I have a Typescript app. I use the localstorage for development purpose to store my objects and I have the problem at the deserialization.
I have an object meeting of type MeetingModel:
export interface MeetingModel {
date: moment.Moment; // from the library momentjs
}
I store this object in the localStorage using JSON.stringify(meeting).
I suppose that stringify call moment.toJson(), that returns an iso string, hence the value stored is: {"date":"2016-12-26T15:03:54.586Z"}.
When I retrieve this object, I do:
const stored = window.localStorage.getItem("meeting");
const meeting: MeetingModel = JSON.parse(stored);
The problem is: meeting.date contains a string instead of a moment !
So, first I'm wondering why TypeScript let this happen ? Why can I assign a string value instead of a Moment and the compiler agree ?
Second, how can I restore my objects from plain JSON objects (aka strings) into Typescript types ?
I can create a factory of course, but when my object database will grow up it will be a pain in the *** to do all this work.
Maybe there is a solution for better storing in the local storage in the first place?
Thank you
1) TypeScript is optionally typed. That means there are ways around the strictness of the type system. The any type allows you to do dynamic typing. This can come in very handy if you know what you are doing, but of course you can also shoot yourself in the foot.
This code will compile:
var x: string = <any> 1;
What is happening here is that the number 1 is casted to any, which to TypeScript means it will just assume you as a developer know what it is and how you to use it. Since the any type is then assigned to a string TypeScript is absolutely fine with it, even though you are likely to get errors during run-time, just like when you make a mistake when coding JavaScript.
Of course this is by design. TypeScript types only exist during compile time. What kind of string you put in JSON.parse is unknowable to TypeScript, because the input string only exists during run-time and can be anything. Hence the any type. TypeScript does offer so-called type guards. Type guards are bits of code that are understood during compile-time as well as run-time, but that is beyond the scope of your question (Google it if you're interested).
2) Serializing and deserializing data is usually not as simple as calling JSON.stringify and JSON.parse. Most type information is lost to JSON and typically the way you want to store objects (in memory) during run-time is very different from the way you want to store them for transfer or storage (in memory, on disk, or any other medium). For instance, during run-time you might need lookup tables, user/session state, private fields, library specific properties, while in storage you might want version numbers, timestamps, metadata, different types of normalization, etc. You can JSON.stringify anything you want in JavaScript land, but that does necessarily mean it is a good idea. You might want to design how you actually store data. For example, an iso string looks pretty, but takes a lot of bytes. If you have just a few that does not matter, but when you are transferring millions a second you might want to consider another format.
My advise to you would be to define interfaces for the objects you want to save and like moment create a .toJson method on your model object, which will return the DTO (Data Transfer Object) that you can simply serialize with JSON.stringify. Then on the way back you cast the any output of JSON.parse to your DTO and then convert it back to your model with a factory function or constructor of your creation. That might seem like a lot of boilerplate, but in my experience it is totally worth it, because now you are in control of what gets stored and that gives you a lot of flexility to change your model without getting deserialization problems.
Good luck!
You could use the reviver feature of JSON.parse to convert the string back to a moment:
JSON.parse(input, (key, value) => {
if (key == "date") {
return parseStringAsMoment(value);
} else {
return value;
});
Check browser support for reviver, though, as it's not the same as basic JSON.parse
Related
I am trying to use the Mapper codec in my connectivity chain to convert a JSON object that looks like this:
{"test2":[
["column1","column2","column3"],
["16091", "449", "05302018"],
["16092", "705", "05302018"]
]}
to an EPL type. To me it looks like a sequence of sequences, so I used
event test1 {
sequence<string> values;
}
event test2 {
sequence<test1> tests;
}
But this gives me the error
Unable to parse event test.1: Incorrect type in get (you asked for map but its' actually list)
Any ideas how I should be using the Mapper codec to this end?
Unless explicitly remapped, that won't quite work. You have to consider the entire structure of the document from top to bottom. It's not a sequence of strings - it's a JSON object/dictionary at top-level, with a value that is a sequence of sequences of string.
A JSON object/dictionary can map to an event type based on field names. So as Matt's answer said, a JSON document like yours would need an event type like
event SomeEventType {
sequence<sequence<string > > test2;
}
If it's not appropriate to create an event type that exactly corresponds to the JSON document's structure, then you'll need to use the mapping codec to rearrange the fields in the JSON document to match the fields and sub-fields in an event type. Or possibly a custom codec; I think Matt's right that the mapper can't do exactly what you want.
Further, because JSON documents are type-less at the top-level, you'll need to make sure that the event type is defined somehow. There are multiple ways of doing that.
(1) If this particular connectivity will only send you events of one type, you can use the 'defaultEventType' configuration option of the apama.eventMap host plug-in at the top of your chain e.g.
apama.eventMap:
defaultEventMap: SomeEventType
(2) If it depends on the structure of the document, you'll need to use the classifier codec. That can take a message going towards the correlator, and assign it an event type based on the content of fields (or simply their presence). You can learn about it in the documentation.
(3) The transport will sometimes define it on messages being sent towards the correlator. For example, in the case of the Universal Messaging transport, then the 'tag' of the UM event will be used as the type. This may or may not be appropriate.
If you do end up doing anything non-trivial with the classifier or mapper, I'd strongly recommend use of the 'diagnostic codec' to help in developing the classifier or mapper rules. This is a codec you can put anywhere in the chain of codecs that will log every event going through it, so you can see how your rules are operating by seeing what happens before and after classification/mapping. You can read about it in the documentation, but it's usually as simple as putting '- diagnosticCodec' somewhere in your chain. I've found it absolutely invaluable when debugging connectivity chains.
you want your event type to look like:
event type1 {
sequence<sequence<string> > data;
}
it's not possible in the mapper directly to convert to your type2/type1 schema, but you'd be able to write your own codec to do that or do post-filtering in EPL.
HTH,
Matt
The majority of my development experience has been from dynamically typed languages like PHP and Javascript. I've been practicing with Golang for about a month now by re-creating some of my old PHP/Javascript REST APIs in Golang. I feel like I'm not doing things the Golang way most of the time. Or more generally, I'm not use to working with strongly typed languages. I feel like I'm making excessive use of map[string]interface{} and slices of them to box up data as it comes in from http requests or when it gets shipped out as json http output. So what I'd like to know is if what I'm about to describe goes against the philosophy of golang development? Or if I'm breaking the principles of developing with strongly typed languages?
Right now, about 90% of the program flow for REST Apis I've rewritten with Golang can be described by these 5 steps.
STEP 1 - Receive Data
I receive http form data from http.Request.ParseForm() as formvals := map[string][]string. Sometimes I will store serialized JSON objects that need to be unmarshaled like jsonUserInfo := json.Unmarshal(formvals["user_information"][0]) /* gives some complex json object */.
STEP 2 - Validate Data
I do validation on formvals to make sure all the data values are what I expect before using it in SQL queries. I treat everyting as a string, then use Regex to determine if the string format and business logic is valid (eg. IsEmail, IsNumeric, IsFloat, IsCASLCompliant, IsEligibleForVoting,IsLibraryCardExpired etc...). I've written my own Regex and custom functions for these types of validations
STEP 3 - Bind Data to SQL Queries
I use golang's database/sql.DB to take my formvals and bind them to my Query and Exec functions like this Query("SELECT * FROM tblUser WHERE user_id = ?, user_birthday > ? ",formvals["user_id"][0], jsonUserInfo["birthday"]). I never care about the data types I'm supplying as arguments to be bound, so they're all probably strings. I trust the validation in the step immediately above has determined they are acceptable for SQL use.
STEP 4 - Bind SQL results to []map[string]interface{}{}
I Scan() the results of my queries into a sqlResult := []map[string]interface{}{} because I don't care if the value types are null, strings, float, ints or whatever. So the schema of an sqlResult might look like:
sqlResult =>
[0] {
"user_id":"1"
"user_name":"Bob Smith"
"age":"45"
"weight":"34.22"
},
[1] {
"user_id":"2"
"user_name":"Jane Do"
"age":nil
"weight":"22.22"
}
I wrote my own eager load function so that I can bind more information like so EagerLoad("tblAddress", "JOIN ON tblAddress.user_id",&sqlResult) which then populates sqlResult with more information of the type []map[string]interface{}{} such that it looks like this:
sqlResult =>
[0] {
"user_id":"1"
"user_name":"Bob Smith"
"age":"45"
"weight":"34.22"
"addresses"=>
[0] {
"type":"home"
"address1":"56 Front Street West"
"postal":"L3L3L3"
"lat":"34.3422242"
"lng":"34.5523422"
}
[1] {
"type":"work"
"address1":"5 Kennedy Avenue"
"postal":"L3L3L3"
"lat":"34.3422242"
"lng":"34.5523422"
}
},
[1] {
"user_id":"2"
"user_name":"Jane Do"
"age":nil
"weight":"22.22"
"addresses"=>
[0] {
"type":"home"
"address1":"56 Front Street West"
"postal":"L3L3L3"
"lat":"34.3422242"
"lng":"34.5523422"
}
}
STEP 5 - JSON Marshal and send HTTP Response
then I do a http.ResponseWriter.Write(json.Marshal(sqlResult)) and output data for my REST API
Recently, I've been revisiting articles with code samples that use structs in places I would have used map[string]interface{}. For example, I wanted to refactor Step 2 with a more standard approach that other golang developers would use. So I found this https://godoc.org/gopkg.in/go-playground/validator.v9, except all it's examples are with structs . I also noticed that most blogs that talk about database/sql scan their SQL results into typed variables or structs with typed properties, as opposed to my Step 4 which just puts everything into map[string]interface{}
Hence, i started writing this question. I feel the map[string]interface{} is so useful because majority of the time,I don't really care what the data is and it gives me to the freedom in Step 4 to construct any data schema on the fly before I dump it as JSON http response. I do all this with as little code verbosity as possible. But this means my code is not as ready to leverage Go's validation tools, and it doesn't seem to comply with the golang community's way of doing things.
So my question is, what do other golang developers do with regards to Step 2 and Step 4? Especially in Step 4...do Golang developers really encourage specifying the schema of the data through structs and strongly typed properties? Do they also specify structs with strongly typed properties along with every eager loading call they make? Doesn't that seem like so much more code verbosity?
It really depends on the requirements just like you have said you don't require to process the json it comes from the request or from the sql results. Then you can easily unmarshal into interface{}. And marshal the json coming from sql results.
For Step 2
Golang has library which works on validation of structs used to unmarshal json with tags for the fields inside.
https://github.com/go-playground/validator
type Test struct {
Field `validate:"max=10,min=1"`
}
// max will be checked then min
you can also go to godoc for validation library. It is very good implementation of validation for json values using struct tags.
For STEP 4
Most of the times, We use structs if we know the format and data of our JSON. Because it provides us more control over the data types and other functionality. For example if you wants to empty a JSON feild if you don't require it in your JSON. You should use struct with _ json tag.
Now you have said that you don't care if the result coming from sql is empty or not. But if you do it again comes to using struct. You can scan the result into struct with sql.NullTypes. With that also you can provide json tag for omitempty if you wants to omit the json object when marshaling the data when sending a response.
Struct values encode as JSON objects. Each exported struct field
becomes a member of the object, using the field name as the object
key, unless the field is omitted for one of the reasons given below.
The encoding of each struct field can be customized by the format
string stored under the "json" key in the struct field's tag. The
format string gives the name of the field, possibly followed by a
comma-separated list of options. The name may be empty in order to
specify options without overriding the default field name.
The "omitempty" option specifies that the field should be omitted from
the encoding if the field has an empty value, defined as false, 0, a
nil pointer, a nil interface value, and any empty array, slice, map,
or string.
As a special case, if the field tag is "-", the field is always
omitted. Note that a field with name "-" can still be generated using
the tag "-,".
Example of json tags
// Field appears in JSON as key "myName".
Field int `json:"myName"`
// Field appears in JSON as key "myName" and
// the field is omitted from the object if its value is empty,
// as defined above.
Field int `json:"myName,omitempty"`
// Field appears in JSON as key "Field" (the default), but
// the field is skipped if empty.
// Note the leading comma.
Field int `json:",omitempty"`
// Field is ignored by this package.
Field int `json:"-"`
// Field appears in JSON as key "-".
Field int `json:"-,"`
As you can analyze from above information given in Golang spec for json marshal. Struct provide so much control over json. That's why Golang developer most probably use structs.
Now on using map[string]interface{} you should use it when you don't the structure of your json coming from the server or the types of fields. Most Golang developers stick to structs wherever they can.
So I've read all the posts on String Based Enums in Typescript, but I couldn't find a solution that meets my requirements. Those would be:
Enums that provide code completion
Enums that can be iterated over
Not having to specify an element twice
String based
The possibilities I've seen so far for enums in typescript are:
enum MyEnum {bla, blub}: This fails at being string based, so I can't simply read from JSONs which are string based...
type MyEnum = 'bla' | 'blub': Not iterable and no code completion
Do it yourself class MyEnum { static get bla():string{return "bla"} ; static get blub():string{return "blub"}}: Specifies elements twice
So here come the questions:
There's no way to satisfy those requirements simultaneously? If no, will it be possible in the future?
Why didn't they make enums string based?
Did someone experience similar problems and how did you solve them?
I think that implementing Enum in a C-like style with numbers is fine, because an Enum (similar to a Symbol) is usually used to declare a value that is uniquely identifiable on development time. How the machine represents that value on run time doesn't really concern the developer.
But what we developer sometimes want (because we're all lazy and still want to have all the benefits!), is to use the Enum as an API or with an API that does not share that Enum with us, even though the API is essentially an Enum because the valid value of a property only is foo and bar.
I guess this is the reason why some languages have string based Enums :)
How TypeScript handles Enums
If you look at the transpiled JavaScript you can see that TypeScript just uses a plain JavaScript Object to implement an Enum. For example:
enum Color {
Red,
Green,
Blue
}
will be transpiled to:
{
0: "Red",
1: "Green",
2: "Blue",
Blue: 2,
Green: 1,
Red: 0
}
This means you can access the string value like Color[Color.Red]. You will still have code completion and you do not have to specify the values twice. But you can not just do Object.keys(Color) to iterate over the Enum, because the values exist "twice" on the object.
Why didn't they make enums string based
To be clear Enums are both number and string based in that direct access is number and reverse map is string (more on this).
Meeting your requirement
You key reason for ruling out raw enums is
so I can't simply read from JSONs which are string based...
You will experience the same thing e.g. when reading Dates cause JSON has no date data type. You would new Date("someServerDateTime") to convert these.
You would use the same strategy to go from server side enum (string) to TS enum (number). Easy done thanks to the reverse lookup MyEnum["someServerString"]
Hydration
This process of converting server side data to client side active data is sometimes called Hydration. My favorite lib for this at the moment is https://github.com/pleerock/class-transformer
I personally handle this stuff myself at the server access level i.e. hand write an API that makes the XHR + does the serialization.
At my last job we automated this with code generation that did even more than that (supported common validation patterns between server and client code).
My server returns a list of objects in JSON. They might be Cats or Dogs, for example.
When I know that they'll all be Cats, I can set the AutoBeanCodex to work easily. When I don't know what types they are, though... what should I do?
I could give all of my entities a type field, but then I'd have to parse each entity before passing it to the AutoBeanCodex, which borders on defeating the point. What other options do I have?
Just got to play with this the other day, and fought it for a few hours, trying #Category methods and others, until I found this: You can create a property of type Splittable, which represents the underlying transport type that has some encoding for booleans/Strings/Lists/Maps. In my case, I know some enveloping type that goes over the wire at design time, and based on some other property, some other field can be any number of other autobeans.
You don't even need to know the type of the other bean at compile time, you could get values out using Splittable's methods, but if using autobeans anyway, it is nice to define the data that is wrapped.
interface Envelope {
String getStatus();
String getDataType();
Splittable getData();
}
(Setters might be desired if you sending data as well as recieving - encoding a bean into a `Splittable to send it in an envelope is even easier than decoding it)
The JSON sent over the wire is decoded (probably using AutoBeanCodex) into the Envelope type, and after you've decided what type must be coming out of the getData() method, call something like this to get the nested object out
SpecificNestedBean bean = AutoBeanCodex.decode(factory,
SpecificNestedBean.class,
env.getData()).as();
The Envelope type and the nested types (in factory above) don't even need to be the same AutoBeanFactory type. This could allow you to abstract out the reading/writing of envelopes from the generic transport instance, and use a specific factory for each dataType string property to decode the data's model (and nested models).
I have an interesting problem to solve that would be helped by successfully casting objects created by LINQ to SQL into a single master object that I could pass around. Here is the scenario at a high level.
I have a number of stored procedures that fetch data and then all return the exact same columns. The params into the procs and the logic vary greatly, so a single proc will not work. Then Linq creates a strongly typed object which is used throughout my application as parameter and return values.
I am using these strongly typed objects as noted above as parameters and return values in a series of filters used to analyze stocks. My client would like to change the order the order of the filters. The issue is that each succeeding filter will only work on what passed the last filter.
Currently I am hard coding my parameters, and if I could create a master object that I could cast any of these Linq objects to, I could then always pass and return the master object.
I have read the materials available on the internet about casting between different types such as static to anonymous types or a list of integers and an array list containing objects representing integers, but I need to actually cast one object into another.
What general direction would I take to solve this problem of converting strongly typed objects generated by linq that are exactly the same into a single master object?
Thank you for any of your thoughts.
If all your linq objects have the same fields, you could have them implement an interface defined with those common fields. Then the calls to your filter methods can depend on an interface rather than a specific implementation. In other words, the parameters in the filter methods will be of the interface type rather than a linq class type.
e.g.: Where ICommonFields is an interface you define with all the common fields in each l2s class -
public class Filterer
{
public ICommonFields filterStuff(ICommonFields x)
{
//do stuff
}
}
or -
public class Filterer
{
public T filterStuff<T>(T x)
where T: class, ICommonFields, new()
{
//do stuff
}
}
I'd prefer the generic version, as T becomes the actual type rather than a reference through an interface - linq-to-sql has issues when using a type through an interface with query expressions.
Edit: sorry, it was late when i first wrote this response (likely excuse! :). Fixed my obvious mistake with the example code :)
Although there might be a way to do this with casting, I'm going to offer you a quick and dirty solution - and I'm assuming that your resultant objects are collection-based:
Given that all of your child objects
all share the same columns, go ahead
and pick one of them to act as your
master object - then simply iterate
through the rows of your other LINQ
objects and add them to the collection
of your master object. If your
resultant object is a strongly typed
data table, then all you'd do is Add
to the .Rows collection.
Additionally, you might be able to just add the elements retrieved some subsequent LINQ queries directly to your master object depending upon how you write your SELECT causes in LINQ.