Skip to content


Rust inspired Async Lock for C

Venturing back into C# for the first time in a long time. I'm only 5 minutes in and already felt compelled to create a new utility class.

Essentially I'm adding an ASP.NET Web API to a daemon process, which requires that the REST API can get exclusive access to some daemon in-memory state. Since I'm building everything around async/await, I went looking for the async equivalent of the traditional lock, only to not find one. From what I could gather, the recommendation is to build one around SemaphoreSlim. After using that explicitly, I was really uncomfortable with having to make sure that I a) released the semaphore and b) did it in a try/finally.

Mastodon Integration

Well, damn it. Here I am procrastinating on my archviz project with a server side project. I am an infrastructure engineer at heart, so anything server related will always pull at me harder than any other project. So right after writing the Future Work section in my last post, I started looking more closely at Daniel's approach to using mastodon for comments. The part that scratched my server-side geek itch was his chicken-egg problem forcing the workflow:

  1. create post
  2. create toot
  3. update post with toot id

I just want to publish my post, have a matching toot automatically be generated and have the original post be able to discover the corresponding toot_id. I want to keep my blog static and don't really want to add this into the build pipeline, so what I need is a web service that will lazy publish the toot and return the toot_id for a given URL.

Blogging with mkdocs was converted from static html and a wordpress site behind nginx on an EC2 instance to a static site generated by mkdocs hosted on S3.

The motivation

For the last ~10 years, I hosted everything on a single EC2 instance behind an ElasticIP. A couple of wordpress sites, some static sites, a couple of node apps, all through nginx. Deploy was git checkouts and some shell scripting. After having my server taken over once because of a wordpress vulnerability, I now ran all my wordpress with read-only files, so that felt decent. Just had to make them read/write for version and plugin updates. Mind you all this is very low traffic hobby sites.

But I really wanted to get to immutable deploys. Run these sites as separate docker containers I could more easily test locally and deploy was a replace. I converted one WP site to docker and figured out how to run it with ECS. Then last month I set out to decommission the EC2 and convert everything left.

My WP deploys were using the default WP container as a base, but was structured with the blog as a sub-directory and a bunch of static site elsewhere. I considered reconfiguring the container to serve the existing hierarchy through its nginx, but in the 10 years of not posting, my tastes for authoring had moved distinctly from WYSIWYG to markdown and if I was going to get back to blogging, I wanted to go static. I briefly considered jekyll, but had been using MkDocs at work and really liked it, plus I am far more fluent in python than ruby. Some brief googling later, I found Material for MkDocs which comes out of the box with blogging support and with LoneKorean's WordPress Export to Markdown I was well on my way.

Deploying many sites in ECS using one ALB

My current go-to deployment strategy is AWS Elastic Container Service (ECS) using Fargate behind an Application Load Balancer (ALB). Each site is its own stateless docker container persisting dynamic data in RDS and/or S3. When I make a change, I build the new container, push it to ECR, create a new task revision and ECS deploys the site for me.

I've now set this up a couple of times and each time I struggle to recollect all the steps along the way, so it's high time I write it down so that I can look it up next time. And now that I understand this a bit better, I was also able to consolidate my infrastructure, since my original approach wasn't necessarily the most cost-efficient setup.

Aside from remembering/reverse engineering all the pieces needed, the part I always got stuck on was the apparent catch-22 of a load balancer wanting a target group, a target group wanting an IP, while the ECS Service wants to set up a load balancer before providing said IP.

ECS RunTask needs public IP to access env file

Learning how to use ECS tasks to run some cron jobs has been an opaque journey to say the least.

I knew my TaskDefinition was fine, because my server was running, but I wanted to use that same definition with a different container command and schedule its execution for housekeeping tasks.

I started with creating an EventBridge schedule, which seemed straight forward enough. But as soon as I created it I was puzzled that there didn't seem to be a way to trigger it for testing nor was there any kind of information on whether or not the last invocation had happened and succeeded.

Closing out a decade of silence

About a decade ago I stopped posting on this blog. It wasn't a conscious decision but between twitter and stackoverflow, my attention had just shifted. Twitter provided an easy way to post tech comments, seductive in its immediacy and the enforced brevity. So I, as many other tech bloggers, led ourselves to believe that the interactions on twitter were a sufficient replacement of blog posts. As a way to acquiesce those niggling objections to that former delusion, stackoverflow served the need for asking and answering questions in a more substantive way.

Over time, the gamification appeal of stackoverflow wore off after a while, and I became mostly a consumer with the occasional issue that I got stuck on. It's still my ends up my primary source of troubleshooting, but mostly because google drops me off there. These days getting really stuck usually has me tracking down a relevant Discord community instead.

And twitter I left at the start of the pandemic, primarily because they kept messing with the ordered timeline and even when nothing was injected, it had really turned into primarily doom scrolling.

But last year I decided to give mastodon a try and have found it to be very much like early twitter. Informative, casual, non-sensational. Just a nice place to get some tech news, trends and conversation from.

However, as I play around with whatever evening project I've got myself into now, I am reminded of why I started this blog in the first place. Namely, capturing my troubleshooting and discovery so that next time I ran into the same or similar I would recall having written it down, or at least have google lead me back here again. So that's what I hope to accomplish here over the next year and beyond.

As part of the move, I've dropped wordpress in favor of static generation using material for mkdocs. I'll talk about how I ended up with that in a future post, assuming this New Year's resolution holds.

Josh.js 0.3 roadmap: rethinking I/O

My goal has been to expand Josh.Shell to be a better emulation of a console window. It seems simple enough: execute a command, print the output in a div. But print something longer than your shell window and you immediately see where the real thing has a couple more tricks up its sleeve:

cat foo.txt

If foo.txt is too large, you could use less:

less foo.txt

And now you pagination, plus a couple of other neat features.

Ok, let's implement that in Josh.Shell. Let's start with the less command. It could be hardcoded to know the div the content is displayed in, do some measuring and start paginating output. Aside from being ugly, you immediately run into another problem: In order to determine after what line you pause paginated output, how do you determine where one line begins and ends. Which only further exposes the problem of output in a div, sure the browser will wrap the text for you, but by delegating layout to the browser, you've lost all knowledge about the shape of the content.

To start taking back control over output we need the equivalent of TermCap, i.e. an abstraction of our terminal div that at least gives height and width in terms of characters. Next, we need change output to be just a string of characters with line feeds. This does lead us down a rabbit hole where we'll eventually need to figure out how to handle ANSI terminal colors, and other character markup, but for the time being, let's assume just plain-text ASCII.

Now we could implement a basic form of less. But chances are the first time you want to use less is a scenario such as this:

ls -lah /foo | less

i.e. we don't have a file that we want to display, we have the output of an existing command that we want to pipe into less. And this is where we run into our next problem: Josh.Readline has only one processor for the entire command line, i.e. the above will always be handled by the command handler attached to ls. And while we could make that command handler smart enough to understand | we'd have to do it for every command and then do the same for < and >.

Intercepting command and completion handling

No, what we need is a way to intercept readline processing before it goes to the command handler for either execution or completion, so that we can recognize command separators and handle each appropriately. It also means that the command no longer should return their output to the shell, but that the pre-processor executing multiple commands receives it and provide it as input for the next command.

The pre-processor work will go in Josh.Readline and can be discussed via Issue 16, while the pipping behavior will be implemented on top of the pre-processor work and discussion of it should happen on Issue 18.

Standard I/O

We certainly could just chain the callbacks, but we still have no way of providing input, and we'd end up being completely synchronous, i.e. one command would have to run to completion before its output could be piped to the next.

Rather than inventing some crazy custom callback scheme, what we are really looking at is just standard I/O. Rather than getting a callback to provide output, the command invocation should receive an environment, which provides input, output and error streams along with TermCap and a completion code callback. The input stream (stdin) can be only be read from while output (stdout) and error (stderr) can only be written to. As soon as the out streams are written to, the next receiver (command or shell) will be invoked with the output as its input. Stderr by default will invoke the shell regardless of what other commands are still in the pipeline.

All these changes are planned for 0.3, a minor revision bump, because it will likely introduce some breaking changes. I don't want to stop supporting the ability to just return HTML, so the stdio model might be something to opt in, leaving the current model in place. If you have feedback on the stdio and TermCap work, please add to the discussion in Issue 14.

One other pre-requisite for these changes is Issue 3. In a regular console, text followed by a backlash and a space and more text or quoting a string treats that sequence of characters as a single argument. Josh.Readline does not do this, causing some problems with completing and executing arguments with spaces in them and that will be even more of a problem once we support piping, so that needs to be fixed first.

Using Josh for form data

While Josh.js was built primarily for creating bash-style shells in the browser, the same mechanisms would be nice to use for form input. Yes, it does break the expected user behavior, but if you are creating a UI for unix people this might just be the geeky edge to push usability over the top. Problem was, Josh.js originally bound itself to the document root and you had to activate/deactivate it to take over key interception. While you could manually trigger this, it was less than ideal for having multiple instances of Josh.Readline on one page each attached to an input field. With todays release of Josh.js (marked minor, since it's backwards compatible and incompatible breaking changes are on the horizon), readline can bind to an element and can even do so after the fact. In addition, key bindings of josh can be disabled or remapped to better match your use case. Finally, because taking over the UX of form input is unfortunately not quite as simple as just binding readline to an input element, Josh.js now includes Josh.Input to simplify the binding.


There are two ways to create a josh form element. Either you attach Josh.Input to an <input> field or a <span>. The former preserves the standard look and feel of an input field, but has to play some tricks to properly handle cursor positioning. The latter can be styled any way you like and uses the underscore cursor behavior also used in Josh.Shell.

The former uses html like this:

<input id="input1" type="text" />

and binds it to Josh.Input with:

var cmd1 = new Josh.Input({id: "input1"});

to produce:


And the latter will generally use a span like this:

<span id="input2"></span>

Adorned with whatever css you like to create the input look and feel and then is bound to Josh.Input the same way with:

var cmd2 = new Josh.Input({id: "input2"});

creating an input like this:


Note that the two inputs share history and killring, which in addition to line editing behavior makes them so much more powerful than just plain old input boxes. Also note that the only reason we capture the object created by new Josh.Input is so that we could access its members, such as the Josh.Readline instance bound to the element. As I said, I wouldn't recommend using this in a regular form, since form input behavior on the web is rather well established, but a custom app that evokes a unix input mentality could certainly benefit from it.

Changes to Josh.js for Input

Adding Josh.Input revv'ed Josh.js to 0.2.9 (i.e. no breaking changes), which allows Josh.Readline and by extension Josh.Shell to be bound to an element. When Josh.Shell is bound to an element, it will now activate/deactivate on focus (for this it will add a tabindex to the shell element if one isn't already there). Binding to an input or input mimicking span did illustrate that certain key bindings just don't make sense. Rather than hardcode a couple of binding exceptions for input, 0.2.9 also introduces the ability to bind and unbind the existing Readline commands to any key (modifiers work, but only a single modifier is recognized per key combo right now). This could be used to change the emacs-style bindings, but really is primarily intended to unbind commands that don't make sense. The bindable commands are:

  • complete - invoke command completion
  • done - invoke the command handler
  • noop - capture the key but don't do anything (bound to caps-lock, pause and insert)
  • history_top - go to and display the history top
  • history_end - go to and display the history end
  • history_next - go to and display the next item in the history
  • history_previous - go to and display the previous item in the history
  • end - cursor to end of line
  • home - cursor to beginning of line
  • left - cursor left
  • right - cursor right
  • cancel - interrupt the current command input
  • delete - delete character under cursor
  • backspace - delete character to the left of cursor
  • clear - clear the shell screen
  • search - start reverse search mode
  • wordback - cursor to previous word
  • wordforward - cursor to next word
  • kill_eof - kill text to end of line
  • kill_wordback - kill the previous word
  • kill_wordforward - kill the next word
  • yank - yank the current head of the killring to the cursor position
  • yank_rotate - if following yank, replace previously yanked text with next text in killring

Binding commands to keys is done with:


and unbinding is done with:


where key is:

 keyCode:  120
 // or
 char: 'x',
 // plus one of these:
 crtlKey: true,
 metaKey: true

Josh also provides a simply lookup for special key keycodes:

Josh.Keys = {
    Special: {
      Backspace: 8,
      Tab: 9,
      Enter: 13,
      Pause: 19,
      CapsLock: 20,
      Escape: 27,
      Space: 32,
      PageUp: 33,
      PageDown: 34,
      End: 35,
      Home: 36,
      Left: 37,
      Up: 38,
      Right: 39,
      Down: 40,
      Insert: 45,
      Delete: 46

Josh.Input automatically unbinds Tab and Ctrl-R.

All these changes do not affect existing usages of Josh.js, however 0.3 is coming up soon and it may have some breaking changes (will try not to, but can't determine yet if that's possible), but I'll talk about those plans in a future post

List comprehension over non-enumerables in C

As I was trying to finish up my C# implementation of Try[A] for Scando, I ran into some LINQ issues. Or at least I thought I did. Using the LINQ syntax kept failing to call my extension methods and instead fell back to the IEnumerable<T> ones. I thought to myself how unfortunate it was that the LINQ syntax was hard wired to IEnumerable<T>, otherwise it would be perfect to emulate Scala's for comprehensions.

Fortunately I had just watched Runar Bjarnason's excellent "Lambda: The Ultimate Dependency Injection Framework" and recalled usage of a container type similar to how Option<T> and Try<T> are used. I also recalled that projecting such a type with a function that also returned a new instance of that container type via map (roughly equivalent to Select) created nested containers, yet I had a test for Option<T> that looked like this:

public void Can_chain_somes() {
 var r = Api.DoSomething()
 Assert.AreEqual("foo", r);

This should have returned an Option<Option<Option<string>>> but instead just returned Option<string>. Obviously my implementation of Select was wrong, which would explain why LINQ syntax didn't use it. And that probably meant that my assumptions about IEnumerable were wrong as well. Runar solved the nested container problem by implementing flatMap which also enabled for comprehensions in Scala. For me that meant that I was also missing SelectMany to make LINQ work properly.

Scala For Comprehension

Before I get into LINQ, I should cover why wrapping a value in a single or no value collection is a useful thing in the first place. Let's look at an example of functions returning Option[A]:

for {
  user <- UserRepository.findById(1) if user.isActive
  profile <- ProfileRepository.getProfileByUser(user)
  url <- profile.url
} yield url

This will get a single Option[User], check that the user is active, fetch the user's profile and then return the profile url. What makes this code special is that we don't have to check that the previous call returned a value. If UserRepository returned None, then the if guard never gets executed (since it gets executed for all values in the "Collection") and likewise ProfileRepository is never called since no user was selected.

With for comprehensions and the Option container we can chain calls and have it handle the short circuiting along the way so we will always receive an Option of the yielded type without checking return values along the way.

LINQ and IEnumerable

Ok, but that's subverting a list processing construct for its behavior on empty collections and Scala's excellent type inference deals with types changing throughout the comprehensions. Can LINQ pull that off?

Turns out, yep, it can. The LINQ syntactic sugar doesn't have any ties to operating on IEnumerable or any type at all. To mimic the Scala for comprehension above, we just need to implement 3 methods.

Select: Transforming C to C

For illustration purposes, I've create a container Type C<T> with an accessor Value. It does not implement IEnumerable<T> as Option<T> originally did (which I've since removed since the only reason had been that I thought I needed it for LINQ).

Let's start with the simplest comprehension style LINQ query:

from x in new C<int>(1) select x

At this point the compiler complains with Could not find an implementation of the query pattern for source type 'Sandbox.C'. 'Select' not found. Simple enough, let's add Select to C<T>:

public C<TResult> Select<TResult>(Func<T, TResult> selector) {
  return new C<TResult>(selector(_value));

Note: LINQ does not care whether its methods are provided as methods on the object or extensions. For this example I'm just attaching it straight on C<T> instead of using an Extension Method, so I don't need the this C<T> source argument.

Now that query works and we are getting back a C<T>, not an IEnumerable<T>. That means that we can call .Value directly on the result of the query.

SelectMany: Flatting C>

Next up is passing the result from the first as input to the next call:

from x in new C<int>(1)
from y in new C<int>(x)
select y

Again, it won't compile. Now it complains about SelectMany. Since there are multiple overloads of SelectMany, let's start with the simplest, i.e. a selector to transform T into C<TResult>:

public C<TResult> SelectMany<TResult>(Func<T, C<TResult>> selector ) {
   return selector(Value);

Except that just leads to a new compiler error: No overload for method 'SelectMany' takes 2 arguments. To get a closer look at what the compiler wants to do, we can just rewrite the query using int[] instead of C<T>:

from x in new[] {1}
from y in new[] {x}
select x;

Then, using IlSpy and turning Query decompilation off, we can see what .NET actually translates that LINQ to:

new int[] {1}.SelectMany(x => new int[] {x}, (x, y) => y);

That's interesting. Instead of

SelectMany<TSource, TResult>(
  this IEnumerable<TSource> source,
  Func<TSource,IEnumerable<TResult>> selector

It's using

SelectMany<TSource, TCollection, TResult>(
  this IEnumerable<TSource> source,
  Func<TSource,IEnumerable<TCollection>> collectionSelector,
  Func<TSource,TCollection,TResult> resultSelector

but passes in a resultCollector that merely ignores the first argument and always returns the second, making it functionally equivalent of the first signature. Here's what that looks like as a Method on C<T>:

public C<TResult> SelectMany<TCollection, TResult>(
    Func<T, C<TCollection>> collectionSelector, 
    Func<T, TCollection, TResult> resultCollector
) {
  var c = collectionSelector(Value);
  return new C<TResult>(resultCollector(Value, c.Value));

And now the LINQ query with multiple from clauses works.

Where: What does a short circuit of C look like?

Finally, we want to add the guard clause, which in LINQ is simply Where:

from x in new C<T>(1) where x == 1
select x

with Where having the following signature

C<T> Where(Func<T, bool> predicate) { ... }

Implementing the guard poses a problem, though. Where will always return a C<T>, but what does a C<T> that failed the predicate check look like? Which also raises the question, what value does the from retrieve when encountering such a C<T>? If the point was that comprehension lets us short circuit the execution chain, then we need a way to indicate that C<T> doesn't have a value.

For this implementation, I've simply added an IsEmpty flag and use the no argument constructor to construct an empty version. While that takes care of implementing Where, it does point to an oversight in Select and SelectMany. Both need to be aware of IsEmpty and return an empty C<T> rather than executing the selectors in order to provide short-circuiting behavior. The full implementation of C<T> now looks like this:

public class C<T> {

  public C() { IsEmpty = true; }
  public C(T value) { Value = value; }

  public T Value { get; private set; }
  public bool IsEmpty { get; private set; }

  public C<T> Where(Func<T, bool> predicate) {
    if(IsEmpty) {
      return this;
    return predicate(Value) ? this : new C<T>();

  public C<TResult> Select<TResult>(Func<T, TResult> selector) {
    return IsEmpty ? new C<TResult>() : new C<TResult>(selector(Value));

  public C<TResult> SelectMany<TCollection, TResult>(
    Func<T, C<TCollection>> collectionSelector,
    Func<T, TCollection, TResult> resultCollector
  ) {
    if(IsEmpty) {
      return new C<TResult>();
    var c = collectionSelector(Value);
    return c.IsEmpty ? new C<TResult>() : new C<TResult>(resultCollector(Value, c.Value));

That still does not answer how from x in a works since that clearly pulls a value from the container. You would expect an enumerator to be required. The key to understanding how this construct works is that the transformation of the call becomes a Select or SelectMany, which has no concept of enumeration. Both have a selector that takes T and converts it into the containerized T, C<T>. Since traditionally the container is IEnumerable, the natural association for x in a is an enumeration, but it really is just an instance of the container with no assumption about what it contains.

Applying LINQ comprehensions

Now that we know how to create a container type, we can create return values for our methods that follow those principles and rewrite the Scala example in C#:

from user in UserRepository.FindById(1) where user.isActive
from profile in ProfileRepository.GetProfileByUser(user)
from url in profile.url
select url

Essentially, C<T> is just a naive re-implementation of Option<T>. The reason I created it instead of just walking through the existing type was to illustrate this container type pattern. It's the pattern Option<T> uses, as does Try<T> and it is used it to implement the Reader Monad for functional dependency injection. The essence of this pattern is that by wrapping T in a container we can attach an environment to it to carry along additional data. In the case of Option, it was the ability to determine the presence or lack of a value for T. In case of Try it is presence of an error occurring while trying to produce T. and for functional Dependency Injection it was the ability to carry along dependencies that a call at the end of a long chain needed without the intermediate calls having to be aware of them. By using the container, functions that care about the environment can take it as input or return it, while functions that don't can be lifted to fit the required shape and take part in the composition without ever needing to be aware of the environment being passed along.

Having used for comprehensions in Scala and seeing how it can remove a lot of imperative boiler plate that does nothing to aid in the comprehension of the workflow, it is nice to see that it requires just three methods to allow LINQ to be used for a similarly expressive syntax for composing method chains.

Scala in the key of C#: Option

Update: Since I first released Option, I've realized that it implementing IEnumerable was unneccesary to use LINQ syntax and actually made it less useful. I've updated the post to reflect these changes to Option.

Currently reading Daniel Westheide's excellent "Neophyte's guide Scala" series and it's inspired me to port some concepts from Scala to C#. This is less about trying to replace Scala -- it has too many compelling aspects that cannot be mimicked -- and more about exploring concepts I come across in Scala in the realm i'm best versed in, and, hopefully, along the way, create some useful C# utilities. First up, the Option<T> type.

Get thee behind me, null

Reading The Option Type the simplicity and elegance struck me. My Option<T> is inspired by Scala's Option[A], which in turn has its origin in Haskell's Option. On the surface it's a pretty simple container for a value that may or may not exist.

var some = Option<string>.Some("foo");

// manually checking for defined
Console.WriteLine(some.IsDefined ? some.Value : "not defined");
// => "foo"

// or use the built in helper
Console.WriteLeing(some.GetOrElse("not defined"));
// => "foo"

// None is a singleton
var none = Option<string>.None;

Console.WriteLine(none.GetOrElse("not defined"));
// => "not defined"

Nobody likes NullReferenceException, so Option makes reference types behave more like nullable value types. But with the null coalescing operator ??, trying to check for null and substituting an alternative value is already very simple in .NET, so why bother with an Option port? After all, the most compelling usage of Option in scala, pattern matching, just cannot be reproduced in .NET, so there goes a large part of the motivation. But once I learned that Option[A] behaves like an Iterable and therefore could use all the common collection methods, I was intrigued.

The Power of LINQ compels you

You see, an Option is can be considered a collection of zero or one values. By implementing the Select, SelectMany and Where Extension Methods for Option we can use LINQ to chain calls together. This makes Option much more composable than manual null checks.

var title = (from url in ParseUrl(urlStr)
             from response in GetWebRequest(url)
             from doc in GetXmlBody(response)
             from title in GetTitleTag(doc)
             select title);
if(title.IsDefined) {

Each method returns an Option, for which the compiler insert the appropriate extension method for the specific LINQ syntax. An undefined Option behaves just like and empty IEnumerable, i.e. the selector callback is skipped and the query is short circuited. Using the from x in a syntax uses SelectMany (if there is more than one from clause) and could just as easily have been written by manually chaining the calls:

var title = ParseUrl(urlStr)
Console.WriteLine(title.GetOrElse("no title found"));

What Else can Option do for Me?

Option implements equality comparison based on the contained type, so two Options of the same type containing the same value will be equal, according to that type's rules. Along with that Option<T>.None equals null and all None regardless of type have the same hashcode, i.e. 0.

Finally, in addition to GetOrElse, there is also OrElse, which provides a way to substitute a different Option, allowing the chaining of many calls to get the first one that returns a value.


Option is available on github under the MIT license in the Scando repository. This repository is where I plan to put all code inspired by Scala. There's already an implementation of the Try type in there as well, which I will be writing about shortly.