I have created a number of JSON schemas that reference http://json-schema.org/draft-04/schema#. Let's say I call these myschema1.schema.json, myschema2.schema.json etc. I am saving JSON strings that have been validated against one of these schemas and at a later date I need to be able to edit that data and re-validate it against the original schema. How can I include a reference to the original schema in the saved JSON file? I thought about simply including it as a property but I don't want this schema property to be included when dynamically creating a class based on the JSON properties as I don't want it to be included in the edit form.
Here's what I would like to be able to do..
{
"$schema": "http://someURI/myschema1",
"Property 1": "One",
"Property 2": "Two"
}
..but as the property name $schema is not included in the schema it fails validation. Any suggestions would be most welcome. Thanks!
Related
I am working on a Power Automate flow to get a JSON file from SharePoint and Parse it. On one of my previous questions I received a solution that worked with a testing JSON file. However when I ran a couple of tests with some JSON files that I need to use, the Parse JSON step gives out errors regarding "missing" required properties.
Basically, the JSON file's arrays do not always have exactly the same elements (properties). For example (below) the element "minimun_version" does not always appear under the element "link", like the image below
and because of this syntax I get the errors below
How can I Parse such a JSON file successfully?
Any idea or suggestion will help me get unstuck.
Thank you
You can allow null values in your Parse Json schema by simply adding that to the schema. April Dunnam has a nice article about this approach:
https://www.sharepointsiren.com/2018/10/flow-parse-json-null-error-fix/
I assume you have something like below in your schema?
"minimum_version": {
"type": "number"
}
You can change that to this to allow null values
"minimum_version": {
"type": [
"number",
"null"
]
}
I've been trying to create an ADF pipeline to move data from one of our databases into an azure storage folder - but I can't seem to get the transform to work correctly.
I'm using a Copy Data task and have the source and sink set up as datasets and data is flowing from one to the other, it's just the format that's bugging me.
In our Database we have a single field that contains a JSON object, this needs to be mapped into the sink object but doesn't have a Column name, it is simply the base object.
So for example the source looks like this
and my output needs to look like this
[
{
"ID": 123,
"Field":"Hello World",
"AnotherField":"Foo"
},
{
"ID": 456,
"Field":"Don't Panic",
"AnotherField":"Bar"
}
]
However, the Copy Data task seems to only seems to accept direct Source -> Sink mapping, and also is treating the SQL Server field as VARCHAR (which I suppose it is). So as a result I'm getting this out the other side
[
{
"Json": "{\"ID\": 123,\"Field\":\"Hello World\",\"AnotherField\":\"Foo\"}"
},
{
"Json": "{\"ID\": 456,\"Field\":\"Don't Panic\",\"AnotherField\":\"Bar\"}"
}
]
I've tried using the internal #json() parse function on the source field but this causes errors in the pipeline. I also can't get the sink to just map directly as an object inside the output array.
I have a feeling I just shouldn't be using Copy Data, or that Copy Data doesn't support the level of transformation I'm trying to do. Can anybody set me on the right path?
Using a JSON dataset as a source in your data flow allows you to set five additional settings. These settings can be found under the JSON settings accordion in the Source Options tab. For Document Form setting, you can select one of Single document, Document per line and Array of documents types.
Select Document form as Array of documents.
Refer - https://learn.microsoft.com/en-us/azure/data-factory/format-json
While developing a client application using one of our existing REST services, I have the choice for using JSON or XML responses. The XML responses are described by XSD files with schema information.
With these XML Schemas I can determine what datatype a certain result must be, and the client can use that information when presenting the data to the user, or when the client asks the user to change a property. (How is quit another question btw as I cannot find any multiplatform Delphi implementation of XML that supports XSD schemas... but like i said: that's another question).
The alternative is to use a JSON response type, but then the client cannot determine the specific datatype of a property because everything is send as a string.
How would a client know that one of those properties is a index from an enumerated type, or a integer number, or an amount or a reference to another object by its ID maybe? (These are just examples)
I would think that the client should not contain "hardcoded" info on the structure of the response, or am I wrong in assuming that?
JSON doesn't have a rich type system like XML does, and JSON doesn't have a schema system for describing things like enumerations and references like XML does. But JSON has only a few data types, and the general formatting of the JSON is self-describing in terms of what data type any given value is using (see the official JSON spec for more details):
a string is always wrapped in quotation marks:
"fieldname": "fieldvalue"
a numeric value is digit characters without quotations:
"fieldname": 12345
an object is always wrapped in curly braces:
"fieldname": { ... object data ... }
an array is always wrapped in square braces:
"fieldname": [ ... array data ... ]
a boolean is always a fixed true or false without quotations:
"name": true
"name": false
a null is always a fixed null without quotations:
"name": null
Anything beyond that will require the client to have external knowledge of the data that is being sent (like a schema in XML, since XML itself does not describe data types at all).
For a sample JSON data which looks like this -
{
"children":{
"Alice":{...},
"Jamie":{...},
"Bob":{...}
// Any new child with a given unique name will be added to this object
},
childrenOrder:["Alice", "Bob", "Jamie"]
}
In the corresponding JSON Schema, I am trying to limit the valid values in "childrenOrder" array to be from the run time children keys.
I didn't see any means of referring to runtime dynamic values in the official JSON Schema documentation (http://json-schema.org/documentation.html).
Is this even possible at the moment?
For the sake of brevity I omitted JSON Schema code. I can add it if folks think it is needed to address the question.
Thanks in advance.
No it is not possible using the current JSON Schema specification. However, there is a proposal for the next version of JSON Schema that could change that.
https://github.com/json-schema/json-schema/wiki/%24data-(v5-proposal)
I am asking this because I see that the current JSON schema draft (http://json-schema.org/) proposes to have the schema of JSON in the following way:
for the JSON :
{
"a":"abc"
"b": 123
}
the schema proposed in the draft is like
{
"type":"object"
"properties":{
"a": {"type":"string"}
"b": {"type":"integer"}
}
}
My question here is does the JSON itself not define its structure? Is a separate schema necessary?
The schema proposed by the draft validates the JSON that have the above structure and those JSON are always of the format
{
"a":"string"
"b": 1 (or some number)
}
So what is the need of a separate schema for JSON. We can simply use the JSON to define its structure also.
PS. I know that we can specify some restrictions on the values that the JSON can take through the schemas proposed in the draft, but from the point of view of defining structure of a JSON, are the proposed schemas necessary?
The JSON itself does not define the structure. For example, I could write:
{
"a": "string",
"b": "another string"
}
That's also valid JSON - but it's "differently structured" JSON, because "b" is now a string. But your API might only accept JSON with a particular structure, so although it's valid JSON, it's not the shape you need.
Now, do you need JSON Schema to define the structure of your JSON data? No. You could instead say:
The value must be an object. It must have two properties:
"a" - must be a string
"b" - must be an integer
A programmer could understand this very easily, with no squiggly brackets or anything.
However, there are advantages to having a machine-readable description of the format, because it lets you automate various things (e.g. testing, generating documentation, generating code/classes, etc.)
Edit: As pointed out in the comments, you can take the type information from some example data, and use that as a model for other data. In this case, you're basically using your example data as a super-basic schema.
For very simple constraints (basic type), this works. However, how would you say that "b" has to be an integer instead of a float? How do you say that "b" must be > 0? How do you say that "a" must not be the empty string ("")?
There are indeed tools that generate a basic JSON Schema from example data - however, the resulting schema usually requires a bit of tweaking to actually describe the format (e.g. min/max, required/optional properties, etc.).
Until now have never been necessary and in the short term I don't think it gets to be.
I personally like JSON because its simplicity, portability and flexibility.
I don't see even major brands using that schema so until now they don't take its serious.