Convert CloudFormation template (yaml) to cdk python code - aws-cloudformation

I have this template that works as expected. Is there any way to convert it as cdk python code?
https://github.com/shantanuo/cloudformation/blob/master/updated/api-to-sns-cf%20(1).yml

There is nothing wrong with using low-level resources, as it's a useful building block. Yes, there are high level constructs, but like everything else in software, occasionally you have to dig deeper. It's a shame that the attitude like this has continued, because for some of us, that have spent years building out a nice collection of CloudFormation templates, are discouraged from using CDK.
Yes, there are some issues with this, mostly because of some poor architecture decisions and a desire to focus on the new instead of building up layers of functionality, but it's possible and you shouldn't be dissuaded in converting your templates to low-level constructs, and then refactoring into higher-level ones as your use case requires.
That said, I would NOT use any kind of automatic tools to do this conversion. You won't actually understand what's going on, and you'll more than likely have issues that you won't know how to handle. Dig in, convert line-by-line, and then enjoy the results.

You can't convert a CloudFormation template to CDK code. It doesn't really make sense to do it, either. Kind of like asking to convert assembly, or C, to Python.
In Troposphere's case it makes sense, because Troposphere has a 1:1 relationship to CloudFormation. The CDK is supposed to be higher level, much like Python's relation with Assembly or C. The CDK does have CfnResource classes, which do translate directly to CloudFormation, but that's just the necessary underlying layer, it's not how the CDK is supposed to be used. If you want to go that way, you'd be better off with Troposphere.
It might sound like it would make sense to be able to do it during a transition period, but in my opinion it's more trouble than it's worth. Anyway, there's nothing that does it at this time.
Edit: For Typescript, there's cdk-dasm. It's Typescript only and it converts CloudFormation to Cfn resources. Quoting from that page:
Generally, this is not a recommended approach when using the AWS CDK, but some people may find this useful as a means to get started or migrate an existing template.
Using this method means that you will have to use the low-level resources (e.g. s3.CfnBucket instead of s3.Bucket). This means that you lose a substantial portion of the value of the CDK, which abstracts away much of the boilerplate and glue logic required to work with AWS resources.

Yes. The CDK's cloudformation_include module natively imports CloudFormation templates, converting each resource into a L1 construct.
After you "convert" the CloudFormation YAML (or JSON) template to CDK, you can read and update imported resources:
from pathlib import Path
from typing import cast
from constructs import Construct
from aws_cdk import Stack, cloudformation_include as include, aws_apigateway as api
class CfnIncludeStack(Stack):
def __init__(self, scope: Construct, construct_id: str, **kwargs) -> None:
super().__init__(scope, construct_id, **kwargs)
converted = include.CfnInclude(
self,
"Converted",
template_file=str(Path(__file__).with_name("template.yml")),
)
cfn_api = cast(api.CfnRestApi, converted.get_resource("ApiGatewayRestApi"))

Related

How to call Python functions from DML?

I would like to have a DML device with interfaces and register banks as the TOP-level of my device but offload processing to Python. Is there a lightweight method of calling into Python from DML?
This post How can I unit test a specific DML method? addresses calling from Python into DML, but I am interested in the reverse.
I think I can create a bunch of custom interfaces to do this, but I'm interested to know if there's a better way.
Implementing parts of a device in Python can make sense, in particular for code that seldom is invoked (user interaction comes to mind), and when faced with tasks like string manipulation where the shortcomings of a C-like language is particularly painful, or when code sharing with CLI commands is desired.
You can use the SIM_call_python_function API to call out to Python from DML. The function uses the equivalent of eval on the passed string, so you can find a module-local function by __import__:
local attr_value_t a = SIM_make_attr_list(0);
local attr_value_t result = SIM_call_python_function(
"__import__('simics').SIM_version", &a);
log info: "%s", SIM_attr_string(result);
SIM_attr_free(&a);
SIM_attr_free(&result);
This API is admittedly not very pretty. Parts of the standard lib for DML 1.2 is in fact written in Python and uses the internal function VT_call_python_module_function for this task instead. That API is nicer, but we cannot recommend use of VT_ functions outside the core Simics team.
This question is really more about the Simics simulator framework than about DML. Given how Simics works, Python code lives in a separate context. There is no obvious light-weight way. Rather, you need to put the Python code in a separate Python class and a separate runtime object and use a Simics simulator interface to orchestrate the calling.
The Python code would in general not be able to access the state of the object anyway, so it would have to be a strict "compute this and return all computed values". Which is not very convenient for device behavior that is really all about mutating the state of the object.
Even with a bunch of interfaces, there is still the matter of state handling. I guess you need an interface for that as well.

Idiomatic Rust plugin system

I want to outsource some code for a plugin system. Inside my project, I have a trait called Provider which is the code for my plugin system. If you activate the feature "consumer" you can use plugins; if you don't, you are an author of plugins.
I want authors of plugins to get their code into my program by compiling to a shared library. Is a shared library a good design decision? The limitation of the plugins is using Rust anyway.
Does the plugin host have to go the C way for loading the shared library: loading an unmangled function?
I just want authors to use the trait Provider for implementing their plugins and that's it.
After taking a look at sharedlib and libloading, it seems impossible to load plugins in a idiomatic Rust way.
I'd just like to load trait objects into my ProviderLoader:
// lib.rs
pub struct Sample { ... }
pub trait Provider {
fn get_sample(&self) -> Sample;
}
pub struct ProviderLoader {
plugins: Vec<Box<Provider>>
}
When the program is shipped, the file tree would look like:
.
├── fancy_program.exe
└── providers
├── fp_awesomedude.dll
└── fp_niceplugin.dll
Is that possible if plugins are compiled to shared libs? This would also affect the decision of the plugins' crate-type.
Do you have other ideas? Maybe I'm on the wrong path so that shared libs aren't the holy grail.
I first posted this on the Rust forum. A friend advised me to give it a try on Stack Overflow.
UPDATE 3/27/2018:
After using plugins this way for some time, I have to caution that in my experience things do get out of sync, and it can be very frustrating to debug (strange segfaults, weird OS errors). Even in cases where my team independently verified the dependencies were in sync, passing non-primitive structs between the dynamic library binaries tended to fail on OS X for some reason. I'd like to revisit this, find what cases it happens in, and perhaps open an issue with Rust, but I'm going to advise caution with this going forward.
LLDB and valgrind are near-essential to debug these issues.
Intro
I've been investigating things along these lines myself, and I've found there's little official documentation for this, so I decided to play around!
First let me note, as there is little official word on these properties please do not rely on any code here if you're trying to keep planes in the air or nuclear missiles from errantly launching, at least not without doing far more comprehensive testing than I've done. I'm not responsible if the code here deletes your OS and emails an erroneous tearful confession of committing the Zodiac killings to your local police; we're on the fringes of Rust here and things could change from one release or toolchain to another.
I have personally tested this on Rust 1.20 stable in both debug and release configurations on Windows 10 (stable-x86_64-pc-windows-msvc) and Cent OS 7 (stable-x86_64-unknown-linux-gnu).
Approach
The approach I took was a shared common crate both crates listed as a dependency defining common struct and trait definitions. At first, I was also going to test having a struct with the same structure, or trait with the same definitions, defined independently in both libraries, but I opted against it because it's too fragile and you wouldn't want to do it in a real design. That said, if anybody wants to test this, feel free to do a PR on the repository above and I will update this answer.
In addition, the Rust plugin was declared dylib. I'm not sure how compiling as cdylib would interact, since I think it would mean that upon loading the plugin there are two versions of the Rust standard library hanging around (since I believe cdylib statically links the Rust stdlib into the shared object).
Tests
General Notes
The structs I tested were not declared #repr(C). This could provide an extra layer of safety by guaranteeing a layout, but I was most curious about writing "pure" Rust plugins with as little "treating Rust like C" fiddling as possible. We already know you can use Rust via FFI by wrapping things in opaque pointers, manually dropping, and such, so it's not very enlightening to test this.
The function signature I used was pub fn foo(args) -> output with the #[no_mangle] directive, it turns out that rustfmt automatically changes extern "Rust" fn to simply fn. I'm not sure I agree with this in this case since they are most certainly "extern" functions here, but I will choose to abide by rustfmt.
Remember that even though this is Rust, this has elements of unsafety because libloading (or the unstable DynamicLib functionality) will not type check the symbols for you. At first I thought my Vec test was proving you couldn't pass Vecs between host and plugin until I realized on one end I had Vec<i32> and on the other I had Vec<usize>
Interestingly, there were a few times I pointed an optimized test build to an unoptimized plugin and vice versa and it still worked. However, I still can't in good faith recommending building plugins and host applications with different toolchains, and even if you do, I can't promise that for some reason rustc/llvm won't decide to do certain optimizations on one version of a struct and not another. In addition, I'm not sure if this means that passing types through FFI prevents certain optimizations such as Null Pointer Optimizations from occurring.
You're still limited to calling bare functions, no Foo::bar because of the lack of name mangling. In addition, due to the fact that functions with trait bounds are monomorphized, generic functions and structs are also out. The compiler can't know you're going to call foo<i32> so no foo<i32> is going to be generated. Any functions over the plugin boundary must take only concrete types and return only concrete types.
Similarly, you have to be careful with lifetimes for similar reasons, since there's no static lifetime checking Rust is forced to believe you when you say a function returns &'a when it's really &'b.
Native Rust
The first tests I performed were on no custom structures; just pure, native Rust types. This would give a baseline for if this is even possible. I chose three baseline types: &mut i32, &mut Vec, and Option<i32> -> Option<i32>. These were all chosen for very specific reasons: the &mut i32 because it tests a reference, the &mut Vec because it tests growing the heap from memory allocated in the host application, and the Option as a dual purpose of testing passing by move and matching a simple enum.
All three work as expected. Mutating the reference mutates the value, pushing to a Vec works properly, and the Option works properly whether Some or None.
Shared Struct Definition
This was meant to test if you could pass a non-builtin struct with a common definition on both sides between plugin and host. This works as expected, but as mentioned in the "General Notes" section, can't promise you Rust won't fail to optimize and/or optimize a structure definition on one side and not another. Always test your specific use case and use CI in case it changes.
Boxed Trait Object
This test uses a struct whose definition is only defined on the plugin side, but implements a trait defined in a common crate, and returns a Box<Trait>. This works as expected. Calling trait_obj.fun() works properly.
At first I actually anticipated there would be issues with dropping without making the trait explicitly have Drop as a bound, but it turns out Drop is properly called as well (this was verified by setting the value of a variable declared on the test stack via raw pointer from the struct's drop function). (Naturally I'm aware drop is always called even with trait objects in Rust, but I wasn't sure if dynamic libraries would complicate it).
NOTE:
I did not test what would happen if you load a plugin, create a trait object, then drop the plugin (which would likely close it). I can only assume this is potentially catastrophic. I recommend keeping the plugin open as long as the trait object persists.
Remarks
Plugins work exactly as you'd expect just linking a crate naturally, albeit with some restrictions and pitfalls. As long as you test, I think this is a very natural way to go. It makes symbol loading more bearable, for instance, if you only need to load a new function and then receive a trait object implementing an interface. It also avoids nasty C memory leaks because you couldn't or forgot to load a drop/free function. That said, be careful, and always test!
There is no official plugin system, and you cannot do plugins loaded at runtime in pure Rust. I saw some discussions about doing a native plugin system, but nothing is decided for now, and maybe there will never be any such thing. You can use one of these solutions:
You can extend your code with native dynamic libraries using FFI. To use the C ABI, you have to use repr(C), no_mangle attribute, extern etc. You will find more information by searching Rust FFI on the internets. With this solution, you must use raw pointers: they come with no safety guarantee (i.e. you must use unsafe code).
Of course, you can write your dynamic library in Rust, but to load it and call the functions, you must go through the C ABI. This means that the safety guarantees of Rust do not apply there. Furthermore, you cannot use the highest level Rust's functionalities as trait, enum, etc. between the library and the binary.
If you do not want this complexity, you can use a language adapted to expand Rust: with which you can dynamically add functions to your code and execute them with same guarantees as in Rust. This is, in my opinion, the easier way to go: if you have the choice, and if the execution speed is not critical, use this to avoid tricky C/Rust interfaces.
Here is a (not exhaustive) list of languages that can easily extend Rust:
Gluon, a functional language like Haskell
Dyon, a small but powerful scripting language intended for video games
Lua with rlua or hlua
You can also use Python or Javascript, or see the list in awesome-rust.

BDD in Scala - Does it have to be ugly?

I've used lettuce for python in the past. It is a simple BDD framework where specs are written in an external plain text file. Implementation uses regex to identify each step, proving reusable code for each sentence in the specification.
Using scala, either with specs2 or scalatest I'm being forced to write the the specification alongside the implementation, making it impossible to reuse the implementation in another test (sure, we could implement it in a function somewhere) and making it impossible to separate the test implementation from the specification itself (something that I used to do, providing acceptance tests to clients for validation).
Concluding, I raise my question: Considering the importance of validating tests by clients, is there a way in BDD frameworks for scala to load the tests from an external file, raising an exception if a sentence in the test is not implemented yet and executing the test normally if all sentences have been implemented?
I've just discovered a cucumber plugin for sbt. Tests would be implemented under test/scala and specifications would be kept in test/resources as plain txt files. I'm just not sure on how reliable the library is and if it will have support in the future.
Edit:
The above is a wrapper for the following plugin wich solves perfectly the problem and supports Scala.
https://github.com/cucumber/cucumber-jvm
This is all about trade-offs. The cucumber-style of specifications is great because it is pure text, that easily editable and readable by non-coders.
However they are also pretty rigid as specifications because they impose a strict format based on features and Given-When-Then. In specs2 for example we can write any text we want and annotate only the lines which are meant to be actions on the system or verification. The drawback is that the text becomes annotated and that pending must be explicitly specified to indicate what hasn't been implemented yet. Also the annotation is just a reference to some code, living somewhere, and you can of course use the usual programming techniques to get reusability.
BTW, the link above is an interesting example of trade-off: in this file, the first spec is "uglier" but there are more compile-time checks that the When step uses the information from a Given step or that we don't have a sequence of Then -> When steps. The second specification is nicer but also more error-prone.
Then there is the issue of maintaining the regular expressions. If there is a strict separation between the people writing the features and the people implementing them, then it's very easy to break the implementation even if nothing substantial changes.
Finally, there is the question of version control. Who owns the document? How can we be sure that the code is in sync with the spec? Who refactors the specification when required?
There is no, by far, perfect solution. My own conclusion is that BDD artifacts should be in the hand of developers and verified by the other stakeholders, reading the code directly if it's readable or reading an html/pdf output. And if the BDD artifacts are owned by developers they might as well use their own tools to make their life easier with verification (using a compiler when possible) and maintenance (using automated refactorings).
You said yourself that it is easy to make the implementation reusable by the normal methods Scala provides for this kind of stuf (methods, functions, traits, classes, types ...), so there isn't really a problem there.
If you want to give a version without code to your customer, you can still give them the code files, and if they can't ignore a little syntax, you probably could write a custom reporter writing all the text out to a file, maybe even formatted with as html or something.
Another option would be to use JBehave or any other JVM based framework, they should work with Scala without a problem.
Eric's main design criteria was sustainability of executable specification development (through refactoring) and not initial convenience due to "beauty" of simple text.
see http://etorreborre.github.io/specs2/
The features of specs2 are:
Concurrent execution of examples by default
ScalaCheck properties
Mocks with Mockito
Data tables
AutoExamples, where the source code is extracted to describe the example
A rich library of matchers
Easy to create and compose
Usable with must and should
Returning "functional" results or throwing exceptions
Reusable outside of specs2 (in JUnit tests for example)
Forms for writing Fitnesse-like specifications (with Markdown markup)
Html reporting to create documentation for acceptance tests, to create a User Guide
Snippets for documenting APIs with always up-to-date code
Integration with sbt and JUnit tools (maven, IDEs,...)
Specs2 is quite impressive in both design and implementation.
If you look closely you will see the DSL can be extended while you keep the typesafe-ty and strong command of domain code under development.
He who leaves aside the "is more ugly" argument and tries this seriously will find power.
Checkout the structured forms and snippets

Environment properties files in scala project

Just starting to learn scala for a new project. Have got to the point where I would like to define different properties files for the different environments the app is going to run on, ideally in a similar way to Rails - very lightweight, just one different properties file per environment that is loaded based on its name. I don't really care if it's a java properties file, YML or scala code.
In the spirit of not reinventing the wheel I've been looking to see if there is some accepted standard Scala way of doing this but I can't find one, I've found a few similar but not identical questions here where people suggest using system properties in the startup script but this feels like it would end up being a nightmare.
I could obviously implement it if needs be but feels like the sort of thing that should already exist. So - does it?
I'm using sbt if that makes a difference.
I know of Configgy. Also, Akka/Play 2.0 will be using Config, which looks nice too. See blog about the latter.
Basically, Configgy has been used for a while now, but has been deprecated, while Config will be all-new. However, having Config as the default Typesafe Stack configuration tool will probably make it the preferred tool for that pretty fast.
I have written a Configgy replacement called Configrity. It can use different input formats (like YAML), it's immutable, supports functional patterns and uses type class to convert automatically the values to the desired type.
I have written BeeConfig, a replacement for java.util.Properties except that it is a Scala API and uses UTF-encoded configuration files. It supports string interpolation, chaining and a bunch of other features. But its main objective is simplicity.
Bitbucket | Blog post
Rick

Why do web development frameworks tend to work around the static features of languages?

I was a little surprised when I started using Lift how heavily it uses reflection (or appears to), it was a little unexpected in a statically-typed functional language. My experience with JSP was similar.
I'm pretty new to web development, so I don't really know how these tools work, but I'm wondering,
What aspects of web development encourage using reflection?
Are there any tools (in statically typed languages) that handle (1) referring to code from a template page (2) object-relational mapping, in a way that does not use reflection?
Please see lift source. It doesn't use reflection for most of the code that I have studied. Almost everything is statically typed. If you are referring to lift views they are processed as Xml nodes, that too is not reflection.
Specifically referring to the <lift:Foo.bar/> issue:
When <lift:Foo.bar/> is encountered in the code, Lift makes a few guesses, how the original name should have been (different naming conventions) and then calls java.lang.Class.forName to get the class. (Relevant code in LiftSession.scala and ClassHelpers.scala.) It will only find classes registered with addToPackages during boot.
Note that it is also possible (and common) to register classes and methods manually. Convention is still that all transformations must be of the form NodeSeq => NodeSeq because that is the only thing which makes sense for an untyped HTML/XHTML output.
So, what you have is Lift‘s internal registry of node transformations on one side, and on the other side the implicit registry of the module. Both types use a simple string lookup to execute a method. I guess it is arguable if one is more reflection based than the other.