Jinqu-odata lets you write LINQ queries against an odata source. For those who don't know LINQ, the benefits are:
- A unified query language, whether querying local arrays, odata sources, or any other remote data source
- Static typing where Typescript can verify your query is sound
jinqu-odata is dependent on the jinqu package.
npm install jinqu-odata
First, we need classes that map to our odata resources. For example:
@oDataResource('Books')
export class Book {
Id: number
Title: string
}
We can now query filtered books as follows:
const service = new ODataService ("https://www.solenya.org/odata")
const books = await service
.createQuery(Book)
.where(b => b.Price > 60)
.toArrayAsync()
for (var b of books)
console.log (b)
You can play with the live sample here
The query is translated to the following odata url:
https://www.solenya.org/odata/Books?$filter=Price gt 60
A common pattern is to inherit from ODataService
to provide stubs for your odata resources as follows:
export class CompanyService extends ODataService {
constructor (provider?: IAjaxProvider) {
super('odata')
}
companies() {
return this.createQuery(Company)
}
}
Currently we don't have code generators for jinqu-odata. However, we're actively considering this feature and it's tracked by this github issue:
jinqu-odata translates LINQ queries to OData Version 4 query strings. In the quries that follow, translations are shown as comments. You can check the unit tests for more thorough coverage of the translations.
To filter results we use the where
operator:
const result = await query
.where(c => c.name.startsWith('Net'))
.toArrayAsync()
// odata/Companies?$filter=startsWith(name, "Net")
Name | TypeScript/JavaScript | OData |
---|---|---|
Equals | ==, === | eq |
Not Equals | !=, !== | ne |
Greater Than | > | gt |
Greater Than or Equal | >= | ge |
Less Than | < | lt |
Less Than or Equal | <= | le |
Logical And | && | and |
Logical Or | || | or |
Logical Not | ! | not |
Arithmetic Add | + | add |
Arithmetic Subtraction | - | sub |
Arithmetic Multiplication | * | mul |
Arithmetic Division | / | div |
Arithmetic Modulo | % | mod |
Arithmetic Negation | - | - |
TypeScript/JavaScript | OData |
---|---|
includes | substringof |
endsWith | endswith |
startsWith | startswith |
length | length |
indexOf | indexof |
replace | replace |
substring | substring |
toLowerCase | tolower |
toUpperCase | toupper |
trim | trim |
concat | concat |
getMonth | month |
getDate | day |
getHours | hour |
getMinutes | minute |
getSeconds | second |
Math.round | round |
Math.floor | floor |
Math.ceiling | ceiling |
The select
operator lets us select only a subset of the fields of a type. It can only occur as the last operator in a query, so must be awaited:
const result = await query.select("name")
// $select=name
The orderBy
operator, optionally followed by some thenBy
operators, specifies result order:
const result = await query
.orderBy(c => c.category)
.thenByDescending(c => c.created).toArrayAsync()
// $orderby=category,created desc
To get the count of a resource:
const count = await query.count()
// Companies/$count will be executed
We can skip a number of items, or limit the number of items, by calling skip
and take
. Here we query for the 3rd page in a result, by skipping the first 20 results, and then returning the top 10 of the remaining results:
const result = await query.skip(20).take(10).toArrayAsync()
// $skip=20&$top=10
We can use the inlineCount
operator to populate the $inlineCount
property on the results.
const result = await query.inlineCount().toArrayAsync()
const inlineCount = result.$inlineCount // only populated if inlineCount operator was called
This is useful in the preceding skip/take
scenario, where to implement paging, we'd like the result to include a total non-paged count, without having to write a separate query. Just add the inlineCount
operator before calling skip/take
.
jinqu-odata supports expand, which enables you to pull in related entities. In this example, we don't merely want to return books; we also want to return the press associated with each book. We can do this as follows:
const companies = await service
.createQuery(Book)
.expand("Press")
.toArrayAsync()
// books$expand=Press
Sometimes we want to drill down more than one level. In this example, our odata source has books
, where we want to return all the authors for some books. However, since books can have multiple authors, there's a join table between Authors and Books. Our model will mirror the odata metadata as follows:
@oDataResource('Books')
export class Book {
Title: string
@Type(() => AuthorBook) AuthorBooks: AuthorBook[]
}
export class AuthorBook {
@Type(() => Author) Author: Author
}
export class Author {
Name: string
}
To query, we first expand
the AuthorBooks
property, and thenExpand
the Book
property, as follows:
const books = await service
.createQuery(Book)
.expand("AuthorBooks")
.thenExpand("Author")
.toArrayAsync()
// books?$expand=AuthorBooks($expand=Author)
For efficiency, we can filter by rows an expand
/thenExpand
query by providing a predicate:
.thenExpand("Author") // no filter
.thenExpand("Author", a => a.endsWith ("Albahari")) // filtered
// books?$expand=AuthorBooks($expand=Author($filter=endswith(Name,'Albahari')))
Similarly, for efficiency, we can filter by columns an expand
/thenExpand
query by providing an array of column names:
.thenExpand("Author") // no filter
.thenExpand("Author", ["Name"]) // filtered columns
// books?$expand=AuthorBooks($expand=Author($select=Name))
The @Type
decorators belong to the class-transformer
library that handles deserialization. We need those annotations since the typescript types aren't actually available at runtime. The class-transformer
library imposes the small design restriction on us that any constructor arguments to our classes are optional.
groupBy
lets you group results by a particular property. Like select
, it can only be used as the last operator in a query, and must therefore be awaited:
// we group resources by "deleted" field
// and select the count of each group with "deleted" field
const promise = await query.groupBy(
c => ({ deleted: c.deleted }),
g => ({ deleted: g.deleted, count: g.count() })
)
// $apply=groupby((deleted),aggregate(deleted,$count as count))
As you can see in the translation, jinqu-odata supports groupBy
with the $apply
convention.
jinqu-odata is licensed under the MIT License.