The GitHub Pages version of this Blog is still a work in progress. For a better viewing experience, view the source code for ths blog here in its source code tree.
I always thought that npm was just the package manager component of Node.js. Actually it is not. The name "npm" does not even stand for node package manager. According to the npm/cli GitHub repo README.md,
Contrary to popular belief, npm is not in fact an acronym for
"Node Package Manager"; It is a recursive ba:wqcronymic abbreviation
for "npm is not an acronym" (if the project was named "ninaa",
then it would be an acronym). The precursor to npm was actually
a bash utility named "pm", which was the shortform name of
"pkgmakeinst" - a bash function that installed various things
on various platforms. If npm were to ever have been considered
an acronym, it would be as "node pm" or, potentially "new pm".
After several hours of web searching mostly secondary, non-authoritative sources, this is what I found,
"Authoritative" sources like GitHub, Microsoft, and all 342 npm GitHub repos are vague regarding the corporate ownership structure. When I tried to research this through Dun & Bradstreet I hit a paywall.
From this GitHub blog dated March 16, 2020",
Later this year, we will enable npm’s paying customers to move their
private npm packages to GitHub Packages—allowing npm to exclusively
focus on being a great public registry for JavaScript.
Looks like npm (the repository) is Micro$oft's loss leader for private JavaScript package hosting. At least Google didn't buy npm.
This project is similar to one I created back on 2024-01-21 to take my first beginning steps with TypeScript (TS). Unlike that project, I am starting off at an intermediate skill level with Lua. My experience comes from maintaining my Lua based Neovim configuration files and helping my daughters with Luau based Roblox code. See
Most of the front-end developers I work with started off learning React. Someday I might do so too, with React or whatever its successor might be, but not before implementing a crude web framework myself.
I wish I lived in a world where Lua, and not TypeScript, was the embedded language of web browsers.
I started another Python Package Index project named grscheller.circular-array back on 2024-01-28. I split this data structure out of grscheller.datastructures. It is a stable release at version 2.0.0 (I was a bit optimistic for version 1.0.0). It is used by both my other PyPI projects. I thought it might be more useful to the Python development community if it were its own project and not just a utility class buried in my grscheller.datastructures project.
The CircularArray class implements the classic circular array datatype from college level computer science data structure courses. It is a stateful, auto-resizing, indexable, double sided queue data structure with O(1) indexing and O(1) pushes and pops from either end. This data structure is not slicable.
When iterated over, it caches its current state so that the data structure can safely mutate while the iterator leisurely iterates.
The class wraps a python list. It can be used directly as an improved
version of a Python List, or in the implementation of other data
structures in a "has-a" relationship. It uses __slots__ for
size and speed efficiency. It is not designed to be used as the base of
some sort of inheritance hierarchy, so if that is what you want to do,
you will need to add a __dict__ to it. Or just fork it and
take out the slots.
I now maintain two projects on the Python Package Index (PyPI).
At work last year, late in the summer, I was a bit sort on my "acquisition continuous learning points." I work for a DoD research lab and my position is acquisition coded. A coworker suggested I take on data structures on-line course. I thought it might be a nice review. I had experience in most of the data structures covered, but I had never heard of one called a "circular array" before. So I coded one up quickly in Python. I thought of adding it to my mosh-pit of code snippets I have in my scheller-linux-archive GitHub repo. Well, over the past several years I have been struggling to grok the Python packaging ecosystem. Using this as an opportunity to learn, I decided to make my little circular array program into its own PyPI project.
Well, that little circular array program has grown into a data structure package that supports functional programming. I tried to keep the package pythonic. It does not force functional programmming onto the user, nor does it force uncaught exceptions either. The data structures do not store Python None as a value. This empowers the package to semantically interpret None as a non-existent value. How does one store something that does not exist in a concrete data structure anyway? Any case, I do use None as an implementation detail.
The second project, Daddy's Boring Math Library, is based on a Python module I wrote back in 2016 when I started to seriously learn Python. The name was suggested by my then 13 year old daughter Mary. I have Master degrees in Mathematics and Physics, so I expect this project to gradually grow over the next few years based on my recreational mathematical interests.
Both projects use Flit as the build and publishing tool to PyPI.
Moved this blog from the grscheller/scheller-linux-archive wiki to GitHub Pages. I maintain the blog in my grscheller/web repo. This repo is where I have started keeping my software deveopment related web content. It made more sense just deploying my to GitHub Pages than making it a part of that repo's wiki.
I will continue maintaining the blog in Markdown, but am using Pandoc to convert it to HTML. The best thing now is that I can maintain the Markdown using Neovim.
Started new repo: grscheller/fpinScala3Stdlib to update the work done in my grscheller/scheller-linux-archive repo where I was working my way through the book Functional Programming in Scala by Paul Chiusano and Runar Bjarnason.
The direction of this effort is no longer to recreate an entire FP infrastructure from scratch. Instead it is to leverage the Scala Standard libraries and selected external libraries to give efficient examples of functional programming.
I was originally inspired to do this from ShapelessCat/fpinscala3 updated for Scala 3. At this point, I will use Chiusano's and Bjarnason's book more for inspiration than as a tutorial.
While determining how likely one of my GitHub repositories will come up on an internet search, I stumbled upon this blog of mine. I figured its time I give it a little love.
One thing I have started doing differently is using only one space between sentences. Won't have any effect on the rendered Markdown produced for this blog. At work I noticed that everyone below the age of about 35 never uses two spaces between sentences. Time to help progress the English language a little bit.
In Neovim :help one way to tell if you're looking at
older Vim documentation is if two spaces are used between sentences.
As I write this, I feel completely handicapped by the native text editing interface GitHub provides. It is not as bad as the ones provides by email and Microsoft 360 web clients, but it is not Neovim. I won't hold my breath waiting for a Vim based interface. Probably start editing this with nvim in a terminal and cut-n-paste here.
I find it interesting that the GitHub editing client is pegging "Neovim" and "nvim" as spelling mistakes, but not Emacs, Vim, nor Nano.
I wish I did this a year ago, maybe several years ago if I went with i3 first.
What was holding me back was the proprietary NVIDIA drives my laptop used. I had chosen GNOME3 because that was what I was forced to use at work and it was the only thing that seemed to work with my laptop several years ago. I knew Wayland was on the horizon and I wanted a WM that supported it.
I was pleased to hear that the NVIDIA drivers were finally going to support GBM. My hopes were dashed when I learned this was only for new video cards. The NVIDIA cards in my personal and work laptops were never going to support anything other than EGL.
Final I got a laptop at work where the UEFI BIOS was not locked down. I installed Arch Linux and NOT the NVIDIA proprietary drivers. I was worried that learning the Sway keybindings would be a burden, but with Sway the keybindings seem natural and intuitive, unlike keybindings associated with various IDE's I've used off and on over the years.
I was pleasantly surprised to find that out-of-the-box Sway is sloppy mouse focused, though with a tiling WM this is not as important anymore. The amount of unnecessary window shuffling has become non-existent. The desktop feels very light weight and fast.
I have decided to abandon using NVIDIA proprietary drives and if possible NVIDIA hardware. Both personal and work laptops have hybrid Intel/NVIDIA chip sets. Both Intel i915 and nouveau kernel modules are loaded. Not entirely sure which chip sets are actually being used by Wayland.
I am happy that I finally get to use Wayland. Even the X Server/XFree86 release manager, Adam Jackson from Redhat, recommends its time we start to migrate off Xorg.
In the last 2 months I have redone my Neovim configuration several
times. Now I am using ~/.config/nvim/init.lua for my
config. I am sorting out neovim/nvim-lspconfig as well as
scalameta/nvim-metals for Scala development and
simrat39/rust-tools.nvim to configure the rust-analizer LSP
server for Rust development.
I have a lot of tweaking to do, but I finally got Metals to work with
Scala 3 code on Arch Linux. The problem was that it was using the wrong
version of the Scala compiler. By dropping
val scala3Version = "3.0.0" from the top of build.sbt and
hardcoding the version later on, things worked. Metals must grok
build.sbt at a very early stage to determine the version of the Scala
compiler to use.
The Scala 3 code in question, grok/Scala3/scalaImplicits
from my scheller-linux-archive GitHub repo, is a
translation of a Scala 2 version,
grok/Scala2/learnScala/implicits, which explored Scala
implicits.
Still can't figure out why lspconf configured pyright is failing to
find my Python libraries in a very simple project where I have a very
simple $PYTHONPATH, lib:../lib, available in
the environment.
After 3 years of stagnating with Scala, I am finally making some forward progress. I have sorted out many of the various overloaded meanings of implicit in Scala 2, just in time for this to all change for Scala 3. In Scala 2, implicit conversions, implicit classes, and implicit values for implicit parameters are all different concepts. Now I have to learn how all these have been cleaned up in Scala 3.
I really want to like SBT, but there is still too much opaque magic going on. When I invoking SBT 1.5.0 on a Scala 3.0.0 project, the first thing it did was to download, locally install, and use SBT 1.5.2. Nothing in the configuration files I created said anything about using a different version of SBT. I have no clue where this choice of SBT is coming from nor is it obvious to me even to know where to start looking for where this is configured.
Scala 3.0.0 reuses the same standard libraries as Scala 2.13.15. As an artifact of this, in the Scala 3.0.0 REPL
scala> scala.util.Properties.versionString
val res1: String = version 2.13.5This is due to this version string being defined in the 2.13.15 standard library. In Scala 3.0.0, but not any of the out-of-the-box 2.13.* versions,
scala> dotty.tools.dotc.config.Properties.versionString
val res0: String = version 3.0.0So, there seems to be no "standard" way to universally check the version of Scala you are running on at either run time or in the REPL.
Recently I noticed that configuring Alacritty terminal emulator to start the fish shell caused environment variables to be defined which should not have been. Also the $PATH was badly munged. Making fish my login shell fixed the $PATH munging issues, but stuff configured only in my POSIX startup scripts was still making it into my fish environment. Turns out, that as of at least Gnome Shell 3.38.4, Gnome Display Manager was causing this.
GDM NON-INTERACTIVELY sources my
~/.profile with /etc/gdm/Xsession using /bin/sh during the
Gnome3 startup process!!! Now, ~/.profile is supposed to be sourced only
by interactive shells. Fixed the problem by putting an interactive shell
test in ~/.profile, like I have in my ~/.bashrc and ~/.shrc files.
This sourcing behavior might come in handy, especially if I ever want to play around alternate $XDG_CONFIG_HOME configurations. Just wished I would have been given a heads up on this behavior.
There is no such thing as the POSIX shell. POSIX shell is an IEEE/Open Group specification. The original AT&T "Bourne Shell" is not a POSIX compliant shell. The POSIX Shell specification says what a POSIX compliant shell must do when given a POSIX complient script. The specification does not say what a POSIX compliant shell should do, or not do, when given a non-POSIX complient script. A shell running in strict POSIX compatibility mode is only limited to what it can do when given a POSIX compliant feature. If a script runs on one POSIX compliant shell, there is no guarantee that it will run on another POSIX compliant shell.
So, how does one test a shell script to make sure it contains only POXIX compliant features? I find the ShellCheck utility a very valuable resource. This is especially true when ShellCheck is paired with the Syntastic Vim plugin.
Writing portable shell scripts can be a challenge. Some people try to write in the most lowest common denominator of shell to accomplish this. I think this is a fool's errand. How can one design a script to work against every possible Bourne descendant shell ever to have existed, unless one tests it against every possible Bourne descendant shell ever to have existed?
Traditionally, a UNIX shell sets up an initial shell environment when logging into a system via a login shell. The shell would source a file like ~/.profile to establish an initial $PATH and export shell variables. Then it would source a file referenced by the environment variable $ENV, typically ~/.shrc or ~/.shinit, to pick up shell functions and aliases.
Aliases and shell functions are not exported to the environment but are picked up afresh with each new shell session via sourcing config files like ~/.bashrc. (Actually, shell functions can be exported to the environment, but this is not typically what is done). By shell session, I am talking about a completely new instance of the shell, not just a subshell.
This worked well until the age of Display Managers. A Display Manager is an X-windows client that logs you directly into your X-session. X-Windows is already running under root and a user owned Session Manager sets up the Desktop Environment. From this environment, client programs, including terminal emulators, can be launched. The user is "logged" into the X-Session, not a login shell. As a result, .profile does not get sourced.
Why not just use .bashrc to configure an initial Bash environment? The problem is is that .bashrc will force every bash shell to the exact same configuration, not just the first initial shell in a terminal window.
When I first started using AT&T System V UNIX, I would login at a real terminal, sometimes connected directly to computer, other times through a network terminal server, and, after logging in, be in a login shell.
Later I would telnet or dial into the UNIX host via a DOS/Windows telnet or hyperterminal PC client. Again, invoking a login shell.
I first started using UNIX Desktop Environments via a DOS based protected mode PC X-terminal emulator and the Tab Window Manager (twm). Later I used CDE on Solaris 2.6 with an actual X-terminal. An X-terminal was a TCP/IP networked CRT & keyboard that ran an embedded X-server without a window manager. In both cases, the BOOTP protocol was used to figured out what UNIX host to contact and display back an X-windows "console window" client. After logging in with such a "console window," guess what, you were in a ksh login shell. AFTER logging in, you would use the startx command to launch a remote Window Manager client to manage the remote applications displayed in the local X-Windows server. Back then I think the Window Manager doubled as the Session Manager, but I could be wrong.
You see the pattern? Configure your initial environment with .profile and used .kshrc to configure aliases and functions. (Back then I only used functions in shell scripts and never used aliases at all - I may not have even known about .kshrc) One file to establish a baseline environment for the initial shell invocation, and another to configure shell behaviors which stayed consistent across all subsequent shell invocations.
So, to correctly configure an initial shell environment, I put a
hooks in my .rc files to source a file called .envrc to set
up the initial environment if this had not aleady been done. My .profile
also sources this file.
No shell variables get "exported" in my rc files. Don't need to
unless I wanted programs other than the shell to see them. In that case
it would be better to put such exports in my surrogate for .profile,
.envrc.
I see the desktop environment as an extension to the command line environment. I wish my command line and desktop environments to complement and interact with each other. I use shell environments to help manage my programming environments.
Over the last 3 weeks I lost several days of effort getting an NVIDIA CUDA environment implemented on Windows 10 using Anaconda Python and the NVIDIA CUDA development kit. The OEM laptop had a NVIDIA Quadro M620 secondary video card (one not physically hooked up to the display), primarily for gaming purposes, which "should" be CUDA compatible.
This installation would have only taken me an hour or two if Microsoft didn't hide Windows Device Manager on me! Installation went fine, apart from having to install NVIDIA's Visual Studio components to keep the installation program happy.
When I ran a pyTorch python program, it failed to use CUDA.
So, went to open Control Panel, Control Panel program not on start menu. Something called "Settings App." OK, cell phone terminology. Opened this and selected Devices. I just assumed this was the name of the device configuration tool in Windows now, like how Windows 3.11 Program Manager evolved into the Taskbar and Windows 3.11 File Manager evolved into Windows Explorer. Bad assumption. Was there no way to list the devices on the PCI bus and their associated device drivers anymore???
At this point, all MS had to do was leave a Device Manager link right there, for me to find, not create something called "Settings App" which stopped me from looking further. After 3 weeks of installs not failing but pyTorch not using CUDA, I came across the "Device Manager" terminology in some 10 year old blog post and, not expecting anything to happen, typed Device Manager into the Start Menu. Lo and behold, good old Device Manager launched. With an "!" point on the icon for the NVIDIA card. Drilling down on the icon I discover an error message:
Windows cannot verify the digital signature for the drivers
required for this device. A recent hardware or software
change might have installed a file that is signed
incorrectly or damaged, or that might be malicious
software from an unknown source. (Code 52)Some web searching on this terminology and "Code 52" identified the problem, Windows was using Secure Boot to "blacklist" the NVIDIA drivers I installed.
After going into the UEFI and turning off Secure Boot, pyTorch worked flawlessly with CUDA.
Windows Device Manager still exists and provides useful functionality, but is totally disconnected from any GUI/App/Tool which a naive user will stumble upon. This says to me that Microsoft does not give a rat's arse about the curious end user wanting a deeper understanding of, and ability to leverage, their operating system. This stinks of the same "at all costs protect end-users from themselves" mentality that we see in Linux desktops environments where the terminal emulator is made very difficult for new end-users to find.
On GNU/Linux, at least Arch Linux using the GNU glibc library, there
is a trick used in /usr/include/bits/confname.h, included by
/usr/include/unistd.h, to define the _SC_*,
_PC_*, and _SC_* macros used with the sysconf,
pathconf, and confstr library functions.
The POSIX standard calls for _PC_*, _SC_*,
and _SC_* to be defined as C preprocessor macros. GNU/Linux
implements them as enumerations, but then turns around and defines
macros with the exact same names and values as the enumeration
symbols.
enum
{
_PC_LINK_MAX,
#define _PC_LINK_MAX _PC_LINK_MAX
_PC_MAX_CANON,
#define _PC_MAX_CANON _PC_MAX_CANON
_PC_MAX_INPUT,
#define _PC_MAX_INPUT _PC_MAX_INPUT
.
.
.
_PC_2_SYMLINKS
#define _PC_2_SYMLINKS _PC_2_SYMLINKS
};Kinda silly, the sole purpose of these macros are just to meet the letter of the POSIX standard. I can think of no other purpose they could serve.
In my own code I would have used different symbols for the enumerations, perhaps lowercase. I understand GNU not wanting to pollute the global namespace.
A comment should have been added to this header file explaining what was being done. Better yet, POSIX should be amended to allow for these names to be implemented as enumerations.
I hate having to simultaneously program in more than one language at a time. The less one has to use the C preprocessor the better. Hopefully real modules will be coming to C sometime soon; its been 40 years too late. At least in C++ enumerations are typed. C needs better type safety.
I am making progress working my way through "Advanced Programming in the UNIX Environment" 3rd edition by W. Richard Stevens. The book has a website APUE with source code, but the version I am developing on GitHub has a more robust GNU Make based build.
My APUE project is actually two projects. One is just working through the chapters of the APUE book. The other is more interesting. I am creating an implementation of Stevens' UNIX System Programming API:
Currently I only have access to Linux based systems, but eventually wish to adapt to and test on other Unix like OS's.
In one of my scheller-linux-archive GIT repo's README.md files, I recently waxed poetic on the related topic of C and C++ as "systems languages." I thought this blog might be a better place for this material.
C and C++ are best thought of as different languages. The syntax of C++ is "more or less" a super set of C. Both can be used to write anything from device drivers to GUI software, but C has some natural advantages over C++ as a "low level language" for Linux.
C and its predecessor B, a simplified BCLP, were implemented using the DEC PDP-7 and PDP-11 assembly languages. The syntax mapped well upon the assembly languages of the day. C becoming popular, kept future assembly languages compatible to it. Also, C syntax was designed for easy parsing by the compiler. Hence leading to the syntax which arose.
Also, C is the standard defacto ABI for Linux/POSIX/UNIX. Before UNIX, the ABI (Application Binary Interface) used to call into an operating system was the hardware's assembly language. To port an operating system to another hardware architecture meant basically rewriting it from the ground up. With C, once you remapped it onto the new assembly language, much of what was previously developed could be reused.
Thus the reason C is so natural as a systems language for Unix, is that, except for the isolated uses of assembly code, Unix kernels and device drivers are written in C.
Different implementations of C++ are usually binary incompatible. By using 'extern "C" { ... }' directives, or foreign function interfaces in other languages, the C ABI becomes the lingua franca that glues code together. This allows user code to easily communicate with the kernel, which is written in C. Also, the kernel can easily communicate with device drivers, also written in C.
As system languages, C & C++ rely heavily on OS resources to do their work. With the right compiler options, C can produce freestanding software that can run on the "bare metal," i.e. embedded software. Without ugly hacks, this can't be done for C++, Rust, Haskell, and other general purpose languages. When used idiomatically, these languages have abstractions which require OS infrastructure to implement.
Standards like POSIX and X/Open are very mature and make porting source code across architectures and OS's not only possible, but cost effective. These standards also serve to make C, and to a lesser extent C++, very hard to change.
With 50 years hindsight, could a better low level language be developed? Most certainly. Will a better, safer, language ever come along and replace C? Probably not in our lifetimes. C is "good enough" and the price to replace it "too high."
I have always admired W. Richard Steven's books on Unix System programming. Back in the early to mid 1990's, I thought someday I would work my way through them. Well, I have finally gotten around to it, in 2018.
Wanting to see what the C++ community was up to, I read Bjarne Stroustrup's "A Tour of C++" Second Edition. I thought that perhaps more recent versions of C++ would make for a better, safer systems language than is ANSI-C.
Before starting such an endeavor, I thought I'd best to learn what it is I am trying to replace. Thanks to the maturity and stability of the POSIX and X/Open standards, Steven's books are as relevant today as they were back in the 1990's.
I having trouble in chapter 9, Parser Combinators in Functional Programming in Scala. The concept of parsers is not the problem. It is not having a partial working implementation of the library I am designing to be most frustrating. My experience has been to get something real simple working, even if it just a "Hello World" boilerplate program, and rapid prototype functionality into it. I am also good at taking a "Big Ball of Mud" production system and, like a bomb disposal expert, carefully refactor it to something actually maintainable as well as aesthetically beautiful. The concept of developing laws for a software design before it is even implemented, and then letting these laws guide the implementation, is something I will need to get much better at doing.
I noticed that both pandoc and GitHub render markdown documents with HTML errors. Consider my GitHub repo's README.md file. When I validate the HTML via the W3C Markup Validation Service, I found 41 errors in the HTML rendered by pandoc and 20 errors in the HTML generated by GitHub. If you run Firefox from the command line, both pandoc and GitHub renderings spew forth JavaScript errors. Not just for my markdown, it seems to be universal for all GitHub rendered markdown.
Finding errors in the big-ball-of-mud that HTML has become is not really that surprising. What I find utterly jaw dropping is the lack of information and/or interest on the Web regarding the existence of these types of errors!
There's seems to be a big hole in my Scala toolbox, Implicits. I like to make everything explicit. I like code that you can reverse engineer easily. I don't like hunting all over a code base to figure out the context in which a piece of code is executing. For that reason, I have tended not to use Scala implicit parameters and conversions.
After viewing Martin Odersky's keynote talk at Scala Days Chicago 2017, I realize that he has many of the same concerns. I need to try to understand implicit parameters/conversions because that is an important direction the language is taking. One good argument he makes is that the Reader Monad is "too powerful" for just the purpose of defining a context. Implicit techniques are not only much simpler, they come with a substantially less computational price. Supplying context should not require sequencing.
Currently, I am somewhere between steps 6 and 7. I might go back and try Haskell again to help me tackle step 8.
I don't come from a Java OOP background. Python run-time OOP allowed me to finally understand C++ style compile-time OOP. Professionally I have been able to apply these OOP skills to write very OOP MATLAB GUI programs, but my experience has been primarily in imperative non-OOP scientific applications programming for the Department of Defense and Bell Laboratories. Pick up a lot of scripting tools while a system admin in the late 1990's and early 2000's.
I am a Linux based developer having learned System V Unix while at Bell Laboratories in the late 80's and early 90's. I gave up on Windows based development after reverse engineering enough of Microsoft Visual C++ 4.0 Foundation Class Libraries to be disgusted by them.
For some reason one day, I decided to teach myself Lisp. This is something I totally failed at while a physics undergraduate in the early 1980's. I wished to see if my increased level of programming maturity would allow me to learn it. This led be to Racket (PLT Scheme) and eventually playing with Haskell. I have struggled with Haskell and I am not yet beyond a beginner level. Despite a master's degree in mathematics, I found understanding its Category Theory aspects difficult. I tried using the book Real World Haskell by Bryan O'Sullivan, Don Stewart, and John Goerzen but was not ready for it. Learn You a Haskell for Great Good! by Miran Lipovaca was much more helpful to me.
After reading some of the Functional Programming academic papers, I decided I needed a good FP tutorial. For the past year or so, I have been working my way through the book Functional Programming in Scala by Paul Chiusano and Runar Bjarnason. This led me to the Scala Programming Language. You can follow my progress working through this book here.
At this point, I am best described as a functional programming enthusiast and hobbyist.