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Parameters

As we learned in [parameters-intro], parameters declarations are useful to validate and coerce request parameters, produce 400 status responses on bad requests thereby providing some protection against bad input data.

Many requests embed parameters in their URIs. For example, let’s imagine a URI to access the transactions of a fictitious bank account.

https://bigbank.com/accounts/1234/transactions?since=tuesday

There could be 2 parameters here. The first, 1234, is contained in the path /accounts/1234/transactions. We call this a path parameter.

The second, tuesday, is embedded in the URI’s query-string (after the ? symbol). We call this a query parameter.

You can declare these parameters in the resource model.

{:parameters {:path {:entry Long}}
 :methods {:get {:parameters {:query {:since String}}}
           :post {:parameters {:body …}}}

Parameters can be specified at resource-level or at method-level. Path parameters are usually declared at the resource-level because they form part of the URI that is independent of the request’s method. In contrast, query parameters usually apply to GET requests, so it’s common to define this parameter at the method-level, and it’s only visible if the method we declare it with matches the request method.

We declare parameter values using the syntax of Plumatic's schema library. This allows us to get quite sophisticated in how we define parameters.

(require [schema.core :refer (defschema)]

(defschema Transaction
  {:payee String
   :description String
   :amount Double}

{:parameters {:path {:entry Long}}
 :methods {:get {:parameters {:query {:since String}}}
           :post {:parameters {:body Transaction}}}

Capturing multi-value parameters

Occasionally, you may have multiple values associated with a given parameter. Query strings and HTML form data both allow for the same parameter to be specified multiple times.

/search?accno=1234&accno=1235

To capture all values in a vector, declare your parameter type as a vector type:

{:parameters {:query {:accno [Long]}}}}

Capturing large request bodies

Sometimes, request bodies are very large or even unlimited. To ensure you don’t run out of memory receiving this request data, you can specify more suitable containers, such as files, database blobs, Amazon S3 buckets or your own extensions.

All data produced and received from yada is handled efficiently and asynchronously, ensuring that even with very large data streams your service continues to work.

{:parameters {:form {:video java.io.File}}}

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