Although there isn’t much to report of late, I thought that it might be appropriate to note a few small developments in my efforts related to L4Re. With travel, distractions, and various irritations intervening, only slow, steady progress was made during August.
Previously, I published a rather long article about operating systems and application environments, but this was not written spontaneously. In fact, it attempts to summarise various perspectives on such topics from the last fifty or so years, discovered as I reviewed the rather plentiful literature that is now readily accessible online. Alongside the distraction of reading historical documents, I had been slowly developing support for running programs in my L4Re-based environment, gradually bringing it to a point where I might be able to explore some more interesting topics.
One topic that overlapped with my last article and various conference talks was that of customising the view of the system a given program might have when it is run. Previous efforts had allowed me to demonstrate programs running and interacting with a filesystem, even one stored on a device such as a microSD card and accessed by hardware booting into L4Re, as opposed to residing in some memory in a QEMU virtual machine. And these programs were themselves granted the privilege of running their own programs. However, all of these programs resided in the same filesystem and also accessed this same filesystem.
Distinct Program Filesystems
What I wanted to do was to allow programs to see a different, customised filesystem instead of the main filesystem. Fortunately, my component architecture largely supported such a plan. When programs are invoked, the process server component supplies a filesystem reference to the newly invoked program, this reference having been the same one that the process server uses itself. To allow the program to see a different filesystem, all that is required is a reference to another filesystem be supplied.
So, the ability is required to configure the process server to utilise a distinct filesystem for invoked programs. After enhancing the process server to propagate a distinct filesystem to created processes, I updated its configuration in the Lua script within L4Re as follows:
l:startv({
caps = {
fsserver = ext2server_paulb, -- this is the filesystem the server uses itself
pipeserver = pipe_server,
prfsserver = ext2server_nested_paulb, -- this is the distinct filesystem for programs
prserver = process_server:svr(),
},
log = { "process", "y" },
},
"rom/process_server", "bin/exec_region_mapper", "prfsserver");
Now, the process server obtains the program or process filesystem from the “prfsserver” capability defined in its environment. This capability or reference can be supplied to each new process created when invoking a program.
Nesting Filesystems
Of course, testing this requires a separate filesystem image to be created and somehow supplied during the initialisation of the system. When prototyping using QEMU on a machine with substantial quantities of memory, it is convenient to just bundle such images up in the payload that is deployed within QEMU, these being exposed as files in a “rom” filesystem by the core L4Re components.
But on “real hardware”, it isn’t necessarily convenient to have separate partitions on a storage device for lots of different filesystems. Instead, we might wish to host filesystem images within the main filesystem, accessing these in a fashion similar to using the loop option with the mount command on Unix-like systems. As in, something like this, mounting “filesystem.fs” at the indicated “mountpoint” location:
mount -o loop filesystem.fs mountpoint
This led to me implementing support for accessing a filesystem stored in a file within a filesystem. In the L4Re build system, my software constructs filesystem images using a simple tool that utilises libext2fs to create an ext2-based filesystem. So, I might have a directory called “docs” containing some documents that is then packed up into a filesystem image called “docs.fs”.
This image might then be placed in a directory that, amongst other content, is packed up into the main filesystem image deployed in the QEMU payload. On “real hardware”, I could take advantage of an existing filesystem on a memory card, copying content there instead of creating an image for the main filesystem. But regardless of the approach, the result would be something like this:
> ls fs
fs
drwxrwxrwx- 1000 1000 1024 2 .
drwxr-xr-x- 0 0 1024 7 ..
-rw-r--r--- 1000 1000 102400 1 docs.fs
Here, “docs.fs” resides inside the “fs” directory provided by the main filesystem.
Files Providing Filesystems
With this embedded filesystem now made available, the matter of providing support for programs to access it largely involved the introduction of a new component acting as a block device. But instead of accessing something like a memory card (or an approximation of one for the purposes of prototyping), this block server accesses a file containing an embedded filesystem though an appropriate filesystem “client” programming interface. Here is the block server being started in the Lua script:
l:startv({
caps = {
blockserver = client_server:svr(),
fsserver = ext2server_paulb,
},
log = { "clntsvr", "y" },
},
-- program, block server capability to provide, memory pages
"rom/client_server", "blockserver", "10");
Then, a filesystem server is configured using the block server defined above, obtaining the nested filesystem from “fs/docs.fs” in the main filesystem to use as its block storage medium:
l:startv({
caps = {
blockserver = client_server,
fsserver = ext2server_nested:svr(),
pipeserver = pipe_server,
},
log = { "ext2svrN", "y" },
},
-- program, server capability, memory pages, filesystem capability to provide
"rom/ext2_server", "blockserver", "fs/docs.fs", "20", "fsserver");
Then, this filesystem server, utilising libext2fs coupled with a driver for a block device, can operate on the filesystem oblivious to what is providing it, which is another component that itself uses libext2fs! Thus, a chain of components can be employed to provide access to files within filesystems, themselves provided by files within other filesystems, and so on, eventually accessing blocks in some kind of storage device. Here, we will satisfy ourselves with just a single level of filesystems within files, however.
So, with the ability to choose a filesystem for new programs and with the ability to acquire a filesystem from the surrounding, main filesystem, it became possible to run a program that now sees a distinct filesystem. For example:
> run bin/ls
drwxr-xr-x- 0 0 1024 4 .
drwxr-xr-x- 0 0 1024 4 ..
drwx------- 0 0 12288 2 lost+found
drwxrwxrwx- 1000 1000 1024 2 docs
[0] Completed with signal 0 value 0
Although a program only sees its own filesystem, it can itself run another program provided from outside. For example, getting “test_systemv” to run “cat”:
> run bin/test_systemv bin/cat docs/COPYING.txt
Running: bin/cat
Licence Agreement
-----------------
All original work in this distribution is covered by the following copyright
and licensing information:
Now, this seems counterintuitive. How does the program invoked from the simple shell environment, “test_systemv”, manage to invoke a program from a directory, “bin”, that is not visible and presumably not accessible to it? This can be explained by the process server. Since the invoked programs are also given a reference to the process server, this letting them start other programs, and since the process server is able to locate programs independently, the invoked programs may supply a program path that may not be accessible to them, but it may be accessible to the process server.
The result is like having some kind of “shadow” filesystem. Programs may be provided by this filesystem and run, but in this arrangement, they may only operate on a distinct filesystem where themselves and other programs may not even be present. Conversely, even if programs are provided in the filesystem visible to a program, they may not be run because the process server may not have access to them. If we wanted to provide an indication of the available programs, we might provide a “bin” directory in each program’s visible filesystem containing files with the names of the available programs, but these files would not need to be the actual programs and “running” them would not actually be running them at all: the shadow filesystem programs would be run instead.
Such trickery is not mandatory, of course. The same filesystem can be visible to programs and the process server that invoked them. But this kind of filesystem shadowing does open up some possibilities that would not normally be available in a conventional environment. Certainly, I imagine that such support could be introduced to everybody’s own favourite operating system, too, but the attraction here is that such experimentation comes at a relatively low level of effort. Moreover, I am not making anyone uncomfortable modifying another system, treading on people’s toes, theatening anyone’s position in the social hierarchy, and generally getting them on the defensive, inviting the inevitable, disrespectful question: “What is it you are trying to do?”
As I noted last time, there isn’t a singular objective here. Instead, the aim is to provide the basis for multiple outcomes, hopefully informative and useful ones. So, in keeping with that agenda, I hope that this update was worth reading.
I have many random VPS and VMs across europe in different providers for reasons.
Two of them, are still running rpm based distro from 2011 and yes 13years later, I have not found the time to migrate them! Needless to say these are still my most stable running linux machines that I have, zero problems, ZERO PROBLEMS and are in production and heavily used every day. Let me write this again in bold: ZERO PROBLEMS.
But as time has come, I want to close some public services and use a mesh VPN for ssh. Tailscale entered the conversation and seems it’s binary works in new and old linux machines too.
long story short, I wanted an init script and with the debian package: dpkg, I could use start-stop-daemon.
Here is the init script:
#!/bin/bash
# ebal, Thu, 08 Aug 2024 14:18:11 +0300
### BEGIN INIT INFO
# Provides: tailscaled
# Required-Start: $local_fs $network $syslog
# Required-Stop: $local_fs $network $syslog
# Default-Start: 2 3 4 5
# Default-Stop: 0 1 6
# Short-Description: tailscaled daemon
# Description: tailscaled daemon
### END INIT INFO
. /etc/rc.d/init.d/functions
prog="tailscaled"
DAEMON="/usr/local/bin/tailscaled"
PIDFILE="/var/run/tailscaled.pid"
test -x $DAEMON || exit 0
case "$1" in
start)
echo "Starting ${prog} ..."
start-stop-daemon --start --background --pidfile $PIDFILE --make-pidfile --startas $DAEMON --
RETVAL=$?
;;
stop)
echo "Stopping ${prog} ..."
if [ -f ${PIDFILE} ]; then
start-stop-daemon --stop --pidfile $PIDFILE --retry 5 --startas ${DAEMON} -- -cleanup
rm -f ${PIDFILE} > /dev/null 2>&1
fi
RETVAL=$?
;;
status)
start-stop-daemon --status --pidfile ${PIDFILE}
status $prog
RETVAL=$?
;;
*)
echo "Usage: /etc/init.d/tailscaled {start|stop|status}"
RETVAL=1
;;
esac
exit ${RETVAL}
an example:
[root@kvm ~]# /etc/init.d/tailscaled start
Starting tailscaled ...
[root@kvm ~]# /etc/init.d/tailscaled status
tailscaled (pid 29101) is running...
[root@kvm ~]# find /var/ -type f -name "tailscale*pid"
/var/run/tailscaled.pid
[root@kvm ~]# cat /var/run/tailscaled.pid
29101
[root@kvm ~]# ps -e fuwww | grep -i tailscaled
root 29400 0.0 0.0 103320 880 pts/0 S+ 16:49 0:00 _ grep --color -i tailscaled
root 29101 2.0 0.7 1250440 32180 ? Sl 16:48 0:00 /usr/local/bin/tailscaled
[root@kvm ~]# tailscale up
[root@kvm ~]# tailscale set -ssh
[root@kvm ~]# /etc/init.d/tailscaled stop
Stopping tailscaled ...
[root@kvm ~]# /etc/init.d/tailscaled status
tailscaled is stopped
[root@kvm ~]# /etc/init.d/tailscaled stop
Stopping tailscaled ...
[root@kvm ~]# /etc/init.d/tailscaled start
Starting tailscaled ...
[root@kvm ~]# /etc/init.d/tailscaled start
Starting tailscaled ...
process already running.
[root@kvm ~]# /etc/init.d/tailscaled status
tailscaled (pid 29552) is running...
Tag(s):
centos6,
tailscale,
init
As noted previously, two of my interests in recent times have been computing history and microkernel-based operating systems. Having perused academic and commercial literature in the computing field a fair amount over the last few years, I experienced some feelings of familiarity when looking at the schedule for FOSDEM, which took place earlier in the year, brought about when encountering a talk in the “microkernel and component-based OS” developer room: “A microkernel-based orchestrator for distributed Internet services?”
In this talk’s abstract, mentions of the complexity of current Linux-based container solutions led me to consider the role of containers and virtual machines. In doing so, it brought back a recollection of a paper published in 1996, “Microkernels Meet Recursive Virtual Machines”, describing a microkernel-based system architecture called Fluke. When that paper was published, I was just starting out in my career and preoccupied with other things. It was only in pursuing those interests of mine that it came to my attention more recently.
It turned out that there were others at FOSDEM with similar concerns. Liam Proven, who regularly writes about computing history and alternative operating systems, gave a talk, “One way forward: finding a path to what comes after Unix”, that combined observations about the state of the computing industry, the evolution of Unix, and the possibilities of revisiting systems such as Plan 9 to better inform current and future development paths. This talk has since been summarised in four articles, concluding with “A path out of bloat: A Linux built for VMs” that links back to the earlier parts.
Both of these talks noted that in attempting to deploy applications and services, typically for Internet use, practitioners are now having to put down new layers of functionality to mitigate or work around limitations in existing layers. In other words, they start out with an operating system, typically based on Linux, that provides a range of features including support for multiple users and the ability to run software in an environment largely confined to the purview of each user, but end up discarding most of this built-in support as they bundle up their software within such things as containers or virtual machines, where the software can pretend that it has access to a complete environment, often running under the control of one or more specific user identities within that environment.
With all this going on, people should be questioning why they need to put one bundle of software (their applications) inside another substantial bundle of software (an operating system running in a container or virtual machine), only to deploy that inside yet another substantial bundle of software (an operating system running on actual hardware). Computing resources may be the cheapest they have ever been, supply chain fluctuations notwithstanding, but there are plenty of other concerns about building up levels of complexity in systems that should prevent us from using cheap computing as an excuse for business as usual.
A Quick Historical Review
In the early years of electronic computing, each machine would be dedicated to running a single program uninterrupted until completion, producing its results and then being set up for the execution of a new program. In this era, one could presumably regard a computer simply as the means to perform a given computation, hence the name.
However, as technology progressed, it became apparent that dedicating a machine to a single program in this way utilised computing resources inefficiently. When programs needed to access relatively slow peripheral devices such as reading data from, or writing data to, storage devices, the instruction processing unit would be left idle for significant amounts of cumulative time. Thus, solutions were developed to allow multiple programs to reside in the machine at the same time. If a running program had paused to allow data to transferred to or from storage, another program might have been given a chance to run until it also found itself needing to wait for those peripherals.
In such systems, each program can no longer truly consider itself as the sole occupant or user of the machine. However, there is an attraction in allowing programs to be written in such a way that they might be able to ignore or overlook this need to share a computer with other programs. Thus, the notion of a more abstract computing environment begins to take shape: a program may believe that it is accessing a particular device, but the underlying machine operating software might direct the program’s requests to a device of its own choosing, presenting an illusion to the program.
Although these large, expensive computer systems then evolved to provide “multiprogramming” support, multitasking, virtual memory, and virtual machine environments, it is worth recalling the evolution of computers at the other end of the price and size scale, starting with the emergence of microcomputers from the 1970s onwards. Constrained by the availability of affordable semiconductor components, these small systems at first tended to limit themselves to modest computational activities, running one program at a time, perhaps punctuated occasionally by interrupts allowing the machine operating software to update the display or perform other housekeeping tasks.
As microcomputers became more sophisticated, so expectations of the functionality they might deliver also became more sophisticated. Users of many of the earlier microcomputers might have run one application or environment at a time, such as a BASIC interpreter, a game, or a word processor, and what passed for an operating system would often only really permit a single application to be active at once. A notable exception in the early 1980s was Microware’s OS-9, which sought to replicate the Unix environment within the confines of 8-bit microcomputer architecture, later ported to the Motorola 68000 and used in, amongst other things, Philips’ CD-i players.
OS-9 offered the promise of something like Unix on fairly affordable hardware, but users of systems with more pedestrian software also started to see the need for capabilities like multitasking. Even though the dominant model of microcomputing, perpetuated by the likes of MS-DOS, had involved running one application to do something, then exiting that application and running another, it quickly became apparent that users themselves had multitasking impulses and were inconvenienced by having to finish off something, even temporarily, switch to another application offering different facilities, and then switch back again to resume their work.
Thus, the TSR and the desk accessory were born, even finding a place on systems like the Apple Macintosh, whose user interface gave the impression of multitasking functionality and allowed switching between applications, even though only a single application could, in general, run at a time. Later, Apple introduced MultiFinder with the more limited cooperative flavour of multitasking, in contrast to systems already offering preemptive multitasking of applications in their graphical environments. People may feel the compulsion to mention the Commodore Amiga in such contexts, but a slightly more familiar system from a modern perspective would be the Torch Triple X workstation with its OpenTop graphical environment running on top of Unix.
The Language System Phenomenon
And so, the upper and lower ends of the computing market converged on expectations that users might be able to run many programs at a time within their computers. But the character of these expectations might have been coloured differently from the prior experiences of each group. Traditional computer users might well have framed the environment of their programs in terms of earlier machines and environments, regarding multitasking as a convenience but valuing compatibility above all else.
At the lower end of the market, however, users were looking to embrace higher-level languages such as Pascal and Modula-2, these being cumbersome on early microprocessor systems but gradually becoming more accessible with the introduction of later systems with more memory, disk storage and processors more amenable to running such languages. Indeed, the notion of the language environment emerged, such as UCSD Pascal, accompanied by the portable code environment, such as the p-System hosting the UCSD Pascal environment, emphasising portability and defining a machine detached from the underlying hardware implementation.
Although the p-System could host other languages, it became closely associated with Pascal, largely by being the means through which Pascal could be propagated to different computer systems. While 8-bit microcomputers like the BBC Micro struggled with something as sophisticated as the p-System, even when enhanced with a second processor and more memory, more powerful machines could more readily bear the weight of the p-System, even prompting some to suggest at one time that it was “becoming the de facto standard operating system on the 68000”, supplied as standard on 68000-based machines like the Sage II and Sage IV.
Such language environments became prominent for a while, Lisp and Smalltalk being particularly fashionable, and with the emergence of the workstation concept, new and divergent paths were forged for a while. Liam Proven previously presented Wirth’s Oberon system as an example of a concise, efficient, coherent environment that might still inform the technological direction we might wish to take today. Although potentially liberating, such environments were also constraining in that their technological homogeneity – the imposition of a particular language or runtime – tended to exclude applications that users might have wanted to run. And although Pascal, Oberon, Lisp or Smalltalk might have their adherents, they do not all appeal to everyone.
Indeed, during the 1980s and even today, applications sell systems. There are plenty of cases where manufacturers ploughed their own furrow, believing that customers would see the merits in their particular set of technologies and be persuaded into adopting those instead of deploying the products they had in mind, only to see the customers choose platforms that supported the products and technologies that they really wanted. Sometimes, vendors doubled down on customisations to their platforms, touting the benefits of custom microcode to run particular programs or environments, ignoring that customers often wanted more generally useful solutions, not specialised products that would become uncompetitive and obsolete as technology more broadly progressed.
For all their elegance, language-oriented environments risked becoming isolated enclaves appealing only to their existing users: an audience who might forgive and even defend the deficiencies of their chosen systems. For example, image-based persistence, where software could be developed in a live environment and “persisted” or captured in an image or “world” for later use or deployment, remains a tantalising approach to software development that sometimes appeals to outsiders, but one can argue that it also brings risks in terms of reproducibility around software development and deployment.
If this sounds familiar to anyone old enough to remember the end of the 1990s and the early years of this century, probing this familiarity may bring to mind the Java bandwagon that rolled across the industry. This caused companies to revamp their product lines, researchers to shelve their existing projects, developers to encounter hostility towards the dependable technologies they were already using, and users to suffer the mediocre applications and user interfaces that all of this upheaval brought with it.
Interesting research, such as that around Fluke and similar projects, was seemingly deprioritised in favour of efforts that presumably attempted to demonstrate “research relevance” in the face of this emerging, everything-in-Java paradigm with its “religious overtones”. And yet, commercial application of supposedly viable “pure Java” environments struggled in the face of abysmal performance and usability.
The Nature of the Machine
Users do apparently value heterogeneity or diversity in their computing environments, to be able to mix and match their chosen applications, components and technologies. Today’s mass-market computers may have evolved from the microcomputers of earlier times, accumulating workstation, minicomputer and mainframe technologies along the way, and they may have incorporated largely sensible solutions in doing so, but it can still be worthwhile reviewing how high-end systems of earlier times addressed issues of deploying different kinds of functionality safely within the same system.
When “multiprogramming” became an essential part of most system vendors’ portfolios, the notion of a “virtual machine” emerged, this being the vehicle through which a user’s programs could operate or experience the machine while sharing it with other programs. Today, using our minicomputer or Unix-inspired operating systems, we think of a virtual machine as something rather substantial, potentially simulating an entire system with all its peculiarities, but other interpretations of the term were once in common circulation.
In the era when the mainframe reigned supreme, their vendors differed in their definitions of a virtual machine. International Computers Limited (ICL) revamped their product range in the 1970s in an attempt to compete with IBM, introducing their VME or Virtual Machine Environment operating system to run on their 2900 series computers. Perusing the literature related to VME reveals a system that emphasises different concepts to those we might recognise from Unix, even though there are also many similarities that are perhaps obscured by differences in terminology. Where we are able to contrast the different worlds of VME and Unix, however, is in the way that ICL chose to provide a Unix environment for VME.
As the end of the 1980s approached, once dominant suppliers with their closed software and solution ecosystems started to get awkward questions about Unix and “open systems”. The less well-advised, like Norway’s rising star, Norsk Data, refused to seriously engage with such trends, believing their own mythology of technological superiority, until it was too late to convince their customers switching to other platforms that they had suddenly realised that this Unix thing was worthwhile after all. ICL, meanwhile, only tentatively delivered a Unix solution for their top-of-the-line systems.
Six years after ICL’s Series 39 mainframe range was released, and after years of making a prior solution selectively available, ICL’s VME/X product was delivered, offering a hosted Unix environment within VME, broadly comparable with Amdahl’s UTS and IBM’s IX/370. Eventually, VME/X was rolled into OpenVME, acknowledging “open systems” rather like Digital’s OpenVMS, all without actually being open, as one of my fellow students once joked. Nevertheless, VME/X offers an insight into what a virtual machine is in VME and how ICL managed to map Unix concepts into VME.
Reading VME documentation, one gets the impression that, fundamentally, a virtual machine in the VME sense is really about giving an environment to a particular user, as opposed to a particular program. Each environment has its own private memory regions, inaccessible to other virtual machines, along with other regions that may be shared between virtual machines. Within each environment, a number of processes can be present, but unlike Unix processes, these are simply execution contexts or, in Unix and more general terms, threads.
Since the process is the principal abstraction in Unix through which memory is partitioned, it is curious that in VME/X, the choice was made to not map Unix processes to VME virtual machines. Instead, each “terminal user”, each “batch job” (not exactly a Unix concept), as well as “certain daemons” were given their own virtual machines. And when creating a new Unix process, instead of creating a new virtual machine, VME/X would in general create a new VME process, seemingly allowing each user’s processes to reside within the same environment and to potentially access each other’s memory. Only when privilege or user considerations applied, would a new process be initiated in a new virtual machine.
Stranger than this, however, is VME’s apparent inability to run multiple processes concurrently within the same virtual machine, even on multiprocessor systems, although processes in different virtual machines could run concurrently. For one process to suspend execution and yield to another in the same virtual machine, a special “process-switching call” instruction was apparently needed, providing a mechanism like that of green threads or fibers in other systems. However, I could imagine that this could have provided a mechanism for concealing each process’s memory regions from others by using this call to initiate a reconfiguration of the memory segments available in the virtual machine.
I have not studied earlier ICL systems, but it would not surprise me if the limitations of this environment resembled those of earlier generations of products, where programs might have needed to share a physical machine graciously. Thus, the heritage of the system and the expectations of its users from earlier times appear to have survived to influence the capabilities of this particular system. Yet, this Unix implementation was actually certified as compliant with the X/Open Portability Guide specifications, initially XPG3, and was apparently the first system to have XPG4 base compliance.
Partitioning by User
A tour of a system that might seem alien or archaic to some might seem self-indulgent, but it raises a few useful thoughts about how systems may be partitioned and the sophistication of such partitioning. For instance, VME seems to have emphasised partitioning by user, and this approach is a familiar and mature one with Unix systems, too. Traditionally, dedicated user accounts have been set up to run collections of associated programs. Web servers often tend to run in a dedicated account, typically named “apache” or “httpd”. Mail servers and database servers also tend to follow such conventions. Even Android has used distinct user accounts to isolate applications from each other.
Of course, when partitioning functionality by user in Unix systems, one must remember that all of the processes involved are isolated from each other, in that they do not share memory inadvertently, and that the user identity involved is merely associated with these processes: it does not provide a container for them in its own right. Indeed, the user abstraction is simply the way that access by these processes to the rest of the system is controlled, largely mediated by the filesystem. Thus, any such partitioning arrangement brings the permissions and access control mechanisms into consideration.
In the simplest cases, such as a Web server needing to be able to read some files, the necessary adjustments to groups or even the introduction of access control lists can be sufficient to confine the Web server to its own territory while allowing other users and programs to interact with it conveniently. For example, Web pages can be published and updated by adding, removing and changing files in the Web site directories given appropriate permissions. However, it is when considering the combination of servers or services, each traditionally operating under their own account, that administrators start to consider alternatives to such traditional approaches.
Let us consider how we might deploy multiple Web applications in a shared hosting environment. Clearly, it would be desirable to give all of these applications distinct user accounts so that they would not be able to interfere with each other’s files. In a traditional shared hosting environment, the Web application software itself might be provided centrally, with all instances of an application relying on the same particular version of the software. But as soon as the requirements for the different instances start to diverge – requiring newer or older versions of various components – they become unable to rely entirely on the centrally provided software, and alternative mechanisms for deploying divergent components need to be introduced.
To a customer of such a service having divergent requirements, the provider will suggest various recipes for installing new software, often involving language-specific packaging or building from source, with compilers available to help out. The packaging system of the underlying software distribution is then mostly being used by the provider itself to keep the operating system and core facilities updated. This then leads people to conclude that distribution packaging is too inflexible, and this conclusion has led people in numerous directions to try and address the apparently unmet needs of the market, as well as to try and pitch their own particular technology as the industry’s latest silver bullet.
There is arguably nothing to stop anyone deploying applications inside a user’s home directory or a subdirectory of the home directory, with /home/user/etc being the place where common configuration files are stored, /home/user/var being used for some kind of coordination, and so on. Many applications can be configured to work in another location. One problem is that this configuration is sometimes fixed within the software when it is built, meaning that generic packages cannot be produced and deployed in arbitrary locations.
Another is that many of the administrative mechanisms in Unix-like systems favour the superuser, rely on operating on software configured for specific, centralised locations, and only really work at the whole-machine level with a global process table, a global set of user identities, and so on. Although some tools support user-level activities, like the traditional cron utility, scheduling jobs on behalf of users, as far as I know, traditional Unix-like systems have never really let users define and run their own services along the same lines as is done for the whole system, administered by the superuser.
Partitioning by Container
If one still wants to use nicely distribution-packaged software on a per-user, per-customer or per-application basis, what tends to happen is that an environment is constructed that resembles the full machine environment, with this kind of environment existing in potentially many instances on the same system. In other words, just so that, say, a Debian package can be installed independently of the host system and any of its other users, an environment is constructed that provides directories like /usr, /var, /etc, and so on, allowing the packaging system to do its work and to provide the illusion of a complete, autonomous machine.
Within what might be called the Unix traditions, a few approaches exist to provide this illusion to a greater or lesser degree. The chroot mechanism, for instance, permits the execution of programs that are generally only able to see a section of the complete filesystem on a machine, located at a “changed root” in the full filesystem. By populating this part of the filesystem with files that would normally be found at the top level or root of the normal filesystem, programs invoked via the chroot mechanism are able to reference these files as if they were in their normal places.
Various limitations in the scope of chroot led to the development of such technologies as jails, Linux-VServer and numerous others, going beyond filesystem support for isolating processes, and providing a more comprehensive illusion of a distinct machine. Here, systems like Plan 9 showed how the Unix tradition might have evolved to support such needs, with Linux and other systems borrowing ideas such as namespaces and applying them in various, sometimes clumsy, ways to support the configuration of program execution environments.
Going further, technologies exist to practically simulate the experience of an entirely separate machine, these often bearing the “virtual machine” label in the vocabulary of our current era. A prime example of such a technology is KVM, available on Linux with the right kind of processor, which allows entire operating systems to run within another. Using a virtual machine solution of this nature is something of a luxury option for an application needing its own environment, being able to have precisely the software configuration of its choosing right down to the level of the kernel. One disadvantage of such full-fat virtual machines is the amount of extra software involved and those layers upon layers of programs and mechanisms, all requiring management and integration.
Some might argue for solutions where the host environment does very little and where everything of substance is done in one kind of virtual machine or other. But if all the virtual machines are being used to run the same general technology, such as flavours of Linux, one has to wonder whether it is worth keeping a distinct hypervisor technology around. That might explain the emergence of KVM as an attempt to have Linux act as a kind of hypervisor platform, but it does not excuse a situation where the hosting of entire systems is done in preference to having a more configurable way of deploying applications within Linux itself.
Some adherents of hypervisor technologies advocate the use of unikernels as a way of deploying lightweight systems on top of hypervisors, specialised to particular applications. Such approaches seem reminiscent of embedded application deployment, with entire systems being built and tuned for precisely one job: useful for some domains but not generally applicable or particularly flexible. And it all feels like the operating system is just being reinvented in a suboptimal, ad-hoc fashion. (Unikernels seem to feature prominently in the “microkernel and component-based OS” developer room at FOSDEM these days.)
Then there is the approach advocated in Liam Proven’s talk, of stripping down an operating system for hypervisor deployment, which would need to offer a degree of extra flexibility to be more viable than a unikernel approach, at least when applied to the same kinds of problems. Of course, this pushes hardware support out of the operating system and into the realm of the hypervisor, which could be beneficial if done well, or it could imperil support for numerous hardware platforms and devices due to numerous technological, economic and social reasons. Liam advocates pushing filesystem support out of the kernel, and potentially out of the operating system as well, although it is not clear what would then need to take up that burden and actually offer filesystem facilities.
Some Reflections
This is where we may return to those complaints about the complexity of modern hosting frameworks. That a need for total flexibility in every application’s software stack presents significant administrative challenges. But in considering the nature of the virtual machine in its historical forms, we might re-evaluate what kind of environment software really needs.
In my university studies, a project of mine investigated a relatively hot topic at the time: mobile software agents. One conclusion I drew from the effort was that programs could be written to use a set of well-defined interfaces and to potentially cooperate with other programs, without thousands of operating system files littering their shared environment. Naturally, such programs would not be running by magic: they would need to be supported by infrastructure that allows them to be loaded and executed, but all of this infrastructure can be maintained outside the environment seen by these programs.
At the time, I relied upon the Python language runtime for my agent programs with its promising but eventually inadequate support for safe execution to prevent programs from seeing the external machine environment. Most agent frameworks during this era were based on particular language technologies, and the emergence of Java only intensified the industry’s focus on this kind of approach, naturally emphasising Java, although Inferno also arrived at around this time and offered a promising, somewhat broader foundation for such work than the Java Virtual Machine.
In the third part of his article series, Liam Proven notes that Plan 9, Inferno’s predecessor, is able to provide a system where “every process is in a container” by providing support for customisable process namespaces. Certainly, one can argue that Plan 9 and Inferno have been rather overlooked in recent years, particularly by the industry mainstream. He goes on to claim that such functionality, potentially desirable in application hosting environments, “makes the defining features of microkernels somewhat irrelevant”. Here I cannot really agree: what microkernels actually facilitate goes beyond what a particular operating system can do and how it has been designed.
A microkernel-based approach not only affords the opportunity to define the mechanisms of any resulting system, but it also provides the ability to define multiple sets of mechanisms, all of them potentially available at once, allowing them to be investigated, compared, and even combined. For example, Linux retains the notion of a user of the system, maintaining a global registry of such users, and even with notionally distinct sets of users provided by user namespaces, cumbersome mappings are involved to relate those namespace users back to this global registry. In a truly configurable system, there can be multiple user authorities, each being accessible by an arbitrary selection of components, and some components can be left entirely unaware of the notion of a user whatsoever.
Back in the 1990s, much coverage was given to the notion of operating system personalities. That various products would, for example, support DOS or Windows applications as well as Macintosh ones or Unix ones or OS/2 ones. Whether the user interface would reflect this kind of personality on a global level or not probably kept some usability professionals busy, and I recall one of my university classmates talking about a system where it was apparently possible to switch between Windows or maybe OS/2 and Macintosh desktops with a key combination. Since his father was working at IBM, if I remember correctly, that could have been an incarnation of IBM’s Workplace OS.
Other efforts were made to support multiple personalities in the same system, potentially in a more flexible way than having multiple separate sessions, and certainly more flexible than just bundling up, virtualising or emulating the corresponding environments. Digital investigated the porting of VMS functionality to an environment based on the Mach 3.0 microkernel and associated BSD Unix facilities. Had Digital eventually adopted a form of OSF/1 based on Mach 3.0, it could have conceivably provided a single system running Unix and VMS software alongside each other, sharing various common facilities.
Regardless of one’s feelings about Mach 3.0, whether one’s view of microkernels is formed from impressions of an infamous newsgroup argument from over thirty years ago, or whether it considers some of the developments in the years since, combining disparate technologies in a coherent fashion within the same system must surely be a desirable prospect. Being able to do so without piling up entire systems on top of each other and drilling holes between the layers seems like a particularly desirable thing to do.
A flexible, configurable environment should appeal to those in the same position as the FOSDEM presenter wishing to solve his hosting problems with pruned-down software stacks, as well as appealing to anyone with their own unrealised ambitions for things like mobile software agents. Naturally, such a configurable environment would come with its own administrative overheads, like the need to build and package applications for deployment in more minimal environments, and the need to keep software updated once deployed. Some of that kind of work should arguably get done under the auspices of existing distribution frameworks and initiatives, as opposed to having random bundles of software pushed to various container “hubs” posing as semi-official images, all the while weighing down the Internet with gigabytes of data constantly scurrying hither and thither.
This article does not propose any specific solution or roadmap for any of this beyond saying that something should indeed be done, and that microkernel-based environments, instead of seeking to reproduce Unix or Windows all over again, might usefully be able to provide remedies that we might consider. And with that, I suppose I should get back to my own experiments in this area.
Make sure you commit anything you want to end up in the KDE Gear 24.08 releases to themNext Dates July 25, 2024: 24.08 Freeze and Beta (24.07.80) tag & releaseAugust 8, 2024: 24.08 RC (24.07.90) Tagging and ReleaseAugust 15, 2024: 24.08 TaggingAugust 22, 2024: 24.08 Releasehttps://community.kde.org/Schedules/KDE_Gear_24.08_Schedule
AWS AppConfig service it’s useful for feature flag functionality, you can access it directly via API but this is not the suggested method, for production workload it’s a best practice to use the provided agent. If you are using AppConfig on Kubernetes or EKS you should add the appconfig-agent to your deployment by adding:
apiVersion: apps/v1
kind: Deployment
metadata:
name: my-app
namespace: my-namespace
labels:
app: my-application-label
spec:
replicas: 1
selector:
matchLabels:
app: my-application-label
template:
metadata:
labels:
app: my-application-label
spec:
containers:
- name: my-app
image: my-repo/my-image
imagePullPolicy: IfNotPresent
- name: appconfig-agent
image: public.ecr.aws/aws-appconfig/aws-appconfig-agent:2.x
ports:
- name: http
containerPort: 2772
protocol: TCP
env:
- name: SERVICE_REGION
value: region
imagePullPolicy: IfNotPresent
This method will work but in some edge cases you could “randomly” get an exception like this:
cURL error 7: Failed to connect to localhost port 2772 after 0 ms: Connection refused (see https://curl.haxx.se/libcurl/c/libcurl-errors.html) for http://localhost:2772/applications/APPLICATION_NAME/environments/ENVIRONMENT_NAME/configurations/CONFIGURATION_NAME
If you take a look at the logs you could notice that the AppConfig agent has been explicitly shut down:
[appconfig agent] INFO shutdown complete (actual duration: 50ms)
[appconfig agent] INFO received terminated signal, shutting down
[appconfig agent] INFO shutting down in 50ms
[appconfig agent] INFO stopping server on localhost:2772
digging into the logs you could notice that the master container is still working for some seconds after the appconfig-agent has been shut down, that’s the problem! appconfig-agent is very fast to shut down, if your primary container is still working when appconfig has been shut down, your primary container will not be able to connect to the agent and you will get the error.
How to make sure that appconfig-agent is always active in a deployment? the new Sidecar Container feature, added in the recent 1.29 Kubernetes release, is a perfect fit: the container in the sidecar (appconfig-agent) will be the first to start and the last to stop, your primary container will always find the sidecar ready.
Modify the deployment this way:
apiVersion: apps/v1
kind: Deployment
metadata:
name: my-app
namespace: my-namespace
labels:
app: my-application-label
spec:
replicas: 1
selector:
matchLabels:
app: my-application-label
template:
metadata:
labels:
app: my-application-label
spec:
containers:
- name: my-app
image: my-repo/my-image
imagePullPolicy: IfNotPresent
initContainers:
- name: appconfig-agent
image: public.ecr.aws/aws-appconfig/aws-appconfig-agent:2.x
restartPolicy: Always
ports:
- name: http
containerPort: 2772
protocol: TCP
env:
- name: SERVICE_REGION
value: region
imagePullPolicy: IfNotPresent
This is the release schedule the release team agreed on https://community.kde.org/Schedules/KDE_Gear_24.08_ScheduleDependency freeze is in around 4 weeks (July 18) and feature freeze one after that. Get your stuff ready!
If you're looking for an isolated and straightforward way to start contributing to KDE, you're in the right place. At KDE, we use fuzzing via oss-fuzz to try to ensure our libraries are robust against broken inputs. Here's how you can help us in this essential task.What is Fuzzing?Fuzzing involves feeding "random" [1] data into our code to check its robustness against invalid or unexpected inputs. This is crucial for ensuring the security and stability of applications that process data without direct user control.Why is Fuzzing Important?Imagine receiving an image via email, saving it to your disk, and opening it in Dolphin. This will make Dolphin create a thumbnail of the image. If the image is corrupted and our image plugin code isn't robust, the best-case scenario is that Dolphin crashes. In the worst case, it could lead to a security breach. Hence, fuzzing helps prevent such vulnerabilities.How You Can Help:We need to update the build of KDE libraries in oss-fuzz to use Qt6. This task could be challenging because it involves static compilation and ensuring the correct flags are passed for all compilation units.Steps to Contribute:Start with karchive Project Download oss-fuzz and go into the karchive subfolder.Update the Dockerfile to download Qt from the dev branch and KDE Frameworks from the master branch.Update build.sh Script:Modify the build.sh script to compile Qt6 (this will be harder since it involves moving from qmake to cmake) and KDE Frameworks 6.Check karchive_fuzzer.cc:This file might need updates, but they should be relatively easy.At the top of karchive_fuzzer.cc, you'll find a comment with the three commands that oss-fuzz runs. Use these to test the image building, fuzzer building, and running processes.Need Help?If you have questions or need assistance, please contact me at aacid@kde.org or ping me on Matrix at @tsdgeos:kde.orgNote:[1] Smart fuzzing engines don't generate purely random data. They use semi-random and semi-smart techniques to efficiently find issues in the code.
Since my last update, I have been able to spend some time gradually broadening and hopefully improving the support for classic programming interfaces in my L4Re-based experiments, centred around a standard C library implementation based on Newlib. Of course, there were some frustrations experienced along the way, and much remains to be done, not only in terms of new functionality that will need to be added, but also verification and correction of the existing functionality as I come to realise that I have made mistakes, these inevitably leading to new frustrations.
One area I previously identified for broadened support was that of process creation and the ability to allow programs to start other programs. This necessitated a review of the standard C process control functions, which are deliberately abstracted from the operating system and are much simpler and more constrained than those found in the unistd.h file that Unix programmers might be more familiar with. The traditional Unix functions are very much tied up with the Unix process model, and there are some arguments to be made that despite being “standard”, these functions are a distraction and, in various respects, undesirable from a software architecture perspective, for both applications and the operating systems that run them.
So, ignoring the idea that I might support the likes of execl, execv, fork, and so on, I returned to consideration of the much more limited system function that is part of the C language standards, this simply running an abstract command provided by a character string and returning a result code when the command has completed:
int system(const char *command);
To any casual application programmer, this all sounds completely reasonable: they embed a command in their code that is then presented to “the system”, which runs the commands and hands back a result or status code. But those of us who are accustomed to running commands at the shell and in our own programs might already be picking apart this simple situation.
First of all, “the system” needs to have what the C standards documentation calls a “command processor”. In fact, even Unix standardisation efforts have adopted the term, despite the Linux manual pages referring to “the shell”. But at this point, my own system does not have a shell or a command processor, instead providing only a process server that manages the creation of new processes. And my process server deals with arrays or “vectors” of strings that comprise a command to be used to run a given program, configured by a sequence of arguments or parameters.
Indeed, this brings us to some other matters that may be familiar to anyone who has had the need to run commands from within programs: that of parameterising command invocations by introducing our own command argument values; and that of making sure that the representation of the program name and its arguments do not cause the shell to misinterpret these elements, by letting an errant space character break the program name into two, for instance. When dealing only with command strings, matters of quoting and tokenisation enter the picture, making the exercise very messy indeed.
So, our common experience has provided us with a very good reason to follow the lead of the classic execv Unix function and to avoid the representational issues associated with command string processing. In this regard, the Python standard library has managed to show the way in some respects, introducing the subprocess module which features interfaces that are equivalent to functions like system and popen, supporting the use of both command strings and lists of command elements to represent the invoked command.
Oddly, however, nobody seems to provide a “vector” version of the system function at the C language level, but it seemed to be the most natural interface I might provide in my own system:
int systemv(int argc, const char *argv[]);
I imagine that those doing low-level process creation in a Unix-style environment would be content to use the exec family of functions, probably in conjunction with the fork function, precisely because a function like execv “shall replace the current process image with a new process image”, as the documentation states. Obviously, replacing the current process isn’t helpful when implementing the system function because it effectively terminates the calling program, whereas the system function is meant to allow the program to continue after command completion. So, fork has to get involved somehow.
The Flow of Convention
I get the impression that people venturing along a similar path to mine are often led down the trail of compatibility with the systems that have gone before, usually tempted by the idea that existing applications will eventually be content to run on their system without significant modification, and thus an implementer will be able to appeal to an established audience. In this case, the temptation is there to support the fork function, the exec semantics, and to go with the flow of convention. And sometimes, a technical obstacle seems like a challenge to be met, to show that an implementation can provide support for existing software if it needs or wants to.
Then again, having seen situations where software is weighed down by the extra complexity of features that people believe it should have, some temptations are best resisted, perhaps with a robust justification for leaving out any particular supposedly desirable feature. One of my valued correspondents pointed me to a paper by some researchers that provides a robust argument for excluding fork and for promoting alternatives. Those alternatives have their shortcomings, as noted in the paper, and they seem rather complicated when considering simple situations like merely creating a completely separate process and running a new program in it.
Of course, there may still be complexity in doing simple things. One troublesome area was that of what might happen to the input and output streams of a process that creates another one: should the new process be able to receive the input that has been sent to the creating process, and should it be able to send its output to the recipient of the creating process’s output? For something like system or systemv, the initial “obvious” answer might be the total isolation of the created process from any existing input, but this limits the usefulness of such functions. It should arguably be possible to invoke system or systemv within a program that is accepting input as part of a pipeline, and for a process created by these functions to assume the input processing role transparently.
Indeed, the Unix world’s standards documentation for system extends the C standard to assert that the system function should behave like a combination of fork and execl, invoking the shell utility, sh, to initiate the program indicated in the call to system. It all sounds a bit prescriptive, but I suppose that what it largely means is that the input and output streams should be passed to the initiated program. A less prescriptive standard might have said that, of course, but who knows what kind of vendor lobbying went on to avoid having to modify the behaviour of those vendors’ existing products?
This leads to the awkward problem of dealing with the state of an input stream when such a stream is passed to another process. If the creating process has already read part of a stream, we need the newly created process to be aware of the extent of consumed data so that it may only read unconsumed data itself. Similarly, the newly created process must be able to append output to the existing output stream instead of overwriting any data that has already been written. And when the created process terminates, we need the creating process to synchronise its own view of the input and output streams. Such exercises are troublesome but necessary to provide predictable behaviour at higher levels in the system.
Some Room for Improvement
Another function that deserves revisiting is the popen function which either employs a dedicated output stream to capture the output of a created process within a program, or a dedicated input stream so that a program can feed the process with data it has prepared. The mode indicates what kind of stream the function will provide: “r” yields an output stream passing data out of the process, “w” yields an input stream passing data into the process.
FILE *popen(const char *command, const char *mode);
This function is not in the C language standards but in Unix-related standards, but it is too useful to ignore. Like the system function, the standards documentation also defines this function in terms of fork and execl, with the shell getting involved again. Not entirely obvious from this documentation is what happens with the stream that isn’t specified, however, but we can conclude that with its talk of input and output filters, as well as the mention of those other functions, that if we request an output stream from the new process, the new process will acquire standard input from the creating process as its own input stream. Correspondingly, if we request an input stream to feed the new process, the new process will acquire standard output for itself and write output to that.
This poses some concurrency issues that the system function largely avoids. Since the system function blocks until the created process is completed, the state of the shared input and output streams can be controlled. But with popen, the created process runs concurrently and can interact with whichever stream it acquired from the creating process, just as the creating process might also be using it, at least until pclose is invoked to wait for the completion of the created process. The standards documentation and the Linux manual page both note such pitfalls, but the whole business seems less than satisfactory.
Again, the Python standard library shows what a better approach might be. Alongside the popen function, the popen2 function creates dedicated input and output pipes for interaction with the created process, the popen3 function adds an error pipe to the repertoire, and there is even a popen4 function that presumably does what some people might expect from popen2, merging the output and error streams into a single stream. Naturally, this was becoming a bit incoherent, and so the subprocess module was brought in to clean it all up.
Our own attempt at a cleaner approach might involve the following function:
pid_t popenv(int argc, const char *argv[], FILE **input, FILE **output, FILE **error);
Here, we want to invoke a program using a vector containing the program and arguments, just as we did before, but we also want to acquire the input, output and error streams. However, we might allow any of these to be specified as NULL, indicating that any such stream will not be opened for the created process. Since this might cause problems, we might need to create special “empty” or “null” streams, where appropriate, so as not to upset the C library.
Unlike popen, we might also provide the process identifier for the created process. This would allow us to monitor the process, control it in some way, and to wait for its completion. The nature of a process identifier is potentially more complicated than one might think, especially in my own system where there can be many process servers, each of them creating new processes without any regard to the others.
A Simpler Portable Environment Standard
Maybe I am just insufficiently aware of the historical precedents in this regard, but it seems that while C language standards are disappointingly tame when it comes to defining interaction with the host environment, the Unix or POSIX standardisation efforts go into too much detail and risk burdening any newly designed system with the baggage of systems that happened to be commercially significant at a particular point in time. Windows NT infamously feigned compliance with such standards to unlock the door to lucrative government contracts and to subvert public software procurement processes, generating colossal revenues that easily paid for any inconvenient compliance efforts. However, for everybody else, such standards seem to encumber system and application developers with obligations and practices that could be refined, improved and made more suitable for modern needs.
My own work depends on L4Re which makes extensive use of capabilities to provide access to entities within the system. For example, each process relies on a task that provides a private address space, within which code and data reside, along with an object space that retains the capabilities available within the task. Although the Fiasco (or L4Re) microkernel has some notion of all the tasks in the system, as well as all the threads, together with other kinds of objects, such global information is effectively private to the kernel, and “user space” programs merely deal with capabilities that reference specific objects. For such programs, there is no way to get some kind of universal list of tasks or threads, or to arbitrarily request control over any particular instances of them.
In systems with different characteristics to the ones we already know, we have to ask ourselves whether we want to reproduce legacy behaviour. To an extent, it might be desirable to have registers of resident processes and the ability to list the ones currently running in the system, introducing dedicated components to retain this information. Indeed, my process servers could quite easily enumerate and remember the details of processes they create, also providing an interface to query this register, maybe even an interface to control and terminate processes.
However, one must ask whether this is essential functionality or not. For now, the rudimentary shell-like environment I employ to test this work provides similar functionality to the job control features of the average Unix shell, remembering the processes created in this environment and offering control in a limited way over this particular section of the broader system.
And so the effort continues to try and build something a little different from, and perhaps a bit more flexible than, what we use today. Hopefully it is something that ends up being useful, too.
cd is a straightforward command. As per the name, it changes the directory and does its job perfectly well. But what if it could do more? One scenario is wanting to execute a command inside a specific location without affecting the current working directory (CWD). This article introduces a cd replacement which offers that feature as well as provides more ways to specify the target directory.It is important to note that it’s not intended for scripting. Rather, it’s only meant for interactive use where it streamlines some operations.New FeaturesFor impatient readers, the code is available on GitHub†. Otherwise, let’s first go through the new features of this enhanced cd.It takes a command as an optional argument. The command is launched inside of the target directory without changing CWD, for example:~/code/rust-rocksdb/librocksdb-sys$ cd .. cargo build
# ... builds rust-rocksdb rather than librocksdb-sys
~/code/rust-rocksdb/librocksdb-sys$The target directory can be specified as a file. The code will change to directory containing that file. This is convenient when copying and pasting paths. A file location can be passed without having to strip the last path component, for example (border around text symbolises copying and pasting):~/code/linux$ git whatchanged -n1 |grep ^:
:100644 100644 8ddb2219a84b 6b384065c013 M include/uapi/linux/kd.h
~/code/linux$ cd include/uapi/linux/kd.h
~/code/linux/include/uapi/linux$The target directory can be specified using a path starting with .../. The code navigates up the directory tree until a matching path is found, for example:~/code/linux/drivers/usb/gadget/udc$ cd .../Documentation
~/code/linux/Documentation$The enhancement integrates with Bash’s autocd option. With it enabled, invoking a directory followed by a command executes that command inside of said directory, for example:/tmp/bash-5.2$ ./examples pwd
cd -- ./examples/ pwd
/tmp/bash-5.2/examples
/tmp/bash-5.2$cd -P resolves all symlinks in PWD. I’ve found this is more useful than POSIX-mandated behaviour. For consistency, of cd -L also doesn’t switch to home directory.InstallationThe new cd comes as a shell script which needs to be sourced in ~/.shellrc, ~/.bashrc or equivalent file.I further recommend adding an alias for - command. This may look strange, but creating a hyphen alias is perfectly fine even though it requires some care. autocd in Bash is also worth a try.The enhanced cd together with those optional configuration options can be installed by executing the following commands:mkdir -p ~/.local/opt
cd ~/.local/opt
# Replace with ‘master’ to get the latest version though
# be warned that there are no guarantees of compatibility
# between the versions.
commit=8ca6070ce2e58581b1aeec748513bbd33904b41d
wget "https://raw.githubusercontent.com/mina86/dot-files/${commit?}/bin/pcd.sh"
. pcd.sh
install='
if [ -e ~/.local/opt/pcd.sh ]; then
. ~/.local/opt/pcd.sh
fi
# Bash interprets ‘-=…’ as a flag so ‘--’ is needed but
# BusyBox complains about it so silence the warning.
alias -- -="cd -" 2>/dev/null
'
# Add to Bash
echo "${install?}" >>~/.bashrc
echo "shopt -qs autocd" >>~/.bashrc
# Add to other shells
echo "${install?}" >>~/.shellrcLimitationsFirstly, the enhanced command does not support any other switches shell’s cd might offer such as -e or -@. Anyone who relies on them should be able to add them to the script with relative ease.Secondly, the command doesn’t fully integrate with CDPATH. While basic functionality of CDPATH works, it cannot be combined with alternative target directory specification used by the new cd.ConclusionThere are commands a seasoned shell user may use without giving them a second thought. Certainly, cd is so obvious and straightforward that there’s nothing to change about it. However, accepting that even fundamental commands could be changed may lead to improvements in one’s workflow.I’ve been using various forms of enhanced cd for over a decade. And with this post I hope I’ve inspired you, Dear Reader, to give it a shot as well. The exact set of features may not be to your liking, but nothing stops you from writing your own cd replacement.† Note that the repository includes my dot-files and I may with time update functionality of the pcd.sh script to the point where description in this article is no longer accurate. This post is describing version at commit 8ca6070c. Setup instructions in Installation section are pinned to that version.
I’ve been using Xonsh, a shell that combines a shell REPL
with a Python REPL, for years now. I’ve also been using Emacs for years, but I
was never able to marry the two in a satisfactory way. But finally, after being
frustrated for long enough, I solved the puzzle. This article is written to help
like one or two other people on this world who use both Emacs and Xonsh.
vterm, probably the best terminal
emulator in Emacs, requires some shell-side configuration to make a shell
integrate cleanly into Emacs. Specifically, an improved clear experience and
directory- and prompt-tracking. vterm can also do message passing, but I’m not
very interested in running Elisp in my terminal emulator—I have the rest of
Emacs for that.
The idea is to print some invisible/hidden strings to the terminal that vterm
can subsequently read, but that the user is unbothered by. The code to achieve
this in .xonshrc is:
# You can modify this however you want.
$PROMPT = "{env_name}� {BOLD_GREEN}{user}{RESET} {BOLD_BLUE}{cwd_base}{RESET}{branch_color}{curr_branch: {}}{RESET} {BOLD_BLUE}{prompt_end}{RESET} "
def _vterm_printf(text):
def _term_is(value):
return $TERM.split("-")[0] == value
if ${...}.get("TMUX") and (_term_is("tmux") or _term_is("screen")):
return $(printf r"\ePtmux;\e\e]%s\007\e\\" @(text))
elif _term_is("screen"):
return $(printf r"\eP\e]%s\007\e\\" @(text))
else:
return $(printf r"\e]%s\e\\" @(text))
def _vterm_prompt_end():
return _vterm_printf("51;A{user}@{hostname}:{cwd}")
if ${...}.get("INSIDE_EMACS"):
$SHELL_TYPE = "readline"
def _clear(args, stdin=None):
print(_vterm_printf("51;Evterm-clear-scrollback"), end="")
tput clear @(args)
aliases["clear"] = _clear
$PROMPT += _vterm_prompt_end()
One important thing to note is that this only works in readline mode.
prompt-toolkit is
much fancier, but for reasons that are unknown to me, modifying $PROMPT as
above does not produce the desired result. I’ve also considered monkey-patching
print_color as a work-around, but there exists no xonsh.built_ins.XSH.shell
inside of .xonshrc to monkey-patch.
After implementing the above code in .xonshrc, you can do the following things
in vterm:
C-c C-p and C-c C-n (vterm-[previous,next]-prompt) move back and forth
between prompts.
C-x C-f (find-file) starts in the CWD of the shell.
When clearing, old data is removed from the buffer.
And that’s it. I’ll see about upstreaming some of this knowledge to vterm some
day soon after some more hacking/testing.
I recently changed up my blog’s theme. I previously used
beautifulhugo, and now I use
hugo-pure. The whole thing’s a touch more
basic, but I’ve not lost any important features. Multi-language supports works
(although it has been ages since I posted in Esperanto), and posts display just
fine.
The most important thing I changed from the hugo-pure theme is the text colour:
my black text is #000 instead of some dark grey. I really dislike dark greys
as text.
The rationale for the change is a decreased footprint. It’s a bit senseless to
transfer an entire megabyte of data just to read some text. As an added benefit,
this new theme has no JavaScript whatsoever. The bundled (minified) CSS is still
a bit on the bulky side, but I’m not enough of a designer to dare tackle that
problem.
Anyway, good stuff, new blog theme. I wish more of the web was just text.
Update (2024-05-30): I’ve changed the text colour to #111 after doing some
research. It’s dark enough to satisfy my dislike for grey texts, and bright
enough to satisfy all the UX people on the internet who say never to use black
text. The original #434343 was a touch silly, though.
Yesterday I released v3.1.0a1 of the
REUSE tool. It is an alpha release for the
soon-to-be-released REUSE Specification v3.2, which can be found in its current
state at this link.
The biggest change is the introduction of REUSE.toml, a configuration file that
replaces the soft-deprecated .reuse/dep5. This configuration file allows you to
declare the copyright and licensing of files (and globs of files) relative to
the file. The important distinctions from .reuse/dep5 are:
you can place the REUSE.toml file anywhere in your project;
you can declare the precedence of information in case REUSE.toml disagrees
with the contents of the file;
and, because REUSE.toml is just a TOML file, you can add any other metadata
that you want.
Because this is an alpha release, the accompanying documentation is not yet
easily discoverable, but it is (in the process of being) written. Below some
links:
The new REUSE Specification v3.2 https://reuse.software/spec-3.2/
An updated FAQ (under construction)
https://github.com/carmenbianca/reuse-website/blob/3.2-improvements/site/content/en/faq.md
The tool documentation https://reuse.readthedocs.io/en/v3.1.0a1/
New man pages https://reuse.readthedocs.io/en/v3.1.0a1/man/index.html
The change log https://reuse.readthedocs.io/en/v3.1.0a1/history.html
The alpha release on PyPI https://pypi.org/project/reuse/3.1.0a1/
The purpose of the alpha release is to collect feedback on the newly implemented
(and defined) REUSE.toml. If you have some spare time to take a look at this,
you can convert your .reuse/dep5 file to REUSE.toml using reuse convert-dep5, and you can e-mail me at carmenbianca@fsfe.org, write to
reuse@lists.fsfe.org, or create issues against the
reuse-tool or
reuse-website repositories. (Some day
soon I’ll finally be able to move those repositories away from GitHub,
inshallah.)
In the near future, after this is properly released, I want to look at creating
a lint-file command for linting individual files instead of the entire
repository (for better pre-commit integration), and I want to see if I can
create a pre-commit hook that automagically adds REUSE information to touched
files.
Some people struggle to understand the distinctions between ‘free software’ and ‘open source software.’ Let’s clear up the confusion with an analogy.Imagine a world without vegetarianism. One day, someone proposes a new diet called ‘moral eating,’ which excludes meat for ethical reasons. Some people embrace it, and discover additional benefits like reduced environmental impact. However, advocates observe that implying people not adhering to the diet are immoral isn’t the best recruitment strategy. They coin the term ‘sustainable eating’ to focus on the environmental advantages.But now people get bogged down in philosophical debates. If one uses the term ‘moral eating’ some assume they don’t care about the environment; on the other hand, if one says ‘sustainable eating’ some assume they don’t care about animals. To avoid this an all-encompassing acronym MSE (Moral and Sustainable Eating) is created. It signifies the same thing — no meat — but avoids getting entangled in justifications.And so we end up with three distinct terms — moral eating, sustainable eating and MSE — which all refer to the same diat. What we call vegetarianism.This is how the terms free software, open source and FOSS (Free and Open Source Software) came to be. They all represent the same category of software with a different advocacy philosophy. Free software emphasises the four essential freedoms and open source uses the Open Source Definition. While the latter might be more explicit on some points — it overtly prohibits discrimination against any people or field of endeavour — the four freedoms implicitly cover them as well.Source-available softwareHere’s where things get tricky. Some companies try to capitalize on the positive associations of open source without truly adhering to its principles. They might ‘open their software’ but release source code under a license that restricts creating derivative works. This could be due to genuine misunderstanding or intentional manipulation. Whatever the reason, if the four essential freedoms aren’t granted, the code isn’t open source. This type of software is more accurately called source-available software.Libre SoftwareAnother point of confusion is the ambiguity of the term ‘free software.’ ‘Free’ can refer to price or freedom. The common saying ‘free as in freedom, not as in beer’ attempts to clarify this imprecision. To eliminate the ambiguity altogether, the terms libre software or libreware have emerged. And to include it in the FOSS acronym it’s sometimes replaced with FLOSS (Free, Libre and Open Source Software).Proprietary software that one can acquire without paying is called freeware. It’s distinct from free software, which is only concerned with user freedoms and permits selling of the software.Creative Commons and Free SoftwareLastly, it’s worth mentioning the Creative Commons organisation. It aims to simplify copyright by allowing creators to share their work with specific permissions. While its goals align somewhat with free software, it’s important to note that not all Creative Commons licenses qualify. Any license that disallows derivative works (NoDerivatives) or commercial use (NonCommercial) doesn’t meet the criteria for free software.There are three Creative Commons licenses which are considered free software:CC0, which is roughly equivalent to something being in Public Domain,CC BY (Attribution), which is roughly equivalent to permissive free software licenses andCC BY-SA (Attribution-ShareAlike), which is roughly equivalent to copyleft free software licenses.However, when licensing source code, it’s generally recommended to use licenses specifically designed for software, such as various GPL variants, the Mozilla Public License, the Apache license, or the MIT license.ConclusionFree software, open source software, libre software, libreware, FOSS and FLOSS all describe the same category of software: software with source code that users can freely run, modify, and redistribute. Source-available software has accessible code whose license prevents one of those activities.
A few weeks ago I attended the KDE Goals April 2024 sprintI was there as part of the Automation & Systematization sprint given my involvement in the release process, the "not very automatized" weekly emails about the status of CI about KDE Gear and KDE Frameworks, etc. but I think that maybe I was there more as "person that has been around a long time, ask me if you have questions about things that are documented through oral tradition"I didn't end up doing lots of work on sprint topics themselves (though I participated in various discussions, did a bit of pair-programming with Aleix on QML accessibility issues, inspired DavidR to do the QML-text-missing-i18n check that he describes in his blog); instead I cheated a bit and used the sprint to focus on some of the KDE stuff I had a bit on my backlog, creating the KDE Gear release/24.05 branches and lots of MR reviewing and more!Thanks KDE e.V. for sponsoring the trip, if you would like such events to continue please we need your continued donationsAnd remember Akademy talk submission period ends in 10 days, send your talk now!
TL;DR: When implementing Display trait for a wrapper type, use self.0.fmt(fmtr) rather than invoking write! macro. See The proper way section below.Imagine a TimeOfDay type which represents time as shown on a 24-hour clock. It could look something like the following:pub struct TimeOfDay {
pub hour: u8,
pub minute: u8,
}
impl core::fmt::Display for TimeOfDay {
fn fmt(&self, fmtr: &mut core::fmt::Formatter) -> core::fmt::Result {
write!(fmtr, "{:02}:{:02}", self.hour, self.minute)
}
}
fn main() {
let hour = 2;
let minute = 5;
assert_eq!("02:05", TimeOfDay { hour, minute }.to_string());
}White it’s a serviceable solution, one might tremble at the lack of type safety. Nothing prevents the creation of nonsensical times such as ‘42:69’. In real life hour rarely goes past 23 and minute sticks to values below 60. Possible approach to prevent invalid time is to use a newtype idiom with structs imposing limits on the wrapped value, for example:use core::fmt;
struct TimeOfDay {
hour: Hour,
minute: Minute,
}
struct Hour(u8);
struct Minute(u8);
impl Hour {
fn new(val: u8) -> Option<Self> { (val < 24).then_some(Self(val)) }
}
impl Minute {
fn new(val: u8) -> Option<Self> { (val < 60).then_some(Self(val)) }
}
impl fmt::Display for TimeOfDay {
fn fmt(&self, fmtr: &mut fmt::Formatter) -> fmt::Result {
write!(fmtr, "{:02}:{:02}", self.hour, self.minute)
}
}
fn main() {
let hour = Hour::new(2).unwrap();
let minute = Minute::new(5).unwrap();
assert_eq!("02:05", TimeOfDay { hour, minute }.to_string());
}Alas, since the new types don’t implement Display trait, the code won’t compile. Fortunately the trait isn’t complicated and one might quickly whip out the following definitions:impl fmt::Display for Hour {
fn fmt(&self, fmtr: &mut fmt::Formatter) -> fmt::Result {
write!(fmtr, "{}", self.0)
}
}
impl fmt::Display for Minute {
fn fmt(&self, fmtr: &mut fmt::Formatter) -> fmt::Result {
write!(fmtr, "{}", self.0)
}
}Having Display, Debug, Octal etc. implementations which call write! macro only is quite common. But while common, it’s at times incorrect. While the above example with such definitions will build, the test in the main will fail (playground) producing the following error:thread 'main' panicked at src/main.rs:40:5:
assertion `left == right` failed
left: "02:05"
right: "2:5"The issue is that invoking write! erases any formatting flags passed through the fmtr argument. Even though TimeOfDay::fmt used {:02} format, the Display implementations disregard the width and padding options by calling write! with {} format.Fortunately, the solution is trivial and in fact even simpler than calling write!.The proper wayIn majority of cases, the proper way to implement traits such as Display or Debug is to use delegation as follows:impl fmt::Display for Hour {
fn fmt(&self, fmtr: &mut fmt::Formatter) -> fmt::Result {
self.0.fmt(fmtr)
}
}
impl fmt::Display for Minute {
fn fmt(&self, fmtr: &mut fmt::Formatter) -> fmt::Result {
self.0.fmt(fmtr)
}
}Since the same Formatter is used, any configuration that the caller specified (such as width and fill) will be applied when formatting the inner type (playground).In fact, there is a crate for that. derive_more offers derives for various traits including Display. When used with no additional options on a newtype struct, the crate will generate a delegating implementation of the trait. In other words, the above impls can be replaced by the following derive annotations:#[derive(derive_more::Display)]
struct Hour(u8);
#[derive(derive_more::Display)]
struct Minute(u8);Display vs DebugRelated trick is delegating between Display and Debug traits (or any other formatting traits). This is especially useful when implementation for both types should be identical. A naïve approach would be to use something like write!(fmtr, "{self:?}") in Display implementation but this suffers from aforementioned issues. Delegation is once again the better approach (playground):use core::fmt;
#[derive(Debug)]
enum DayOfWeek {
Monday,
Tuesday,
Wednesday,
Thursday,
Friday,
Saturday,
Sunday,
}
impl fmt::Display for DayOfWeek {
fn fmt(&self, fmtr: &mut fmt::Formatter) -> fmt::Result {
fmt::Debug::fmt(self, fmtr)
}
}
fn main() {
println!("dbg={:?} disp={}", DayOfWeek::Monday, DayOfWeek::Monday);
}
Back in March I was in the UK troubleshooting a Humax set-top box (STB) that
was behaving erratically. Most of the time it would work as expected, but
sometimes it would just display a green screen when switching on or changing
channels.
I approached this in a number of ways: searching online for other people's
experiences with these boxes, trying to find any software updates that might
have been needed, and looking into alternatives if these approaches should
fail.
One option that was left open was buying a new digital video recorder (DVR),
though I was a bit reluctant to rush into this given that there seem to be very
few reasonably priced ones available these days. The market seems to have moved
to smart TVs and streaming services.
In the end, the solution to the original problem was to change from using a
HDMI cable to connect the set-up box and television to using a SCART cable
instead. The problem seemed to have been related to
HDCP
content protection.
The unused approach
One of the fallback options I looked at was buying a Raspberry Pi and a TV
hat, and I figured that I might as well just do this to see if it was a viable
replacement for a DVR. It wasn't, though it could be made to work with a fair
amount more effort and a more powerful Pi than the Zero 2 W that I chose for
the experiment.
Although various online stores have guides to help with setting up the hardware
and software, it was quite frustrating to get the software configured to
download program guides and receive broadcasts. There was a window of time when
it worked, but it seemed quite unreliable otherwise.
Repurposing the Pi
While it's possible that the Pi I bought might be needed in its original role,
I think it's more likely I'd try to buy a replacement for the original Humax
box instead. In the meantime, I started looking into porting Inferno to it.
Rather, that should be re-porting Inferno, because the original port was for
ARMv6-based hardware, and the Pi Zero 2W is actually ARMv8-based.
Slow progress can be observed
in the diary.
Categories: Inferno,
Free Software
Akademy 2024 (the annual world summit for KDE) is happening in Würzburg, Saturday 7th – Thursday 12th September. (I hope you knew that)First of all, if you're reading this and thinking, "Should i go to Akademy?" The answer is [most probably] YES! Akademy has something for everyone, be it coders, translators, promoters, designers, enthusiasts, etc.Now, with this out of the way, one of the many things that makes Akademy is the talks on the weekend, and you know who has something to say? *YOU*Yes, *YOU*. I'm sure you've been working on something interesting, or have a great idea to share.*YOU* may think that your idea is not that great or the things you work on are not interesting, but that's seldomly the case when someone explains me their "boring" thing they've been working on, i always think "Wow that's great".Ok, so now that I've convinced you to send a talk proposal, when better than *TODAY* to send it?Yes I know the Call for Participation is open until the 24 of May, but by sending it today you make sure you don't forget sending it later and also [more important for me] you help those of us in the Program Committee not to worry when the final date starts approaching and we don't have lots of talks yet because you all prefer sending talks on the very last minute.So stop reading and send your talk today ;-)
Digitaliseringsproblemer kan løses med fri/Open Source software
– åbent brev til partiernes IT-ordførere
FSFE Danmark v/Allan Dukat, Øjvind Fritjof Arnfred og Carsten Agger –
Om os i FSFE Danmark:
https://community.fsfe.org/t/handleplan-og-arbejdsgrundlag-for-fsfe-danmark/963
I slutningen af 2019 klagede en far til Datatilsynet over Helsingør Kommune, fordi hans otte-årige søn i sin folkeskole havde fået udleveret en Chromebook computer med en Google-konto uden faderens samtykke. Dette betød, som han anførte i klagen, at sønnens persondata ulovligt blev videregivet til Google.
Kommunernes Landsforening (KL) overtog forhandlingerne med Datatilsynet på vegne af de 53 kommuner, der benyttede Chromebook og Google.
Under hele forløbet undlod KL at overveje, om der var andre måder at tilrettelægge undervisningen på, men støttede ubetinget Helsingør Kommunes ret til at videregive elevernes persondata til Google. 4 år senere slog Datatilsynet i en endelig afgørelse fast, at skolernes brug af Chromebook og Google Workspace er ulovlig. KL’s indstilling var og er, at loven må laves om, som de skriver i deres pressemeddelelse:
”Hvis ikke regeringen kommer på banen, så er der sort skærm for titusindvis af skolebørn i mere end halvdelen af landets kommuner efter sommerferien. Det vil ramme skolerne hårdt. Vil vi virkelig det? Og der vil være tusindvis af ordblinde børn, som ikke kan få den nødvendige hjælp. Vil vi tillade det? Noget andet – og langt mere vidtrækkende – er, at der er skabt en kæmpe utryghed på en lang række andre velfærdsområder, hvor vi ikke ved, om vi er købt eller solgt.”
Kilde: https://www.kl.dk/forsidenyheder/2024/marts/kl-uden-action-fra-regeringen-staar-tusindvis-af-skoleelever-med-sort-skaerm-efter-sommerferien
KL tager således skoleelevernes private data som gidsler i stedet for at undersøge lovlige alternativer. Det er nok også meget optimistisk af KL at tro, at Folketinget vil eller kan ændre loven på en måde, som strider mod det europæiske databeskyttelsesregulativ GDPR, som Datatilsynet har henvist til i deres afgørele.
I oktober 2023 kom det frem i pressen, at Københavns Kommune havde flere ulovlige kontrakter med deres IT-leverandører. Kommunens egen databeskyttelsesrådgiver skrev således i et notat fra april 2023:
»Københavns Kommune har på nuværende tidspunkt flere ulovlige kontrakter med leverandører og vil i den nærmeste fremtid have behov for at forny flere af disse kontrakter, fordi leverandørens løsning ikke udbydes af andre, og fordi systemet er nødvendigt for, at Københavns Kommune kan levere velfærdsydelser til borgere.«
Kilde: https://www.computerworld.dk/art/284811/koebenhavns-kommune-har-hundredevis-af-ulovlige-it-kontrakter
I november 2023 viste det sig, at regionerne fik uforudset høje udgifter til softwarelicenser. Priserne for centrale softwareløsninger steg betydeligt mere end inflationen, men da journalsystemerne simpelthen ikke kunne fungere uden, var der ikke andet at gøre end at betale regningen og finde pengene ved besparelser andre steder i regionerne.
Kilde: https://www.version2.dk/artikel/danske-myndigheder-sidder-fast-i-kloeerne-paa-it-giganter-forhandlingerne-sker-med-en-pistol-panden
I februar 2024 var det kommunernes tur til at beklage sig over betalingen for Microsofts officepakke i “skyen”.
Her er problemet, at både data og programmer ligger på Microsofts servere, så man ikke som i “gamle dage” kunne undlade at opgradere programmerne og fortsætte med at bruge de ældre udgaver. For hvis man ikke betaler, mister man adgangen til systemerne. Også her er sagsbehandlingen dybt afhængig af de ansattes officeprogrammer.
Kilde: https://www.dr.dk/nyheder/indland/kommunerne-er-dybt-afhaengige-af-microsoft-og-deres-udgifter-stiger-og-stiger
Ligeledes i februar 2024 lækker en hacker kildekode til programmer, som Netcompany har udviklet til adskillige danske myndigheder. Kildekoden afslører brugernavne og passwords, og eksperter ser eksempler på manglende adskillelse mellem programmer, konfiguration og runtime environment. Eftersom Netcompany ejer koden og ikke deler den med nogen, var der ingen, der vidste dette, før koden blev offentliggjort.
Kilde: https://www.version2.dk/artikel/hackere-laekker-kildekode-og-passwords-fra-netcompany-truer-den-danske-stat og flere efterfølgende artikler.
Hvordan kan man løse disse problemer?
Vi mener, at kernen i enhver digitaliseringsstrategi må være, at det offentlige altid beholder ejerskabet af og suveræniteten over deres IT-systemer.
Dette kan opnås ved at følge FSFEs slogan om “Public Money Public Code”, https://publiccode.eu/da/, der siger, at al software betalt af offentlige midler altid skal være fri software, også kendt som “open source”. Denne type software er kendetegnet ved, at modtageren altid har ret til at undersøge softwaren, som de selv synes; køre den med ethvert formål uden begrænsning; selv ændre og forbedre den; samt dele den med andre, også som de selv synes, med eller uden egne forbedringer.
Dette princip vender magtforholdet mellem kunde og producent om og betyder, at kunden altid kan tage produktet og få det videreudviklet og driftet hos en anden leverandør. Hvis det offentlige følger dette princip, betyder det netop også, at myndighederne og ingen andre har den fulde kontrol over deres løsninger og aldrig mere kan presses på pris og vilkår af urimelige leverandører.
Derfor bør alle udbud indeholde en klausul om, at al kode brugt i det offentlige og udviklet for offentlige midler skal være fri software/open source. Dette har virkelig mange fordele:
Fri software/open source sikrer, at man aldrig er prisgivet en enkelt leverandør, da en anden leverandør altid vil kunne arbejde videre med systemet
Når programmerne er fri software/open source, er der ingen binding til bestemte leverandørers datacentre – de kan placeres hvor som helst, hos en anden leverandør eller lokalt. Derved bliver konkurrencen mellem forskellige leverandører mere fri, idet man slipper for de kunstige monopoler, der i dag holder kunderne fanget i løsninger, der ikke er de bedste eller billigste på markedet.
Når et program er betalt, kan alle dele af det offentlige bruge det, uden yderligere udgifter eller licenser – hvis én region eller ét land fx har fået udviklet et patientjournalsystem, kan alle regioner og lande frit bruge det uden at betale for den funktionalitet, der allerede er udviklet.
Programmer, som er fri software/open source er grundlæggende sikrere, fordi udviklerne ved, at andre kan se hvad de laver, og der er flere til at finde fejlene.
Derudover ville det være oplagt at holde offentlige data inden for landets grænser.
Vi ved godt, at det vil være en lang og dyr proces at nå dertil, men vi er overbeviste om, at det på sigt vil være for det bedste, økonomisk såvel som sikkerhedsmæssigt, både af hensyn til databeskyttelsen og landets suverænitet, at indføre denne klausul, om at al offentlig software skal være fri software/open source.
Derfor bør processen startes øjeblikkeligt, og man kan passende kigge på OS2 – det offentlige digitaliseringsfællesskab, https://www.os2.eu/, for at finde inspiration til, hvordan det eventuelt kan gøres.
Til yderligere inspiration henvises til disse sider:
Hvad er fri software, https://media.fsfe.org/w/3bc6b0e6-fee3-4239-9ec7-dd0c1669b841
German state ditches Windows, Microsoft Office for Linux and LibreOffice, https://www.theregister.com/2024/04/04/germanys_northernmost_state_ditches_windows/
Free Software Foundation Europes hjemmeside, https://fsfe.org/
Kontakt
Carsten Agger <agger at fsfe.org>, koordinator for Danmark og medlem af Free Software Foundation Europes bestyrelse og europæiske team, tlf. 2086 5010
Allan Dukat <allan at fsfe.org>, aktivist og støttemedlem i FSFE Danmark
Øjvind Fritjof Arnfred <slartibartfas at fsfe.org>, aktivist og støttemedlem i FSFE Danmark
I have a small server running in my flat that serves files locally via NFS and remotely via Nextcloud. This post documents
the slightly overpowered upgrade of the hardware and subsequent performance / efficiency optimisations.
TL;DR
I can fully saturate a 10Gbit LAN connection, achieving more than 1100 MiB/s throughput.
I can perform a zpool scrub with 11 GiB/s, completing a 6.8TiB scrub in 11min.
Idle power usage can be brought down to 34W.
Old setup and requirements
What the server does:
Serve files via NFS to
my workstation (high traffic)
a couple of Laptops (low traffic)
the TV running Kodi (medium traffic)
Host a Nextcloud which provides file storage, PIM etc. for a handful of people
Not a lot of compute is necessary, and I have tried to keep power usage low. The old hardware served me well really long:
AMD 630 CPU
16GiB RAM
2+1 * 4TiB spinning disk RAIDZ1 with SSD ZIL (“write-cache”)
The main pain point was slow disk access resulting in poor performance when large files were read by the Nextcloud.
Browsing through my photo collection via NFS was also very slow, because thumbnail generation needed to pull all the images.
Furthermore, low speed meant that I was not doing as much on the remote storage as I would have liked (e.g. storing
games), resulting in my workstation’s storage always running out.
And I was just reaching the limits of my ZFS pool anyway, so it was time for an upgrade!
New setup
To get better I/O, I thought about switching from HDD to SSD, but then realised that SSD performance is very low compared
to NVME performance, although the price difference is not that much. Also, NFS+ZFS leads to quite a bit of I/O, typically
requiring the use of faster caching devices, further complicating the setup.
Consequently, I decided to go for a pure NVME setup.
Of course, the new server would also need 10GBit networking, so that I can use all that speed in the LAN!
This is the new hardware! I will discuss the details below.
Mainboard, CPU and RAM
The main requirement for the mainboard is to offer connectivity for four NVME disks. And to be prepared for the future,
I would actually like 1-2 extra NVME slots.
There are two ways to attach NVMEs to a motherboard:
directly (“natively”)
via an extension card that is plugged into a PCIexpress slot
Initially, I had assumed no mainboard would offer sufficient native slots, so I did a lot of research on option 2.
The summery: it is quite messy. If you want to use a single extension card that hosts multiple NVMEs (which is required
in this case), you need so called “bifurcation support” on the mainboard.
This lets you e.g. put a PCIe x8 card with two NVME 4x disks into a PCIe 8x slot on the mainboard.
However, this feature is really poorly documented,1 and and varies between mainboard AND CPU whether they
support no bifurcation, only 8x → 4x4x or also 16x → 4x4x4x4x.
The different PCIe versions and speeds, and the difference between the actually supported speed and the electrical
interface add further complications.
In the end, I decided to not do any experiments and look for a board that natively supports a high number of NVME slots.
For some reasons, this feature is very rare on AMD mainboards, so I switched to Intel (although actually I am a bit of
an AMD fanboy). I probably could have gone with a board that has 5 slots, but I use hardware for a long time and wanted
to be safe, so I took board that has 6 NVME slots (2 free slots):
ASRock Z790 NOVA WiFi
None of the available boards had a proper2 10GBit network adaptor, so having a usable PCIe slot for a dedicated card
was also a requirement.
It is important to check whether PCIe slots can still be used when all NVME slots are occupied; sometimes they
internally share the bandwidth. But for the above board this is not the case.
Important: To be able to boot FreeBSD on this board, you need to add the following to /boot/device.hints:
hint.uart.0.disabled="1"
hint.uart.1.disabled="1"
For the CPU, I just went with something on the low TDP end of the current Intel CPU range, the Intel Core i3-12100T.
Four cores + four threads was exactly what I was looking for, and 35W TDP sounded good.
I paired that with some off-the-shelf 32GiB RAM kit.
Case, power supply & cooling
Strictly speaking a 2U case would have been sufficient, but I thought a 3U case might offer better air circulation.
I ended up with the Gembird 19CC-3U-01.
For unknown reasons, I chose a 2U horizontal CPU fan, instead of a 3U one.
The latter would definitely have provided better airflow, but since the fan barely runs at all, it doesn’t make much of
a difference.
I was unsuccessful in finding a good PSU that is super efficient in the average case of around 40W power usage but also
covers spikes well above 100W, so I just chose the cheapest 300W one I could get :)
The case with everything in place.
The built in fans are very noisy. I chose to replace one of the intake fans with a spare one I had lying around and
only connect one of the rear outtake fans. But I added an extra fan where the extension slots are to divert some
airflow around the NIC—which otherwise gets quite warm. This should also blow some air over the NVME heatsinks!
All fans can be regulated and fine-tuned from the BIOS of the mainboard which I totally recommend you do. At the current
temperatures and average workloads the whole setup is almost silent.
Storage
Now, the fun begins. Since I needed more space than before, I clearly want a 3+1 x 4TiB RAIDZ1.
My goal was to be able to saturate a 10GBit connection (so get around 1GiB/s throughput) and still
have the server be able to serve the Nextcloud without slowing down significantly. Currently the WAN upload is quite
slow, but I hope to have fibre in the future. In any case, I thought that any modern NVME should be fast enough, because
they all advertise speeds of multiple GiB/s.
Choice of disks
Anyway, I got two Crucial P3 Plus 4TB (which were on sale at Amazon for ~190€), as well as two Lexar NM790 4TB (which were also a lot cheaper than they are now).
My assumption that that they were very comparable, was very wrong:
Disk
IOPS rand-read
IOPS read
IOPS write
MB/s read
MB/s write
“cat speed” MB/s
Crucial
53,500
794,000
455,000
2,600
4,983
~700
Lexar
53,700
796,000
456,000
4,578
5,737
~2,700
I used this fellow’s fio-script to
generate all columns except the last. The last column was generated by simply cat’ing a 10GiB file of random numbers to /dev/null which
roughly corresponds to the read portion of copying a 4k movie file.
Since I had two disks each, I actually took the time to test all of them in different mainboard slots, but the results
were very consistent: in real-life tasks, the Crucial disk underperformed significantly, while the Lexar disks were
super fast.
I decided to return the Crucial disks and get two more by Lexar 😎
Disk encryption
I always store my data encrypted at rest. FreeBSD offers GELI block-level encryption (similar to LUKS on Linux).
But OpenZFS also provides a dataset/filesystem-level encryption since a while.
I previously used GELI, but I wanted to switch to ZFS native encryption, because it provides some advantages:
Flexibility: I can choose later which datasets to encrypt; I can encrypt different datasets with different keys.
Zero-knowledge backups: I can send incremental backups off-site that are received and fully integrated into the target
pool without that server ever getting the decryption keys.
Forward-compatibility: I can upgrade to better encryption algorithms later.
Linux-compatibility: I can import the existing pool in a Linux environment for debugging or benchmarking.
However, I had also heard that ZFS native encryption was slower, so I decided to do some benchmarks:
Disk
IOPS rand-read
IOPS read
IOPS write
MB/s read
MB/s write
“cat speed” MB/s
no encryption
54,700
809,000
453,000
4,796
5,868
2,732
geli-aes-256-xts
40,000
793,000
446,000
3,332
3,334
952
zfs-enc-aes-256-gcm
26,100
513,000
285,000
3,871
4,648
2,638
zfs-enc-aes-128-gcm
29,300
532,000
353,000
3,971
4,794
2,631
Interestingly, GELI3 performs much better on the IOPS, but much worse on throughput, especially on our real-life test
case. Maybe some smart person knows the reason for this, but I took this benchmark as an assurance that going with
native encryption was the right choice.4 One reason for the good performance of the native encryption seems
to be that it makes use of the CPU’s avx2 extensions.
At this point, I feel like I do need to warn people about some ZFS encryption related issues that I learned about later.
Please read this. I have had no problems to date, but make
up your own mind.
RaidZ1
recordsize
compr.
encrypt
IOPS rand-read
IOPS read
IOPS write
MB/s read
MB/s write
“cat speed” MB/s
128 KiB
off
off
50,000
869,000
418,000
3,964
5,745
2,019
128 KiB
on
off
49,800
877,000
458,000
3,929
4,654
1,448
128 KiB
off
aes128
26,300
484,000
230,000
3,589
5,331
2,142
128 KiB
on
aes128
27,400
501,000
228,000
3,510
3,927
2,120
These are the numbers after creation of the RAIDZ1 based pool. They are quite similar to the numbers measured before.
The impact of encryption on IOPS is clearly visible, less so on sequential read/write throughput.
Compression seems to impact write throughput but not read throughput which is expected for zstd. It is unclear why
“cat speed” is lower here.
recordsize
compr.
encrypt
IOPS rand-read
IOPS read
IOPS write
MB/s read
MB/s write
“cat speed” MB/s
1 MiB
off
off
7,235
730,000
404,000
3,686
3,548
2,142
1 MiB
on
off
7,112
800,000
470,000
3,624
3,447
2,064
1 MiB
off
aes128
3,259
497,000
258,000
3,029
3,422
2,227
1 MiB
on
aes128
3,697
506,000
249,000
3,137
3,361
2,237
Many optimisation guides suggest setting the zfs recordsize to 1 MiB for most use-cases, especially storage of media
files.
But this seems to drastically penalise random read IOPS while providing little to no benefit in the sequential
read/write scenarios. This is actually a bit surprising and I will need to investigate this more.
Is it perhaps because NVMEs are good at parallel access and therefor suffer less from fragmentation anyway?
In any case, the main take away message is that overall read and
write throughputs are over 3,000 MiB/s in the synthetic case and over 2,000 MiB/s in the manual case, which is great.
Other disk performance metrics
Operation
Speed [MiB/s]
Copying 382 GiB between two datasets (both enc+comp)
1,564
Copying 505 GiB between two datasets (both enc+comp)
800
zfs scrub of the full pool
11,000
These numbers further illustrate some real world use-cases. It’s interesting to see the difference between the
first two, but it’s also important to keep in mind that this is reading and writing at the same time.
Maybe some internal caches are exhausted after a while? I didn’t debug these numbers further, but I think the speed is
quite good after such a long read/write.
More interesting is the speed for scrubbing, and, yes, I have checked this a couple of times. A scrub of 6.84TiB
happens in 10m - 11m, which is pretty amazing, I think, considering that it is reading the data and calculating
checksums. I am assuming that sequential read is just very fast and that access to the different disks happens in
parallel. The checksum implementation is apparently also avx2 optimised.
LAN
Network adapter
Based on recommendations, I decided to buy an Intel card. Cheaper 10GBit network cards are available from
Marvell/Aquantia, but the driver support in FreeBSD is poor, and the performance is supposedly also not close
to that of Intel.
Many people suggested I go for SFP+ (fibre) instead of
10GBase-T (copper), but I already have CAT7 cables in my flat. While I could have used fibre purely for connecting
the server to the switch (and this would likely save some power), I would have had to buy a new switch and
the options were just not economical—I already have
a switch with two 10GBase-T ports which I had bought for exactly this setup.
The cheapest Intel 10GBase-T card out there is the X540 which is quite old and available on Amazon for around 80€.
I bought two of those (one for the server and one for the workstation). More modern cards are supposedly more energy
efficient, but also a lot more expensive.5
NFS Performance
On server and client, I set:
kern.ipc.maxsockbuf=4737024 in /etc/sysctl.conf
mtu 9000 media 10gbase-t in the /etc/rc.conf (ifconfig)
Only on the server:
nfs_server_maxio="1048576" in /etc/rc.conf
Only on the client:
nfsv4,nconnect=8,readahead=8 as the mount options for the nfs mount.
vfs.maxbcachebuf=1048576 in /boot/loader.conf (not sure any more if this makes a difference).
These settings allow larger buffers and increase the amount of readahead. This favours large sequential reads/writes over small random reads/writes.
The full options on the client end up being:
# nfsstat -m
X.Y.Z.W:/ on /mnt/server
nfsv4,minorversion=2,tcp,resvport,nconnect=8,hard,cto,sec=sys,acdirmin=3,acdirmax=60,acregmin=5,acregmax=60,nametimeo=60,negnametimeo=60,rsize=1048576,wsize=1048576,readdirsize=1048576,readahead=8,wcommitsize=16777216,timeout=120,retrans=2147483647
I use NFS4 for my workstation and NFS3 for everyone else. I have performed no benchmarks on NFS3, but I see no reason
why it would be slower.
IOPS rand-read
IOPS read
IOPS write
MB/s read
MB/s write
“cat speed” MB/s
283
292,000
33,200
1,156
594
1,164
This benchmark was performed on a dataset with 1M recordsize, encryption, but no compression.
Random read IOPS are pretty bad, and I see a strong correlation here to the rsize (if I halve it, I double the IOPS; not shown in table).
It’s possible that every 4KiB read actually triggers a 1MiB read in NFS which would explain this.
On the other hand, the sequential read and write performance is pretty good with synthetic and real world read speeds
being very close to the theoretical maximum of the 10GBit connection.
One thing to keep in mind: The blocksize when reading has a very strong impact on the performance. This
can be seen when using dd with different bs arguments. Of course, 1MiB is optimal if that is also used by NFS, and
cat seems to do this. However, cp does not which results in a much slower performance than if using dd if=.. of=.. bs=1M.
I have done measurements with plain nc over the wire (also reaching 1,160 MiB/s) and iperf3 which achieves 1,233 MiB/s just below the 1,250 MiB/s equivalent of 10Gbit.
Power consumption and thermals
For a computer running 24/7 in my flat, power consumption is of course important. I bought a device to measure
power consumption at the outlet to get an accurate picture.
idle
Because the computer is idle most of the time, optimising idle power usage is most important.
Change
W/h
default
50
*_cx_lowest="Cmax"
45
disable WiFi and BT
42
media 10gbase-t
45
machdep.hwpstate_pkg_ctrl=0
41
turn on chassis fans
42
ASPM modes to L0s+L1 / enabled
34
I assume that the same setup on Linux would be slightly more efficient, but 34W in idle is acceptable.
Clearly, the most impactful changes were:
Activating ASPM for the PCIe devices in the BIOS.
Adding performance_cx_lowest="Cmax" and economy_cx_lowest="Cmax" to /etc/rc.conf.
Adding machdep.hwpstate_pkg_ctrl=0 to /boot/loader.conf.
You can find online resources on what these options do. You might need to update the BIOS to be able to disable
WiFi and Bluetooth devices completely. You can also use hints in the /boot/device.hints, but this doesn’t save
as much power.
Using 10GBase-T speed on the network device (instead of 1000Base-T) unfortunately increases power usage notably, but
there is nothing I could find to mitigate this.
Things that are often recommended but that did not help me (at least not in idle):
NVME power states (more on this below)
lower values for sysctl dev.hwpstate_intel.*.epp (more on this below)
hw.pci.do_power_nodriver=3
idle temperatures
°C
CPU
37-40
NVMEs
52-55
The latter was particularly interesting, because I had heard that newer NVMEs, and especially those by Lexar get
very warm. It should be noted though, that the mainboard comes with a large heatsink that covers all NVMEs.
under load
The only “load test” that I performed was a scrub of the pool.
Since this puts stress on the NVMEs and also the CPUs, it should be at least indicative of how things are going.
during zpool scrub
°C
CPU
55-59
NVMEs
69-75
The power usage fluctuates between 85W and 98W. I think all of these values are acceptable.
NVME power state hint
scrub speed GiB/s
W/h
0 (default)
11
< 100
1
8
< 93
2
4
< 70
You can use nvmecontrol to tell the NVME disks to save energy. More information on this here
and here.
I was surprised that all of this works reliably on FreeBSD, but it does! The man-page is not great though. Simply
call nvmecontrol power -p X nvmeYns1 to set the hint to X on device Y, if desired. Note that this needs to be repeated after
every reboot.
dev.hwpstate_intel.*.epp
scrub speed GiB/s
W/h
50 (default)
11.0
< 100
100
3.3
< 60
You can use the dev.hwpstate_intel.*.epp sysctls for you cores to tune the eagerness of that core to scale up with
higher number meaning less eagerness.
In the end, I decided not to apply any of these “under load optimisations”.
It is just very difficult, because, as shown, all optimisations that reduce watts per time also increase time.
I am not certain of any good ways to quantify this, but it feels like keeping the system at 70W for 30min instead of 100W for 10min, is not really worth it.
And I kind of also want the system to be fast, that’s why I spent so much money on it 🙃
The CPU does have a cTDP mode that can be activated via the BIOS and which is “worth it”, according to some articles
I have read. I might give this a try in the future.
Final remarks
What a ride! I spent a lot of time optimising and benchmarking this and I am quite happy with the outcome.
I am able to exhaust the 10GBit LAN connection completely, and still have resources left on the server :)
Thanks to the people at www.bsdforen.de who had quite a few helpful suggestions.
If you see anything that I missed, or have suggestions on how to improve this setup, let me know in the comments!
Footnotes
With ASUS being the only exception. ↩︎
Proper in this context means well-supported by FreeBSD and with a good performance.
Usually, that means an Intel NIC. Unfortunately all the modern boards come Marvell/Aquantia AQtion adaptors which
are not well-supported by FreeBSD. ↩︎
The geli device was created with: geli init -b -s4096 -l256 ↩︎
I wanted to perform all these tests with Linux as well, but I ran out of time 🙈 ↩︎
I did try a slightly more more modern adapter with Intel 82599EN chip. This is a SFP+ chip, but I found an
adaptor with built-in 10GBase-T for around 150€. It ended up having some driver issues (you needed to plug and unplug
the CAT cable for the device to go UP), and it used more energy than the X540, so I sent it back. ↩︎
Meta Horizon OS is a variant of Android, which includes GPLed parts, including the kernel Linux. Replicant is a fully free variant of Android that can run on smartphones and other kinds of devices. As the maintainer of libsurvive I have been working on a port to Android/Replicant which is known to work well with the Rockchip RK3399.
A few weeks ago, I asked for the source code for the Oclulus-Linux kernel, but until now the Meta Quest does not comply with the GPL. So I plan to make my own device running Replicant and maybe Guix codenamed the Replica Quest. The Replica Quest will include a user interface called LibreVR Mobile and on my POWER9 system I use LibreVR Desktop. Any part that Meta releases as free software can be integrated into Replicant. Non-free parts need to be replaced, that will be hard work.
Like last year, I attended the 10th
International Workshop on Plan 9 remotely,
presenting a talk about porting Inferno to various Cortex-M microcontrollers.
The presentation covers things that I mentioned in my
previous post, so I won't go into details.
My diary
entry has links to the video and materials.
Categories: Inferno,
Free Software
Make sure you commit anything you want to end up in the KDE Gear 24.05 releases to themNext Dates April 25 2024: 24.05 Freeze and Beta (24.04.80) tag & release May 9, 2024: 24.05 RC (24.04.90) Tagging and ReleaseMay 16, 2024: 24.05 TaggingMay 23, 2024: 24.05 Releasehttps://community.kde.org/Schedules/KDE_Gear_24.05_Schedule
On-and-off over the past few months I wrote a new tool called
Protokolo. I wrote earlier about how I implemented
internationalisation for this project. This blog post is a simple and short
introduction to the tool.
Protokolo—Esperanto for ‘report’ or ‘minutes’—is a change log generator. It
solves a very simple (albeit annoying) problem space at the intersection of
change logs and version control systems:
Different merge requests all edit the same area in CHANGELOG, inevitably
resulting in merge conflicts.
If a section for an unreleased version does not yet exist in the main branch’s
CHANGELOG (typically shortly after release), feature branches must create this
section. If multiple feature branches do this, you get more merge conflicts.
Old merge requests, when merged, sometimes add their change log entry to the
section of a release that is already published.
Protokolo gets rid of the above problems by having the user create a separate
file for each change log fragment (think: one new file per merge request). Then,
just before release, all the files get concatenated into a new section in
CHANGELOG.
This idea is not exactly new. Towncrier
does the same thing. Protokolo is only different in some of the implementation
details.
The documentation of Protokolo is—I
think—excellent and comprehensive. To prevent myself from repeating things in
this blog post, I recommend reading the documentation for a usage guide.
Barring some improvements I want to do to Click and
internationalisation, I think the
project is finished, insofar as software projects are ever finished. And that’s
pretty cool! I should finish software projects more often.
TL;DR—look at Protokolo and do
exactly what it does.
This is a short article because I am lazy but do want to be helpful. The
sections are the steps you should take. All code presented in this article is
licensed CC0-1.0.
Use gettext
As a first step, you should use
gettext. This effectively
means wrapping all string literals in _() calls. This article won’t waste a
lot of time on how to do this or how gettext works. Just make sure to get
plurals right, and make sure to provide translator comments where necessary.
I recommend using the class-based API. In your module, create the following file
i18n.py.
import gettext as _gettext_module
import os
_PACKAGE_PATH = os.path.dirname(__file__)
_LOCALE_DIR = os.path.join(_PACKAGE_PATH, "locale")
TRANSLATIONS = _gettext_module.translation(
"your-module", localedir=_LOCALE_DIR, fallback=True
)
_ = TRANSLATIONS.gettext
gettext = TRANSLATIONS.gettext
ngettext = TRANSLATIONS.ngettext
pgettext = TRANSLATIONS.pgettext
npgettext = TRANSLATIONS.npgettext
This assumes that your compiled .mo files will live in
your-module/locale/<lang>/LC_MESSAGES/your-module.mo. We’ll take care of that
later. Putting the compiled files there isn’t ideal (you want them in
/usr/share/locale), but it’s the best you can do with Python packaging.
In subsequent files, just do the following to translate strings:
from .i18n import _
# TRANSLATORS: translator comment goes here.
print(_("Hello, world!"))
However, the Click module doesn’t use our TRANSLATIONS object. To fix this, we
need to use the GNU gettext API. This is kind of dirty, because it messes with
the global state, so let’s do it in cli.py (the file which contains all your
Click groups and commands).
if gettext.find("your-module", localedir=_LOCALE_DIR):
gettext.bindtextdomain("your-module", _LOCALE_DIR)
gettext.textdomain("your-module")
Internationalise Click
When using Click, you have two challenges:
You need to translate the help docstrings of your groups and commands.
You need to translate the Click gettext strings.
Translating docstrings
Normally, you have some code like this:
@click.group(name="your-module")
def main():
"""Help text goes here."""
...
And when you run your-module --help, you get the following output:
$ your-module --help
Usage: your-module [OPTIONS] COMMAND [ARGS]...
Help text goes here.
Options:
--help Show this message and exit.
You cannot wrap the docstring in a _() call. So by necessity, we will need to
remove the docstring and do something like this:
_MAIN_HELP = _("Help text goes here.")
@click.group(name="your-module", help=_MAIN_HELP)
def main():
...
For multiple paragraphs, I translate each paragraph separately, which is easier
for the translators:
_HELP_TEXT = (
_("Help text goes here.")
+ "\n\n"
+ _(
"Longer help paragraph goes here. We use implicit string concatenation"
" to avoid putting newlines in the translated text."
)
)
Translate the Click gettext strings
We will create a script generate_pot.sh that generates our .pot file,
including the Click translations. My script-fu isn’t very good, but it appears
to work.
#!/usr/bin/env sh
# Set VIRTUAL_ENV if one does not exist.
if [ -z "${VIRTUAL_ENV}" ]; then
VIRTUAL_ENV=$(poetry env info --path)
fi
# Get all the translation strings from the source.
xgettext --add-comments --from-code=utf-8 --output=po/your-module.pot src/**/*.py
xgettext --add-comments --output=po/click.pot "${VIRTUAL_ENV}"/lib/python*/*-packages/click/**.py
# Put everything in your-module.pot.
msgcat --output=po/your-module.pot po/your-module.pot po/click.pot
# Update the .po files. Ideally this should be done by Weblate, but it appears
# that it isn't.
for name in po/*.po
do
msgmerge --output="${name}" "${name}" po/your-module.pot;
done
After running this script, all strings that must be translated are in your
.pot and existing .po files.
You can use the above script for argparse as well, with minor modifications.
Generate .pot file automagically
You don’t want to manually run the generate_pot.sh script. Instead, you want
the CI (Forgejo Actions) to run it on your behalf whenever a gettext string is
changed or introduced.
Use the following .forgejo/workflows/gettext.yaml file.
name: Update .pot file
on:
push:
branches:
- main
# Only run this job when a Python source file is edited. Not strictly
# needed.
paths:
- "src/your-module/**.py"
jobs:
create-pot:
runs-on: docker
container: nikolaik/python-nodejs:python3.11-nodejs21
steps:
- uses: actions/checkout@v3
- name: Install gettext and wlc
run: |
apt-get update
apt-get install -y gettext wlc
# We mostly install your-module to install the click dependency.
- name: Install your-module
run: poetry install --no-interaction --only main
- name: Lock Weblate
run: |
wlc --url https://hosted.weblate.org/api/ --key ${{secrets.WEBLATE_KEY }} lock your-project/your-module
- name: Push changes from Weblate to upstream repository
run: |
wlc --url https://hosted.weblate.org/api/ --key ${{secrets.WEBLATE_KEY }} push your-project/your-module
- name: Pull Weblate translations
run: git pull origin main
- name: Create .pot file
run: ./generate_pot.sh
# Normally, POT-Creation-Date changes in two locations. Check if the diff
# includes more than just those two lines.
- name: Check if sufficient lines were changed
id: diff
run:
echo "changed=$(git diff -U0 | grep '^[+|-][^+|-]' | grep -Ev
'^[+-]("POT-Creation-Date|#:)' | wc -l)" >> $GITHUB_OUTPUT
- name: Commit and push updated your-module.pot
if: ${{ steps.diff.outputs.changed != '0' }}
run: |
git config --global user.name "your-module-bot"
git config --global user.email "<>"
git add po/your-module.pot po/*.po
git commit -m "Update your-module.pot"
git push origin main
- name: Unlock Weblate
run: |
wlc --url https://hosted.weblate.org/api/ --key ${{ secrets.WEBLATE_KEY }} pull your-project/your-module
wlc --url https://hosted.weblate.org/api/ --key ${{ secrets.WEBLATE_KEY }} unlock your-project/your-module
The job is fairly self-explanatory. The wlc command talks with Weblate, which
we will set up soon. The job installs dependencies, gets the latest
translations from Weblate, generates the .pot, and then pushes the generated
.pot (and .po files) if there were changed strings.
See
reuse-tool
for a GitHub Actions job. It is currently missing the wlc locking.
Set up Weblate
Create your project in Weblate. In the VCS
settings, set version control system to ‘Git’. Set your source repository and
branch correctly. Set the push URL to
https://<your-token>@codeberg.org/your-name/your-module.git. You get the token
from https://codeberg.org/user/settings/applications. You will need to give
the token access to ‘repository’. There should be a more granular way of doing
this, but I am not aware of it.
Set the repository browser to
https://codeberg.org/your-name/your-module/src/branch/{{branch}}/{{filename}}#{{line}}.
Turn ‘Push on commit’ on, and set merge style to ‘rebase’. Also, always lock on
error.
In your project settings on Weblate, generate a project API token. Then in your
Forgejo Actions settings, create a secret named WEBLATE_KEY with the project
API token as value.
Publishing your translations with Poetry
Now that all the translation plumbing is working, you just need to make sure
that you generate your .mo files when building/publishing with Poetry.
We add a build step to Poetry using the undocumented build
script. Add the following to your pyproject.toml:
[tool.poetry.build]
generate-setup-file = false
script = "_build.py"
Do NOT name your file build.py. It will break Arch Linux
packaging.
Create the file _build.py. Here are the contents:
import glob
import logging
import os
import shutil
import subprocess
from pathlib import Path
_LOGGER = logging.getLogger(__name__)
ROOT_DIR = Path(os.path.dirname(__file__))
BUILD_DIR = ROOT_DIR / "build"
PO_DIR = ROOT_DIR / "po"
def mkdir_p(path):
"""Make directory and its parents."""
Path(path).mkdir(parents=True, exist_ok=True)
def rm_fr(path):
"""Force-remove directory."""
path = Path(path)
if path.exists():
shutil.rmtree(path)
def main():
"""Compile .mo files and move them into src directory."""
rm_fr(BUILD_DIR)
mkdir_p(BUILD_DIR)
msgfmt = None
for executable in ["msgfmt", "msgfmt.py", "msgfmt3.py"]:
msgfmt = shutil.which(executable)
if msgfmt:
break
if msgfmt:
po_files = glob.glob(f"{PO_DIR}/*.po")
mo_files = []
# Compile
for po_file in po_files:
_LOGGER.info(f"compiling {po_file}")
lang_dir = (
BUILD_DIR
/ "your-module/locale"
/ Path(po_file).stem
/ "LC_MESSAGES"
)
mkdir_p(lang_dir)
destination = Path(lang_dir) / "your-module.mo"
subprocess.run(
[
msgfmt,
"-o",
str(destination),
str(po_file),
],
check=True,
)
mo_files.append(destination)
# Move compiled files into src
rm_fr(ROOT_DIR / "src/your-module/locale")
for mo_file in mo_files:
relative = (
ROOT_DIR / Path("src") / os.path.relpath(mo_file, BUILD_DIR)
)
_LOGGER.info(f"copying {mo_file} to {relative}")
mkdir_p(relative.parent)
shutil.copyfile(mo_file, relative)
if __name__ == "__main__":
main()
It is probably a little over-engineered (building into build/ and then
consequently copying to src/your-module/locale is unnecessary), but it works.
Finally, make sure to actually include *.mo files in pyproject.toml:
include = [
{ path = "src/your-module/locale/**/*.mo", format="wheel" }
]
And that’s it! A rather dense and curt blog post, but it should contain helpful
bits and pieces.
A couple of months have elapsed since my last, brief progress report on L4Re development, so I suppose a few words are required to summarise what I have done since. Distractions, travel, and other commitments notwithstanding, I did manage to push my software framework along a little, encountering frustrations and the occasional sensation of satisfaction along the way.
Supporting Real Hardware
Previously, I had managed to create a simple shell-like environment running within L4Re that could inspect an ext2-compatible filesystem, launch programs, and have those programs communicate with the shell – or each other – using pipes. Since I had also been updating my hardware support framework for L4Re on MIPS-based devices, I thought that it was time to face up to implementing support for memory cards – specifically, SD and microSD cards – so that I could access filesystems residing on such cards.
Although I had designed my software framework with things like disks and memory devices in mind, I had been apprehensive about actually tackling driver development for such devices, as well as about whether my conceptual model would prove too simple, necessitating more framework development just to achieve the apparently simple task of reading files. It turned out that the act of reading data, even when almost magical mechanisms like direct memory access (DMA) are used, is as straightforward as one could reasonably expect. I haven’t tested writing data yet, mostly because I am not that brave, but it should be essentially as straightforward as reading.
What was annoying and rather overcomplicated, however, was the way that memory cards have to be coaxed into cooperation, with the SD-related standards featuring layer upon layer of commands added every time they enhanced the technologies. Plenty of time was spent (or wasted) trying to get these commands to behave and to allow me to gradually approach the step where data would actually be transferred. In contrast, setting up DMA transactions was comparatively easy, particularly using my interactive hardware experimentation environment.
There were some memorable traps encountered in the exercise. One involved making sure that the interrupts signalling completed DMA transactions were delivered to the right thread. In L4Re, hardware interrupts are delivered via IRQ (interrupt request) objects to specific threads, and it is obviously important to make sure that a thread waiting for notifications (including interrupts) expects these notifications. Otherwise, they may cause a degree of confusion, which is what happened when a thread serving “blocks” of data to the filesystem components was presented with DMA interrupt occurrences. Obviously, the solution was to be more careful and to “bind” the interrupts to the thread interacting with the hardware.
Another trap involved the follow-on task of running programs that had been read from the memory card. In principle, this should have yielded few surprises: my testing environment involves QEMU and raw filesystem data being accessed in memory, and program execution was already working fine there. However, various odd exceptions were occurring when programs were starting up, forcing me to exercise the useful kernel debugging tool provided with the Fiasco.OC (or L4Re) microkernel.
Of course, the completely foreseeable problem involved caching: data loaded from the memory card was not yet available in the processor’s instruction cache, and so the processor was running code (or potentially something that might not have been code) that had been present in the cache. The problem tended to arise after a jump or branch in the code, executing instructions that did undesirable things to the values of the registers until something severe enough caused an exception. The solution, of course, was to make sure that the instruction cache was synchronised with the data cache containing the newly read data using the l4_cache_coherent function.
Replacing the C Library
With that, I could replicate my shell environment on “real hardware” which was fairly gratifying. But this only led to the next challenge: that of integrating my filesystem framework into programs in a more natural way. Until now, accessing files involved a special “filesystem client” library that largely mimics the normal C library functions for such activities, but the intention has always been to wrap these with the actual C library functions so that portable programs can be run. Ideally, there would be a way of getting the L4Re C library – an adapted version of uClibc – to use these client library functions.
A remarkable five years have passed since I last considered such matters. Back then, my investigations indicated that getting the L4Re library to interface to the filesystem framework might be an involved and cumbersome exercise due to the way the “backend” functionality is implemented. It seemed that the L4Re mechanism for using different kinds of filesystems involved programs dynamically linking to libraries that would perform the access operations on the filesystem, but I could not find much documentation for this framework, and I had the feeling that the framework was somewhat underdeveloped, anyway.
My previous investigations had led me to consider deploying an alternative C library within L4Re, with programs linking to this library instead of uClibc. C libraries generally come across as rather messy and incoherent things, accumulating lots of historical baggage as files are incorporated from different sources to support long-forgotten systems and architectures. The challenge was to find a library that could be conveniently adapted to accommodate a non-Unix-like system, with the emphasis on convenience precluding having to make changes to hundreds of files. Eventually, I chose Newlib because the breadth of its dependencies on the underlying system is rather narrow: a relatively small number of fundamental calls. In contrast, other C libraries assume a Unix-like system with countless, specialised system calls that would need to be reinterpreted and reframed in terms of my own library’s operations.
My previous effort had rather superficially demonstrated a proof of concept: linking programs to Newlib and performing fairly undemanding operations. This time round, I knew that my own framework had become more complicated, employed C++ in various places, and would create a lot of work if I were to decouple it from various L4Re packages, as I had done in my earlier proof of concept. I briefly considered and then rejected undertaking such extra work, instead deciding that I would simply dust off my modified Newlib sources, build my old test programs, and see which symbols were missing. I would then seek to reintroduce these symbols and hope that the existing L4Re code would be happy with my substitutions.
Supporting Threads
For the very simplest of programs, I was able to “stub” a few functions and get them to run. However, part of the sophistication of my framework in its current state is its use of threading to support various activities. For example, monitoring data streams from pipes and files involves a notification mechanism employing threads, and thus a dependency on the pthread library is introduced. Unfortunately, although Newlib does provide a similar pthread library to that featured in L4Re, it is not really done in a coherent fashion, and there is other pthread support present in Newlib that just adds to the confusion.
Initially, then, I decided to create “stub” implementations for the different functions used by various libraries in L4Re, like the standard C++ library whose concurrency facilities I use in my own code. I made a simple implementation of pthread_create, along with some support for mutexes. Running programs did exercise these functions and produce broadly expected results. Continuing along this path seemed like it might entail a lot of work, however, and in studying the existing pthread library in L4Re, I had noticed that although it resides within the “uclibc” package, it is somewhat decoupled from the C library itself.
Favouring laziness, I decided to see if I couldn’t make a somewhat independent package that might then be interfaced to Newlib. For the most part, this exercise involved introducing missing functions and lots of debugging, watching the initialisation of programs fail due to things like conflicts with capability allocation, perhaps due to something I am doing wrong, or perhaps exposing conditions that are fortuitously avoided in L4Re’s existing uClibc arrangement. Ultimately, I managed to get a program relying on threading to start, leaving me with the exercise of making sure that it was producing the expected output. This involved some double-checking of previous measures to allow programs using different C libraries to communicate certain kinds of structures without them misinterpreting the contents of those structures.
Further Work
There is plenty still to do in this effort. First of all, I need to rewrite the remaining test programs to use C library functions instead of client library functions, having done this for only a couple of them. Then, it would be nice to expand C library coverage to deal with other operations, particularly process creation since I spent quite some time getting that to work.
I need to review the way Newlib handles concurrency and determine what else I need to do to make everything work as it should in that regard. I am still using code from an older version of Newlib, so an update to a newer version might be sensible. In this latest round of C library evaluation, I briefly considered Picolibc which is derived from Newlib and other sources, but I didn’t fancy having to deal with its build system or to repackage the sources to work with the L4Re build system. I did much of the same with Newlib previously and, having worked through such annoyances, was largely able to focus on the actual code as opposed to the tooling.
Currently, I have been statically linking programs to Newlib, but I eventually want to dynamically link them. This does exercise different paths in the C and pthread libraries, but I also want to explore dynamic linking more broadly in my own environment, having already postponed such investigations from my work on getting programs to run. Introducing dynamic linking and shared libraries helps to reduce memory usage and increase the performance of a system when multiple programs need the same libraries.
There are also some reasonable arguments for making the existing L4Re pthread implementation more adaptable, consolidating my own changes to the code, and also for considering making or adopting other pthread implementations. Convenient support for multiple C library implementations, and for combining these with other libraries, would be desirable, too.
Much of the above has been a distraction from what I have been wanting to focus on, however. Had it been more apparent how to usefully extend uClibc, I might not have bothered looking at Newlib or other C libraries, and then I probably wouldn’t have looked into threading support. Although I have accumulated some knowledge in the process, and although some of that knowledge will eventually have proven useful, I cannot help feeling that L4Re, being a fairly mature product at this point and a considerable achievement, could be more readily extensible and accessible than it currently is.
Migrate legacy openldap to a docker container.
Prologue
I maintain a couple of legacy EOL CentOS 6.x SOHO servers to different locations. Stability on those systems is unparalleled and is -mainly- the reason of keeping them in production, as they run almost a decade without a major issue.
But I need to do a modernization of these legacy systems. So I must prepare a migration plan. Initial goal was to migrate everything to ansible roles. Although, I’ve walked down this path a few times in the past, the result is not something desirable. A plethora of configuration files and custom scripts. Not easily maintainable for future me.
Current goal is to setup a minimal setup for the underlying operating system, that I can easily upgrade through it’s LTS versions and separate the services from it. Keep the configuration on a git repository and deploy docker containers via docker-compose.
In this blog post, I will document the openldap service. I had some is issues against bitnami/openldap docker container so the post is also a kind of documentation.
Preparation
Two different cases, in one I have the initial ldif files (without the data) and on the second node I only have the data in ldifs but not the initial schema. So, I need to create for both locations a combined ldif that will contain the schema and data.
And that took me more time that it should! I could not get the service running correctly and I experimented with ldap exports till I found something that worked against bitnami/openldap notes and environment variables.
ldapsearch command
In /root/.ldap_conf I keep the environment variables as Base, Bind and Admin Password (only root user can read them).
cat /usr/local/bin/lds
#!/bin/bash
source /root/.ldap_conf
/usr/bin/ldapsearch
-o ldif-wrap=no
-H ldap://$HOST
-D $BIND
-b $BASE
-LLL -x
-w $PASS $*
sudo lds > /root/openldap_export.ldif
Bitnami/openldap
GitHub page of bitnami/openldap has extensive documentation and a lot of environment variables you need to setup, to run an openldap service. Unfortunately, it took me quite a while, in order to find the proper configuration to import ldif from my current openldap service.
Through the years bitnami has made a few changes in libopenldap.sh which produced a frustrated period for me to review the shell script and understand what I need to do.
I would like to explain it in simplest terms here and hopefully someone will find it easier to migrate their openldap.
TL;DR
The correct way:
Create local directories
mkdir -pv {ldif,openldap}
Place your openldap_export.ldif to the local ldif directory, and start openldap service with:
docker compose up
---
services:
openldap:
image: bitnami/openldap:2.6
container_name: openldap
env_file:
- path: ./ldap.env
volumes:
- ./openldap:/bitnami/openldap
- ./ldifs:/ldifs
ports:
- 1389:1389
restart: always
volumes:
data:
driver: local
driver_opts:
device: /storage/docker
Your environmental configuration file, should look like:
cat ldap.env
LDAP_ADMIN_USERNAME="admin"
LDAP_ADMIN_PASSWORD="testtest"
LDAP_ROOT="dc=example,dc=org"
LDAP_ADMIN_DN="cn=admin,$ LDAP_ROOT"
LDAP_SKIP_DEFAULT_TREE=yes
Below we are going to analyze and get into details of bitnami/openldap docker container and process.
OpenLDAP Version in docker container images.
Bitnami/openldap docker containers -at the time of writing- represent the below OpenLDAP versions:
bitnami/openldap:2 -> OpenLDAP: slapd 2.4.58
bitnami/openldap:2.5 -> OpenLDAP: slapd 2.5.17
bitnami/openldap:2.6 -> OpenLDAP: slapd 2.6.7
list images
docker images -a
REPOSITORY TAG IMAGE ID CREATED SIZE
bitnami/openldap 2.6 bf93eace348a 30 hours ago 160MB
bitnami/openldap 2.5 9128471b9c2c 2 days ago 160MB
bitnami/openldap 2 3c1b9242f419 2 years ago 151MB
Initial run without skipping default tree
As mentioned above the problem was with LDAP environment variables and LDAP_SKIP_DEFAULT_TREE was in the middle of those.
cat ldap.env
LDAP_ADMIN_USERNAME="admin"
LDAP_ADMIN_PASSWORD="testtest"
LDAP_ROOT="dc=example,dc=org"
LDAP_ADMIN_DN="cn=admin,$ LDAP_ROOT"
LDAP_SKIP_DEFAULT_TREE=no
for testing: always empty ./openldap/ directory
docker compose up -d
By running ldapsearch (see above) the results are similar to below data
lds
dn: dc=example,dc=org
objectClass: dcObject
objectClass: organization
dc: example
o: example
dn: ou=users,dc=example,dc=org
objectClass: organizationalUnit
ou: users
dn: cn=user01,ou=users,dc=example,dc=org
cn: User1
cn: user01
sn: Bar1
objectClass: inetOrgPerson
objectClass: posixAccount
objectClass: shadowAccount
userPassword:: Yml0bmFtaTE=
uid: user01
uidNumber: 1000
gidNumber: 1000
homeDirectory: /home/user01
dn: cn=user02,ou=users,dc=example,dc=org
cn: User2
cn: user02
sn: Bar2
objectClass: inetOrgPerson
objectClass: posixAccount
objectClass: shadowAccount
userPassword:: Yml0bmFtaTI=
uid: user02
uidNumber: 1001
gidNumber: 1001
homeDirectory: /home/user02
dn: cn=readers,ou=users,dc=example,dc=org
cn: readers
objectClass: groupOfNames
member: cn=user01,ou=users,dc=example,dc=org
member: cn=user02,ou=users,dc=example,dc=org
so as you can see, they create some default users and groups.
Initial run with skipping default tree
Now, let’s skip creating the default users/groups.
cat ldap.env
LDAP_ADMIN_USERNAME="admin"
LDAP_ADMIN_PASSWORD="testtest"
LDAP_ROOT="dc=example,dc=org"
LDAP_ADMIN_DN="cn=admin,$ LDAP_ROOT"
LDAP_SKIP_DEFAULT_TREE=yes
(always empty ./openldap/ directory )
docker compose up -d
ldapsearch now returns:
No such object (32)
That puzzled me … a lot !
Conclusion
It does NOT matter if you place your ldif schema file and data and populate the LDAP variables with bitnami/openldap. Or use ANY other LDAP variable from bitnami/openldap reference manual.
The correct method is to SKIP default tree and place your export ldif to the local ldif directory. Nothing else worked.
Took me almost 4 days to figure it out and I had to read the libopenldap.sh.
That’s it !
Tag(s):
openldap,
docker,
bitnami,
docker-compose
SymPy is a lightweight symbolic mathematics library for Python under the
3-clause BSD license that can be used either as a library or in an interactive
environment. It features symbolic expressions, solving equations, plotting and
much more!
Creating and using functions
Creating a function is as simple as using variables and putting
them into a mathematical expression:
1
2
3
4
from sympy.abc import x, y
f = 2 * x**2 + 3 * y + 10
f.subs(((x, 4), (y, 5))) # yields 57
Line 1 imports the x and y
Symbols
from the abc collection of Symbols, line 3 creates the f function which is
$2x^2 + 3y + 10$, and line 4 evaluates f with values 3 and 5 for x and y,
respectively.
SymPy exports a large
list of
mathematical functions for more complex expressions such logarithm, exponential,
etc., and is able to analyze the fucntion’s characteristics over arbitrary
intervals:
1
2
3
4
5
from sympy import Interval, is_monotonic, minimum, sin
f = sin(x)
is_monotonic(f, Interval(0, 10)) # yields False
minimum(f, x, Interval(0, 10) ) # yields -1
Plotting
SymPy is able to easily plot functions on a given interval:
1
2
3
4
5
6
7
from sympy.plotting import plot
f = 1 / (1 + sympy.exp(-x))
p1 = plot(f, sympy.diff(f), (x, -10, 10), show=False, legend=True)
p1[0].label = 'sigmoid'
p1[1].label = 'derivative of sigmoid'
p1.show()
Line 1 imports the
plot()
function, line 3 creates the f Function object from the sigmoid
expression $\frac{1}{1+\exp^{-x}}$, line 4 plots f and its derivative between
-5 and 5, lines 5-6 set the legends labels and lines 7 shows the created plot:
Sigmoid and its derivative.
In a few lines of code, the library allows one to create a mathematical
function, do operations on it like computing its derivative and plot the result.
Moreover, as SymPy uses Matplotlib under the hood by
default, the plots are modifiable using the Matplotlib API.
SymPy also supports 3D plots with the
plot3d()
function which helps understanding the relationship between two variables and an
outcome. The following code computes the energy of the recoiling electron after
Compton scattering depending on the initial photon energy and the scattering
angle (in degrees) using the Compton scattering
formula : $$\beta = \arccos
\left(1 - \frac{Ee * 511}{E0 * (E0 - Ee)}\right) * \frac{180}{3.14159}$$
1
2
3
4
5
6
7
from sympy.plotting import plot3d
E0, Ee = sympy.symbols('E0 Ee')
beta = sympy.acos(1.0 - Ee * 511 / (E0 * (E0 - Ee))) * 180 / 3.14159
p1 = plot3d(beta, (E0, 1, 511), (Ee, 0, 400), show=False, size=(10,10))
p1.zlabel=r'$\beta$ angle'
p1.show()
Line 1 imports the plot3d function, line 3 creates the E0 (the initial
photon energy) and theta custom variables1, line 4 defines the beta
function which depends on the E0 and Ee variables, line 6 does the
plotting and defines the axes intervals, line 7 sets the axes’ labels and line 8
displays the following figure:
Compton angle depending on E0 and Ee.
Solving equations
SymPy also has an equation solver for algebraic equations and equations systems:
SymPy considers the equations strings to be equal to zero for ease of use.
1
2
3
4
5
6
f = 3 * x - 1
sympy.solveset(f, x) # yields 1/3
eq1 = x + 5 + y - 2
eq2 = -3 * x + 6 * y - 3
sympy.solve((eq1, eq2), (x, y)) # yields {x: -7/3, y: -2/3}
The equation solvers also works for boolean logic, where SymPy tells what should
be the truth values of the variables to satisfy a boolean expression:
1
sympy.satisfiable(x & ~y & (x | y)) # yields {x: True, y: False}
An unsatisfiable expression yields False.
Geometry
SymPy also features a geometry module allowing to perform geometric operations such as Points, Segments and Polygons. It’s
1
2
3
4
5
6
7
from sympy.geometry import Point, Segment, Polygon
from spb import plot_geometry
p = Polygon(Point(0, 0), Point(0, 3), Point(3, 3), Point(3, 0))
s = Segment(Point(1, 3), Point(4, 0))
p1 = plot_geometry(p,s, is_filled=False, legend=False)
p.intersect(s) # yields {Point2D(1, 3), Point2D(3, 1)}
Line 1 imports classes from the geometry module, Line 2 import the SymPy plotting backends library, which contains additional plotting features needed to plot geometric objects, line 3 and 4 create a polygon and a segment, respectively, line 6 plots the figure and line 7 returns the intersection points of the polygon and the segment. Line 6 produces the following figure:
Compton angle depending on E0 and Ee.
The SymPy library is thus easy to use and suitable for various applications.
Because it’s Free Software, anyone can use, share, study and improve it for
whatever purpose, just like mathematics.
We could use the x and y variables here but having custom variables
names makes reading the code easier. ↩︎
I seem to be spending too much time looking into obscure tales from computing history, but continuing an earlier tangent from a recent article, noting the performance of different computer systems at the end of the 1980s and the start of the 1990s, I found myself evaluating one of those Internet rumours that probably started to do the rounds about thirty years ago. We will get to that rumour – a tall tale, indeed – in a moment. But first, a chart that I posted in an earlier article:
Performance evolution of the Archimedes and various competitors
As this nice chart indicates, comparing processor performance in computers from Acorn, Apple, Commodore and Compaq, different processor families bestowed a competitive advantage on particular systems at various points in time. For a while, Acorn’s ARM2 processor gave Acorn’s Archimedes range the edge over much more expensive systems using the Intel 80386, showcased in Compaq’s top-of-the-line models, as well as offerings from Apple and Commodore, these relying on Motorola’s 68000 family. One can, in fact, claim that a comparison between ARM-based systems and 80386-based systems would have been unfair to Acorn: more similarly priced systems from PC-compatible vendors would have used the much slower 80286, making the impact of the ARM2 even more remarkable.
Something might be said about the evolution of these processor families, what happened after 1993, and the introduction of later products. Such topics are difficult to address adequately for a number of reasons, principally the absence of appropriate benchmark results and the evolution of benchmarking to more accurately reflect system performance. Acorn never published SPEC benchmark figures, nor did ARM (at the time, at least), and any given benchmark as an approximation to “real-world” computing activities inevitably drifts away from being an accurate approximation as computer system architecture evolves.
However, in another chart I made to cover Acorn’s Unix-based RISC iX workstations, we can consider another range of competitors and quite a different situation. (This chart also shows off the nice labelling support in gnuplot that wasn’t possible with the currently disabled MediaWiki graph extension.)
Performance of the Acorn R-series and various competitors in approximate chronological order of introduction: a chart produced by gnuplot and converted from SVG to PNG for Wikipedia usage.
Now, this chart only takes us from 1989 until 1992, which will not satisfy anyone wondering what happened next in the processor wars. But it shows the limits of Acorn’s ability to enter the lucrative Unix workstation market with a processor that was perceived to be rather fast in the world of personal computers. Acorn’s R140 used the same ARM2 processor introduced in the Archimedes range, but even at launch this workstation proved to be considerably slower than somewhat more expensive workstation models from Digital and Sun employing MIPS and SPARC processors respectively.
Fortunately for Acorn, adding a cache to the ARM2 (plus a few other things) to make the ARM3 unlocked a considerable boost in performance. Although the efficient utilisation of available memory bandwidth had apparently been a virtue for the ARM designers, coupling the processor to memory performance had put a severe limit on overall performance. Meanwhile, the designers of the MIPS and SPARC processor families had started out with a different perspective and had considered cache memory almost essential in the kind of computer architectures that would be using these processors.
Acorn didn’t make another Unix workstation after the R260, released in 1990, for reasons that could be explored in depth another time. One of them, however, was that ARM processor design had been spun out to a separate company, ARM Limited, and appeared to be stalling in terms of delivering performance improvements at the same rate as previously, or indeed at the same rate as other processor families. Acorn did introduce the ARM610 belatedly in 1994 in its Risc PC, which would have been more amenable to running Unix, but by then the company was arguably beginning the process of unravelling for another set of reasons to be explored another time.
So, That Tall Tale
It is against this backdrop of competitive considerations that I now bring you the tall tale to which I referred. Having been reminded of the Atari Transputer Workstation by a video about the Transputer – another fascinating topic and thus another rabbit hole to explore – I found myself investigating Atari’s other workstation product: a Unix workstation based on the Motorola 68030 known as the Atari TT030 or TT/X, augmenting the general Atari TT product with the Unix System V operating system.
On the chart above, a 68030-based system would sit at a similar performance level to Acorn’s R140, so ignoring aspirational sentiments about “high-end” performance and concentrating on a price of around $3000 (with a Unix licence probably adding to that figure), there were some hopes that Atari’s product would reach a broad audience:
As a UNIX platform, the affordable TT030 may leapfrog machines from IBM, Apple, NeXT, and Sun, as the best choice for mass installation of UNIX systems in these environments.
As it turned out, Atari released the TT without Unix in 1990 and only eventually shipped a Unix implementation in around 1992, discontinuing the endeavour not long afterwards. But the tall tale is not about Atari: it is about their rivals at Commodore and some bizarre claims that seem to have drifted around the Internet for thirty years.
Like Atari and Acorn, Commodore also had designs on the Unix workstation market. And like Atari, Commodore had a range of microcomputers, the Amiga series, based on the 68000 processor family. So, the natural progression for Commodore was to design a model of the Amiga to run Unix, eventually giving us the Amiga 3000UX, priced from around $5000, running an implementation of Unix System V Release 4 branded as “Amiga Unix”.
Reactions from the workstation market were initially enthusiastic but later somewhat tepid. Commodore’s product, although delivered in a much more timely fashion than Atari’s, will also have found itself sitting at a similar performance level to Acorn’s R140 but positioned chronologically amongst the group including Acorn’s much faster R260 and the 80486-based models. It goes without saying that Atari’s eventual product would have been surrounded by performance giants by the time customers could run Unix on it, demonstrating the need to bring products to market on time.
So what is this tall tale, then? Well, it revolves around this not entirely coherent remark, entered by some random person twenty-one years ago on the emerging resource known as Wikipedia:
The Amiga A3000UX model even got the attention of Sun Microsystems, but unfortunately Commodore did not jump at the A3000UX.
If you search the Web for this, including the Internet Archive, the most you will learn is that Sun Microsystems were supposedly interested in adopting the Amiga 3000UX as a low-cost workstation. But the basis of every report of this supposed interest always seems to involve “talk” about a “deal” and possibly “interest” from unspecified “people” at Sun Microsystems. And, of course, the lack of any eventual deal is often blamed on Commodore’s management and perennial villain of the Amiga scene…
There were talks of Sun Microsystems selling Amiga Unix machines (the prototype Amiga 3500) as a low-end Unix workstations under their brand, making Commodore their OEM manufacturer. This deal was let down by Commodore’s Mehdi Ali, not once but twice and finally Sun gave up their interest.
Of course, back in 2003, anything went on Wikipedia. People thought “I know this!” or “I heard something about this!”, clicked the edit link, and scrawled away, leaving people to tidy up the mess two decades later. So, I assume that this tall tale is just the usual enthusiast community phenomenon of believing that a favourite product could really have been a contender, that legitimacy could have been bestowed on their platform, and that their favourite company could have regained some of its faded glory. Similar things happened as Acorn went into decline, too.
Picking It All Apart
When such tales appeal to both intuition and even-handed consideration, they tend to retain a veneer of credibility: of being plausible and therefore possibly true. I cannot really say whether the tale is actually true, only that there is no credible evidence of it being true. However, it is still worth evaluating the details within such tales on their merits and determine whether the substance really sounds particularly likely at all.
So, why would Sun Microsystems be interested in a Commodore workstation product? Here, it helps to review Sun’s own product range during the 1980s, to note that Sun had based its original workstation on the Motorola 68000 and had eventually worked up the 68000 family to the 68030 in its Sun-3 products. Indeed, the final Sun-3 products were launched in 1989, not too long before the Amiga 3000UX came to market. But the crucial word in the previous sentence is “final”: Sun had adopted the SPARC processor family and had started introducing SPARC-based models two years previously. Like other workstation vendors, Sun had started to abandon Motorola’s processors, seeking better performance elsewhere.
A June 1989 review in Personal Workstation magazine is informative, featuring the 68030-based Sun 3/80 workstation alongside Sun’s SPARCstation 1. For diskless machines, the Sun 3/80 came in at around $6000 whereas the SPARCstation 1 came in at around $9000. For that extra $3000, the buyer was probably getting around four times the performance, and it was quite an incentive for Sun’s customers and developers to migrate to SPARC on that basis alone. But even for customers holding on to their older machines and wanting to augment their collection with some newer models, Sun was offering something not far off the “low-cost” price of an Amiga 3000UX with hardware that was probably more optimised for the role.
Sun will have supported customers using these Sun-3 models for as long as support for SunOS was available, eventually introducing Solaris which dropped support for the 68000 family architecture entirely. Just like other Unix hardware vendors, once a transition to various RISC architectures had been embarked upon, there was little enthusiasm for going back and retooling to support the Motorola architecture again. And, after years resisting, even Motorola was embracing RISC with its 88000 architecture, tempting companies like NeXT and Apple to consider trading up from the 68000 family: an adventure that deserves its own treatment, too.
So, under what circumstances would Sun have seriously considered adopting Commodore’s product? On the face of it, the potential compatibility sounds enticing, and Commodore will have undoubtedly asserted that they had experience at producing low-cost machines in volume, appealing to Sun’s estimate, expressed in the Personal Workstation review, that the customer base for a low-cost workstation would double for every $1000 drop in price. And surely Sun would have been eager to close the doors on manufacturing a product line that was going to be phased out sooner or later, so why not let Commodore keep making low-cost models to satisfy existing customers?
First of all, we might well doubt any claims to be able to produce workstations significantly cheaper than those already available. The Amiga 3000UX was, as noted, only $1000 or so cheaper than the Sun 3/80. Admittedly, it had a hard drive as standard, making the comparison slightly unfair, but then the Sun 3/80 was around already in 1989, meaning that to be fair to that product, we would need to see how far its pricing will have fallen by the time the Amiga 3000UX became available. Commodore certainly had experience in shipping large volumes of relatively inexpensive computers like the Amiga 500, but they were not shipping workstation-class machines in large quantities, and the eventual price of the Amiga 3000UX indicates that such arguments about volume do not automatically confer low cost onto more expensive products.
Even if we imagine that the Amiga 3000UX had been successfully cost-reduced and made more competitive, we then need to ask what benefits there would have been for the customer, for developers, and for Sun in selling such a product. It seems plausible to imagine customers with substantial investments in software that only ran on Sun’s older machines, who might have needed newer, compatible hardware to keep that software running. Perhaps, in such cases, the suppliers of such software were not interested or capable of porting the software to the SPARC processor family. Those customers might have kept buying machines to replace old ones or to increase the number of “seats” in their environment.
But then again, we could imagine that such customers, having multiple machines and presumably having them networked together, could have benefited from augmenting their old Motorola machines with new SPARC ones, potentially allowing the SPARC machines to run a suitable desktop environment and to use the old applications over the network. In such a scenario, the faster SPARC machines would have been far preferable as workstations, and with the emergence of the X Window System, a still lower-cost alternative would have been to acquire X terminals instead.
We might also question how many software developers would have been willing to abandon their users on an old architecture when it had been clear for some time that Sun would be transitioning to SPARC. Indeed, by producing versions of the same operating system for both architectures, one can argue that Sun was making it relatively straightforward for software vendors to prepare for future products and the eventual deprecation of their old products. Moreover, given the performance benefits of Sun’s newer hardware, developers might well have been eager to complete their own transition to SPARC and to entice customers to follow rapidly, if such enticement was even necessary.
Consequently, if there were customers stuck on Sun’s older hardware running applications that had been effectively abandoned, one could be left wondering what the scale of the commercial opportunity was in selling those customers more of the same. From a purely cynical perspective, given the idiosyncracies of Sun’s software platform from time to time, it is quite possible that such customers would have struggled to migrate to another 68000 family Unix platform. And even without such portability issues and with the chance of running binaries on a competing Unix, the departure of many workstation vendors to other architectures may have left relatively few appealing options. The most palatable outcome might have been to migrate to other applications instead and to then look at the hardware situation with fresh eyes.
And we keep needing to return to that matter of performance. A 68030-based machine was arguably unappealing, like 80386-based systems, clearing the bar for workstation computing but not by much. If the cost of such a machine could have been reduced to an absurdly low price point then one could have argued that it might have provided an accessible entry point for users into a vendor’s “ecosystem”. Indeed, I think that companies like Commodore and Acorn should have put Unix-like technology in their low-end products, harmonising them with higher-end products actually running Unix, and having their customers gradually migrate as more powerful computers became cheaper.
But for workstations running what one commentator called “wedding-cake configurations” of the X Window System, graphical user interface toolkits, and applications, processors like the 68030, 80386 and ARM2 were going to provide a disappointing experience whatever the price. Meanwhile, Sun’s existing workstations were a mature product with established peripherals and accessories. Any cost-reduced workstation would have been something distinct from those existing products, impaired in performance terms and yet unable to make use of things like graphics accelerators which might have made the experience tolerable.
That then raises the question of the availability of the 68040. Could Commodore have boosted the Amiga 3000UX with that processor, bringing it up to speed with the likes of the ARM3-based R260 and 80486-based products, along with the venerable MIPS R2000 and early SPARC processors? Here, we can certainly answer in the affirmative, but then we must ask what this would have done to the price. The 68040 was a new product, arriving during 1990, and although competitively priced relative to the SPARC and 80486, it was still quoted at around $800 per unit, featuring in Apple’s Macintosh range in models that initially, in 1991, cost over $5000. Such a cost increase would have made it hard to drive down the system price.
In the chart above, the HP 9000/425t represents possibly the peak of 68040 workstation performance – “a formidable entry-level system” – costing upwards of $9000. But as workstation performance progressed, represented by new generations of DECstations and SPARCstations, the 68040 stalled, unable to be clocked significantly faster or otherwise see its performance scaled up. Prominent users such as Apple jumped ship and adopted PowerPC along with Motorola themselves! Motorola returned to the architecture after abandoning further development of the 88000 architecture, delivering the 68060 before finally consigning the architecture to the embedded realm.
In the end, even if a competitively priced and competitively performing workstation had been deliverable by Commodore, would it have been in Sun’s interests to sell it? Compatibility with older software might have demanded the continued development of SunOS and the extension of support for older software technologies. SunOS might have needed porting to Commodore’s hardware, or if Sun were content to allow Commodore to add any necessary provision to its own Unix implementation, then porting of those special Sun technologies would have been required. One can question whether the customer experience would have been satisfactory in either case. And for Sun, the burden of prolonging the lifespan of products that were no longer the focus of the company might have made the exercise rather unattractive.
Companies can always choose for themselves how much support they might extend to their different ranges of products. Hewlett-Packard maintained several lines of workstation products and continued to maintain a line of 68030 and 68040 workstations even after introducing their own PA-RISC processor architecture. After acquiring Apollo Computer, who had also begun to transition to their own RISC architecture from the 68000 family, HP arguably had an obligation to Apollo’s customers and thus renewed their commitment to the Motorola architecture, particularly since Apollo’s own RISC architecture, PRISM, was shelved by HP in favour of PA-RISC.
It is perhaps in the adoption of Sun technology that we might establish the essence of this tale. Amiga Unix was provided with Sun’s OPEN LOOK graphical user interface, and this might have given people reason to believe that there was some kind of deeper alliance. In fact, the alliance was really between Sun and AT&T, attempting to define Unix standards and enlisting the support of Unix suppliers. In seeking to adhere most closely to what could be regarded as traditional Unix – that defined by its originator, AT&T – Commodore may well have been picking technologies that also happened to be developed by Sun.
This tale rests on the assumption that Sun was not able to drive down the prices of its own workstations and that Commodore was needed to lead the way. Yet workstation prices were already being driven down by competition. Already by May 1990, Sun had announced the diskless SPARCstation SPC at the magic $5000 price point, although its lowest-cost colour workstation was reportedly the SPARCstation IPC at a much more substantial $10000. Nevertheless, its competitors were quite able to demonstrate colour workstations at reasonable prices, and eventually Sun followed their lead. Meanwhile, the Amiga 3000UX cost almost $8000 when coupled with a colour monitor.
With such talk of commodity hardware, it must not be forgotten that Sun was not without other options. For example, the company had already delivered SunOS on the Sun386i workstation in 1988. Although rather expensive, costing $10000, and not exactly a generic PC clone, it did support PC architecture standards. This arguably showed the way if the company were to target a genuine commodity hardware platform, and eventually Sun followed this path when making its Solaris operating system available for the Intel x86 architecture. But had Sun had a desperate urge to target commodity hardware back in 1990, partnering with a PC clone manufacturer would have been a more viable option than repurposing an Amiga model. That clone manufacturer could have been Commodore, too, but other choices would have been more convincing.
Conclusions and Reflections
What can we make of all of this? An idle assertion with a veneer of plausibility and a hint of glory denied through the notoriously poor business practices of the usual suspects. Well, we can obviously see that nothing is ever as simple as it might seem, particularly if we indulge every last argument and pursue every last avenue of consideration. And yet, the matter of Commodore making a Unix workstation and Sun Microsystems being “interested in rebadging the A3000UX” might be as simple as imagining a rather short meeting where Commodore representatives present this opportunity and Sun’s representatives firmly but politely respond that the door has been closed on a product range not long for retirement. Thanks but no thanks. The industry has moved on. Did you not get that memo?
Given that there is the essence of a good story in all of this, I consulted what might be the first port of call for Commodore stories: David Pleasance’s book, “Commodore The Inside Story”. Sadly, I can find no trace of any such interaction, with Unix references relating to a much earlier era and Commodore’s Z8000-based Unix machine, the unreleased Commodore 900. Yet, had such a bungled deal occurred, I am fairly sure that this book would lay out the fiasco in plenty of detail. Even Dave Haynie’s chapter, which covers development of the Amiga 3000 and subsequent projects, fails to mention any such dealings. Perhaps the catalogue of mishaps at Commodore is so extensive that a lucrative agreement with one of the most prominent corporations in 1990s computing does not merit a mention.
Interestingly, the idea of a low-cost but relatively low-performance 68030-based workstation from a major Unix workstation vendor did arrive in 1989 in the form of the Apollo DN2500, costing $4000, from Hewlett-Packard. Later on, Commodore would apparently collaborate with HP on chipset development, with this being curtailed by Commodore’s bankruptcy. Commodore were finally moving off the 68000 family architecture themselves, all rather too late to turn their fortunes around. Did Sun need a competitive 68040-based workstation? Although HP’s 9000/425 range was amongst the top sellers, Sun was doing nicely enough with its SPARC-based products, shipping over twice as many workstations as HP.
While I consider this tall tale to be nothing more than folklore, like the reminiscences of football supporters whose team always had a shot at promotion to the bigger league every season, “not once but twice” has a specificity that either suggests a kernel of truth or is a clever embellishment to sustain a group’s collective belief in something that never was. Should anyone know the real story, please point us to the documentation. Or, if there never was any paper trail but you happened to be there, please write it up and let us all know. But please don’t just go onto Wikipedia and scrawl it in the tradition of “I know this!”
For the record, I did look around to see if anyone recorded such corporate interactions on Sun’s side. That yielded no evidence, but I did find something else that was rather intriguing: hints that Sun may have been advised to try and acquire Acorn or ARM. Nothing came from that, of course, but at least this is documentation of an interaction in the corporate world. Of stories about something that never happened, it might also be a more interesting one than the Commodore workstation that Sun never got to rebadge.
Update: I did find a mention of Sun Microsystems and Unix International featuring the Amiga 3000UX on their exhibition stands at the Uniforum conference in early 1991. As noted above, Sun had an interest in promoting adoption of OPEN LOOK, and Unix International – the Sun/AT&T initiative to define Unix standards – had an interest in promoting System V Release 4 and, to an extent, OPEN LOOK. So, while the model may have “even got the attention of Sun Microsystems”, it was probably just a nice way of demonstrating vendor endorsement of Sun’s technology from a vendor who admitted that what it could offer was not “competitive with Sun” and what it had to offer.
“I Love Free Software Day” is a nice and positive campaign of FSFE to thank the people that enable Free Software on Valentines day. With many gatherings it is also a good opportunity to get together. In the Netherlands there was a workshop in The Hague and we had a meeting in Arnhem at hackerspace Hack42.
The meeting started with a tour for those that haven’t visisted the hackerspace before. Especially because Hack42 only recently moved to this location. Then we could start for real. First an introduction round while enjoying slices of pizza. Everybody told about their personal experiences with Free Software and about the software and people that deserve a thank you.
In this way we learned about different software: web browsers Waterfox and Firefox, browser addon Vimium, desktop environment KDE, music program Audacity, text editor Vim (in memoriam Bram Moolenaar), photo importer Rapid Photo Downloader, smartphone operating systems CalyxOS and UBports, smartphone installer OpenAndroidInstaller, catalog software Omeka, compiler Free Pascal, personal cloud environment Nextcloud, document editor LibreOffice and home automation software Home Assistant. This was an inspiring and insightful round. Remarkable was that for almost everybody Firefox was one of the first Free Software applications.
Writing of thank you’s started mostly with email and chat because most projects and developers lack a postal address. But after some research more and more handwritten I Love Free Software Day postcards ended up on the table, ready to send. It was great to see the collaboration by supporting each others cards with a signature. While were at it we also noticed some thank you’s online on social media. The animated harts by Fedora really stood out.
It was a great evening that really brought the community together. I’m proud of the enthousiasm and kind words. Hopefully the sent thank you’s have a great impact.
I’m already looking forward to a love-filled meeting next year.