering; Apple has you by the proverbial balls. If your own code is also proprietary then your customers are in the same vulnerable position, so stop complaining.
I edit a database newsletter – https://dbweekly.com/ – so tend to always have my eyes out for new releases, what's coming along, and what not. And I thought I'd share a few more things that have jumped out at me recently in case anyone's in the mood for spelunking.
1. QuestDB – https://questdb.io/ – is a performance-focused, open-source time-series database that uses SQL. It makes heavy use of SIMD and vectorization for the performance end of things.
2. GridDB - https://griddb.net/en/ - is an in-memory NoSQL time-series database (there's a theme lately with these!) out of Toshiba that was boasting doing 5m writes per second and 60m reads per second on a 20 node cluster recently.
3. MeiliSearch - https://github.com/meilisearch/MeiliSearch – not exactly a database but basically an Elastic-esque search server written in Rust. Seems to have really taken off.
4. Dolt – https://github.com/liquidata-inc/dolt – bills itself as a 'Git for data'. It's relational, speaks SQL, but has version control on everything.
TerminusDB, KVRocks, and ImmuDB also get honorable mentions.
Thanks to everyone here who took a chance on us in the beginning and shared helpful feedback over the years! How to serve startups/developers more effectively at scale is still the main thrust of our product focus. We've fixed and improved a lot of things since we launched here in 2011, but we also still have a lot of work to do. (Both "obvious things we want to fix" and "new functionality we want to build".) I always appreciate hearing from HN users (even if I don't always have time to respond): patrick@stripe.com.
For anyone thinking about what they should work on: I started building developer tools when I was 15 and "tools for creation" is still, IMO, one of the most interesting areas to work in.
> It's weird to me that being considered a "defender of X" could even be a bad thing. That's the process by which we collectively make decisions, it's the basis behind stuff like fair trials for example; the lawyer acting for a defendant is not a bad person.
Except that in fair trials we have the concept of stare decisis, that once something has been decided, it's been decided. We very intentionally do not have the courtroom try to reason something out from first principles every time. We do not defend each person who runs a red light by saying, is it actually bad to run a red light. The cases which do overturn existing legal or social precedent are rare, carefully picked by the lawyers to be as sympathetic as possible (cf. Rosa Parks), and carefully timed to line up with sufficient hope of social consensus having changed around the law.
While it is absolutely your right to say "What if this bad thing is not actually bad," to do so without presenting a novel argument about it, and especially to do so for the sake of being contrarian, is not how we make decisions. You should look at the strongest arguments on both sides. You should privately take the opposing side and then see if you can knock it down.
The arguments Stallman presented were hardly arguments and were not novel at all. They're arguments that have occurred to the people he's arguing against, already. If he wants to seek the truth and not just advocate a side, he could have and should have figured that out. I still believe in his right to free speech (in the sense that I would defend his freedom to speak without government coercion), but I don't think he made a contribution to the discourse that's worth defending at a social level.
