type Simple = JsonProvider<""" { "name":"John", "age":94 } """>
let simple = Simple.Parse(""" { "name":"Tomas", "age":4 } """)
simple.Age
simple.Name
The problem you're pointing out is not a problem with statically typed languages. It's a problem with bad languages.
If Java were conceived of today - I think it might look a little different with respect to this.
I'd like to point out that there are many areas wherein fluid typing might help a little bit, especially on the UI.
Have to make a class for 'every little thing' gets cumbersome.
I wish there was a 'lighter typing' opportunity in some cases (schema-ish JSON).
But I agree that in the long run, static typing is really the way to go for the most part.
It does the job but it's not nearly as nice as javascript or python. It's about double the code in Java and it doesn't read nicely.
I think it depends on what you're doing.
EDIT: also, java is bad at dealing with json if the api could return data in multiple different schemas and you don't know which one it is until you parse it but I've only run into this once and it's just bad API design.
Developing/experimenting/scripting is where it's painful.
It's a common challenge for Elm beginners.
There are less awful ways to deserialize JSON in other languages. In C# with JSON.Net, you have options ranging from very dynamic-style handling, all the way to fully-typed deserialization into POCOs, for example.
[1] I have no love for Salesforce; it's a mess. Their weird custom dialect of SQL for a REST API query language is also buckets of fun.
data DataMessage = DataMessage { company :: Text
}
deriving (Show)
$(deriveJSON defaultOptions ''DataMessage)
data DataList = DataList { _data :: [DataMessage]
}
deriving (Show)
$(deriveJSON defaultOptions { fieldLabelModifier = drop 1 } ''DataList)
Then there isn't much bloat. You wrote your types and generated your way to parse them.
You could test with:
main = do
print (encode (DataMessage "some-company"))
print (decode "{\"company\":\"some-company\"}" :: Maybe DataMessage)
print (encode (DataList [DataMessage "c1", DataMessage "c2", DataMessage "c3"]))
print (decode "{\"data\":[{\"company\":\"c1\"},{\"company\":\"c2\"}]}" :: Maybe DataList)
But this is hard with any typing system. Using dynamic typing will just hide the problems under the rug, and they will explode in your face later on. Static typing just made those problems explicit.
There are many benefits to static typing, beyond the external boundaries of the system, where it definitely lives up to its promises.
Furthermore every dynamic language I've used has had tooling spring up, e.g. in the form of linters, that includes at least some basic checking for type mismatch where possible. I'm not so sure static typing leads to problems. It isn't problem free--no programming language or paradigm is--but I do think the lack of it leads to some problems that are easily avoided without too much extra overhead.
As it happens, I agree that JSON is probably a long-term mistake, although it is definitely an improvement over XML, the previous player in that space.
In Java JSON is horrible for serialization because of Java behaviors (your best option is Object). That doesn't mean JSON is horrible for serialization, in general. Fields do have types (int, string, object, array) making it slightly better than arbitrary serialization.
Although I'd agree that I find development with dynamically typed languages a bit more chaotic than static or strongly typed ones. And not necessarily in a fun, good way, either.
Now, instead of fixing problem by enforcing some schema you propose to use dynamically typed programming language which won't solve the problem but instead will make it spread thorough the whole codebase.
At least static typing limits the damage to the code that directly deals with parsing JSON.
But these aren't needless errors. If something is not of the type that you expect, there should be an error, and static typing makes this more explicit. The verbosity is more to do with that particular implementation, not anything inherent to static type systems.
All the research from expiercal studies mostly all show that static vs dynamic languages all correlated with a Expertise reversal effect. This is for beginners not experience programmers. That at the start of the studies for the first 8 to 9 months novices have a negative correlation with the speed of development work with a statically typed language. After 8 to 9 months they gain a singificant boost from static type language.
Source to backup my statement and resource if you're interested @ Susan_hall
Functional Geekery Episode 55 – Andreas Stefik https://www.functionalgeekery.com/episode-55-andreas-stefik/...
Secondly another study that was published for Polymorphism in Python from the website (neverworkintheory)
Polymorphism in Python http://neverworkintheory.org/2016/06/13/polymorphism-in-pyth...
Gives the qoute: `Our findings show that the receiver in 97.4% of all call-sites in the average program can be described by a single static type using a conservative nominal type system using single inheritance. If we add parametric polymorphism to the type system, we increase the typeability to 97.9% of all call-sites for the average program.`
I could qoute other resources to backup my statements though if you want to have a skype coversation I'm up for a talk.
"A large class of errors are caught, earlier in the development process, closer to the location where they are introduced."
I would re-state this as:
"A large class of errors are introduced, which otherwise would not exist."
Consider dealing with JSON in Java. Every element, however deeply nested, needs to be cast, and miscasting leads to endless errors, elsewhere in the code. Given JSON whose structure changes (because you draw from an API which leaves out fields if they don't have data for that field) your only option is to cast to Object, and then you have to guess your way forward, figuring out what the Object might be.
Consider the Salesforce clone of Java, Apex, which I have had to work in this month.
The if() statements here are the same one's that I would have to write in Ruby or Python or PHP, but meanwhile I've had to do a bunch of other, useless work:
And then, downstream of this: I'm leaving out the code that is downstream of this function, but it is full of more of the same: guessing at fields, guessing at how they should be cast, using if() to guard against null or empty. Tons of unnecessary bloat. Lots of easy errors to make.Again, some of the if() statements need to be made in Ruby or Python or PHP, but the rest of it is just pure bloat. Verbose, unneeded and unhelpful.
In a dynamic language I could simply work with a deeply nested data structure of maps and lists, and I'd handle the casting at the very end of the process. In a dynamic language, I could treat everything as a string till the very end, and then cast to integers or dates or floats or strings as needed. In a dynamic language, I could write the code faster, with less errors, and with less code.
Static typing does not live up to its promises.
[ Edit to add ]
We have no control over the API that we draw from. We are drawing from the API of a different company. I wish they didn't use JSON. If they have to use JSON, I wish they at least enforced a consistent schema. But they don't. And that is why static type checking fails: because the real world is chaotic, and when you have to interact with that real world, you are often forced to do so dynamically, because of the mistakes that other companies have made. The real world is dynamic.
The idea that you can know an external API perfectly is a fantasy. The real world is messy. The real world does not always conform to a strict schema.
The notion that An External API Is Reliable is as stupid as the notion The Network Is Reliable:
https://blog.fogcreek.com/eight-fallacies-of-distributed-com...
[[ Further edit to add ]]
the_af wrote:
"Using dynamic typing will just hide the problems under the rug, and they will explode in your face later on. Static typing just made those problems explicit."
What I wrote was:
"In a dynamic language I could simply work with a deeply nested data structure of maps and lists, and I'd handle the casting at the very end of the process"
I'll simplify this: there are 3 times when we can enforce a schema:
1.) when the API call returns with a string
2.) on every line, scattered through dozens of functions
3.) at the end, when I have the data that I want
In my original comment, I advocated for #3. Here are the reasons I don't like the first 2 options:
#1 - the external API is bloated, so writing a schema for the whole thing would be difficult to justify in terms of business. We only need a tiny slice of the data.
#2 - having casting discovery information scattered through dozens of functions makes the code brittle and refactoring difficult.
With Ruby or Python or PHP or any dynamic language I have the option of #3: grab the data, cast everything as a string, grab the tiny sliver of data I actually need, and then enforce the schema on that tiny sliver. This is the data that I can cast to integers, floats, dates, etc -- whatever is actually needed.
In static-type languages such as Java, I'm forced to go with either #1 or #2, and they are both bad options.
About this, from tigershark:
"it is only the usage of an awful JSON library in a not so nice language"
Bad JSON is part of the real world. If your static-type language can not handle bad JSON, then it can not handle the real world. That is my point: static-type checking is too academic, too pure, for the real world.
As to "not so nice language", you are engaging in the No True Scotsman fallacy, which goes like this: no True statically typed language would be this bad! But following the No True Scotsman illogic, the rest of your unstated assumptions amount to: It's only the statically typed languages that most programmers actually use that are this bad! But somewhere there is a statically-typed language of such unbelievable purity, it overcomes all of these problems!