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 >.
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.
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.
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:
Input:
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:
Span:
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.
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:
readline.bind(key,cmd);
and unbinding is done with:
readline.unbind(key);
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:
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
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:
[Test]
public void Can_chain_somes() {
var r = Api.DoSomething()
.Select(Api.Passthrough)
.Select(Api.Passthrough)
.GetOrElse("bar");
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.
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.
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 Scalafor comprehension above, we just need to implement 3 methods.
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.
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
)
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.
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.
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.
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.
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.
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) {
Console.WriteLine(title.Value);
}
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)
.SelectMany(GetWebRequest)
.SelectMany(GetXmlBody)
.SelectMany(GetTitleTag);
Console.WriteLine(title.GetOrElse("no title found"));
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.
Everytime I click my way through a hierarchy tree, I long for a simple BASH shell with TAB completion. It's such a simple thing, but TAB completion (usually implemented via the trusty Readline library) still ranks as one of the most productive tools in my book. So as I was once again trying to navigate to some page in a MindTouch site, I thought that all I really want is to treat this documentation hierarchy like a file system and mount it with a bash shell. Shortly after that I'd implemented a command line interface using our API and Miguel DeIcaza's C# Readline inspired library, GetLine. But I couldn't stop there, I wanted it built into the site itself as a Quake-style, dropdown console. I figured that this should be something that already exists in the javascript ecosystem, but alas, I only found a number of demos/implementations tightly integrated into whatever domain they were trying to create a shell for. The most inspired of them was the XKCD shell, but it also was domain specific. Worst of all, key-trapping and line editing was minimal and none of them even trapped TAB properly, leaving me with little interest in using any of them as a base for my endeavours.
Thus the challenge was set: I wanted a CLI w/ full Readline support in the browser for every web project I work on. That means TAB completion, emacs-style line editing, killring and history with reverse search. Go! Of course, some changes from a straight port of Readline had to be made: Commands needed to work using callbacks rather than synchronous. History needed to go into LocalStorage so it would survive page reloads, Killring wouldn't co-operate with the clipboard. But other than that it was all workable, including a simple UI layer to deal with prompts, etc., to create a BASH-like shell.
The result of this work is the Javascript Online SHell, a collection of building blocks for adding a command line interface to any site: Readline.js handles all the key-trapping to implement full Readline line editing. History.js is a simple command history backed by localstorage. Killring.js implements the cut/paste history mechanism popular in old skool, pre-clipboard unix applications. Shell.js provides the UI layer to quickly create a console in the browser and, finally, Pathhandler.js implements cd, pwd, ls and filepath TAB completion with simple hooks to adapt it to any hierarchy. The site for josh.js provides detailed documentation and tutorials from the hello world scenario to browsing github repos as if they were local git file systems.
For the fun of it, I've added a simple REST endpoint to this blog to get basic information for all published articles. Since I already publish articles using a YYYY/MM/Title naming convention, I turned the article list into a hierarchy along those path delimiters, so it can be navigated like a file system like this:
In addition I added a command, posts [n], to created paged lists of articles and a command, go, to navigate to any of these articles. Since the information required (e.g. id, title, path) is small enough to load quickly in its entirety, I decided to forego the more representative use of Josh.js with a REST callback for each command/completion and instead load it all at initialization and operate against the memory model. I wrote a 35 line node.js REST API to serve up the post json which is called on the first console activation, takes the list of articles and builds an in-memory tree of the YYYY/MM/Title hierarchy:
Implementing unix filesystem style navigation in the console is as simple as adding Josh.PathHandler to the shell and providing implementations of getNode(path, callback) and getChildNodes(node, pathParts, callback). These two functions are responsible for finding nodes by path and finding a node's children, respectively, which is the plumbing required for pwd, ls, cd and TAB completion of paths. The posts command is even simpler: Since it only takes an optional numeric argument for the page to show, there is no completion handler to implement. The execution handler simply does a slice on the array of articles to get the desired "page", uses underscore.map to first transform the data into the viewmodel and then renders it with underscore.template:
The final addition is the go command which acts either on the current "directory" or the provided path. Since any argument is a path, go gets to re-use Josh.PathHandler.pathCompletionHandler which ls and cd use.
Once called, the appropriate node is resolved and the path of the node used to change the window location. The console uses localStorage to track the open state of the console, so that navigating to a new page re-opens the console as appropriate while the page location is used to initialize the current directory in the console. The help, clear and history commands come for free.
Oh, and then there is wat? as a go shortcut to get to this article :)
Go ahead, play with it, let me know whether there are assumptions built in that prevent your favorite console scenario. For reference and those interested in the nitty gritty, the full, annotated source for the console I use on this blog can be found here. Most of the lift is done by Josh.js, and its fairly simple to get your own console going. Check out the documentation here along with the tutorials that walk through some usage scenarios.
Josh.js is certainly ready for use and deployment, but until it's been put through its paces a bit more to figure out what's working and what's not, the API is still open for significant changes. I'm tracking things I am planning to do or working on via GitHub Issues. Please submit any problems there as well, or even better, provide a pull request. I hope my love for CLIs on websites will inspire others to do the same for their applications. I certainly will endeavour to include a shell in every web project I undertake for the forseeable future.
Over years, I've developed a dislike for frameworks, especially ORMs and web stacks such as Rails. But aside from complaining about "magic" and a vague icky feeling, I could never eloquently explain why. Meanwhile, all my spare time web projects have been done with Express and, man, I haven't had more fun in years, again not being able to eloquently explain why.
So when it came time to pick a stack for a scala web app, I was staring at a sea of options. Play seemed to be the obvious choice, being part of the TypeSafe stack, but looking at their documentation I got that icky feeling again. I searched for some vs. posts to hear what people like/dislike about the many options available. And that's where I came across a paragraph that was the best explanation of why I stay clear of frameworks when i can:
"[...] frameworks are fine, but it is incumbent upon you tohave an intimate understanding of how such frameworks abstract over thisinfrastructure, as well as the infrastructure itself. Some will disagreewith that, arguing that the very reason you want these abstractions isso you don't need this understanding. If you buy that then I wish youluck; you'll surely need it should you decide to develop a non-trivialapplication."
-- [Scalatra vs Unfiltered vs Lift vs Play](http://www.scala-lang.org/node/10817#comment-46844)
It all comes down to the fallacy that an abstraction alleviates the need to understand what it abstracts. Sure, for the scenarios where what you are trying to do maps 100% to the target scenarios of the framework and you have no bugs, frameworks can really cut down on that boiler plate. This is why scaffolding examples of most frameworks are so magically concise. They excercise exactly what the framework was built to be best at. But the moment you step out of their wheelhouse or need to troubleshoot something (even if the bug is in your own code), you'll have to not only know how the abstracted system should work but also how the abstraction works, giving you two domains to master rather than just one.
I used to be huge proponent of ORMs. I even wrote two and a half of them. My original love for them stemmed from believing that I could curb bad SQL getting into production by providing an abstraction. I was violently disabused of that notion and have since come to accept that badly written code isn't a structural, but rather a cultural problem of developers either not understanding what is bad or not caring because they are insulated from the pain their code causes.
But I was still convinced that ORMs were an inherent win. I went on to evangelize NHibernate, Linq-2-SQL, LLBLGen Pro.Entity Framework never got a chance, since I was already burned out by the time it stopped sucking.
Over time it became obvious ORMs were not saving me time or preventing mistakes. Quite the opposite, setup was increasingly more complex, as you had to design schemas AND write mapping code to get them to work right. Usage went the same way: I knew what SQL I wanted to execute and now had a new dance to tweaking the ORM queries to do what I wanted. I was an abstraction whisperer. And that's not even the hours wasted with bugs. Debugging through the veil of abstraction usually ended up showing not an error in business logic or data structure but simply in usage or configuration of the ORM.
One of the attractions of frameworks is that they drastically cut down on repetitive boilerplate code. I admit that using component libraries, you will likely do more manual wiring in your initial setup than with a framework, but this is generally a one-time setup per project. In my experience that one time cost of explicit wire-up pales in comparison to the benefits of having explicit configuration that you can trace down when problems do occur. So my stance is that wire-up isn't repeated boilerplate but rather explicit specificatgion and so does not violate the spirit of DRY.
For the most part I favor components that simplify working in an infrastructure's domain language over frameworks that try to hide that domain and expose it as a different one. Sooner or later you will have to understand what's happening under the hood and when that time comes, having a collection helpers for working with the native paradigm beats trying to diagnose the interactions of two (or more) domains.
