@aws-sdk/client-machine-learning
Description
AWS SDK for JavaScript MachineLearning Client for Node.js, Browser and React Native.
Definition of the public APIs
exposed by Amazon Machine Learning
Installing
To install this package, simply type add or install @aws-sdk/client-machine-learning
using your favorite package manager:
npm install @aws-sdk/client-machine-learning
yarn add @aws-sdk/client-machine-learning
pnpm add @aws-sdk/client-machine-learning
Getting Started
Import
The AWS SDK is modulized by clients and commands.
To send a request, you only need to import the MachineLearningClient
and
the commands you need, for example DescribeMLModelsCommand
:
const { MachineLearningClient, DescribeMLModelsCommand } = require("@aws-sdk/client-machine-learning");
import { MachineLearningClient, DescribeMLModelsCommand } from "@aws-sdk/client-machine-learning";
Usage
To send a request, you:
- Initiate client with configuration (e.g. credentials, region).
- Initiate command with input parameters.
- Call
send
operation on client with command object as input. - If you are using a custom http handler, you may call
destroy()
to close open connections.
const client = new MachineLearningClient({ region: "REGION" });
const params = {
};
const command = new DescribeMLModelsCommand(params);
Async/await
We recommend using await
operator to wait for the promise returned by send operation as follows:
try {
const data = await client.send(command);
} catch (error) {
} finally {
}
Async-await is clean, concise, intuitive, easy to debug and has better error handling
as compared to using Promise chains or callbacks.
Promises
You can also use Promise chaining
to execute send operation.
client.send(command).then(
(data) => {
},
(error) => {
}
);
Promises can also be called using .catch()
and .finally()
as follows:
client
.send(command)
.then((data) => {
})
.catch((error) => {
})
.finally(() => {
});
Callbacks
We do not recommend using callbacks because of callback hell,
but they are supported by the send operation.
client.send(command, (err, data) => {
});
v2 compatible style
The client can also send requests using v2 compatible style.
However, it results in a bigger bundle size and may be dropped in next major version. More details in the blog post
on modular packages in AWS SDK for JavaScript
import * as AWS from "@aws-sdk/client-machine-learning";
const client = new AWS.MachineLearning({ region: "REGION" });
try {
const data = await client.describeMLModels(params);
} catch (error) {
}
client
.describeMLModels(params)
.then((data) => {
})
.catch((error) => {
});
client.describeMLModels(params, (err, data) => {
});
Troubleshooting
When the service returns an exception, the error will include the exception information,
as well as response metadata (e.g. request id).
try {
const data = await client.send(command);
} catch (error) {
const { requestId, cfId, extendedRequestId } = error.$metadata;
console.log({ requestId, cfId, extendedRequestId });
}
Getting Help
Please use these community resources for getting help.
We use the GitHub issues for tracking bugs and feature requests, but have limited bandwidth to address them.
To test your universal JavaScript code in Node.js, browser and react-native environments,
visit our code samples repo.
Contributing
This client code is generated automatically. Any modifications will be overwritten the next time the @aws-sdk/client-machine-learning
package is updated.
To contribute to client you can check our generate clients scripts.
License
This SDK is distributed under the
Apache License, Version 2.0,
see LICENSE for more information.
Client Commands (Operations List)
AddTags
Command API Reference / Input / Output
CreateBatchPrediction
Command API Reference / Input / Output
CreateDataSourceFromRDS
Command API Reference / Input / Output
CreateDataSourceFromRedshift
Command API Reference / Input / Output
CreateDataSourceFromS3
Command API Reference / Input / Output
CreateEvaluation
Command API Reference / Input / Output
CreateMLModel
Command API Reference / Input / Output
CreateRealtimeEndpoint
Command API Reference / Input / Output
DeleteBatchPrediction
Command API Reference / Input / Output
DeleteDataSource
Command API Reference / Input / Output
DeleteEvaluation
Command API Reference / Input / Output
DeleteMLModel
Command API Reference / Input / Output
DeleteRealtimeEndpoint
Command API Reference / Input / Output
DeleteTags
Command API Reference / Input / Output
DescribeBatchPredictions
Command API Reference / Input / Output
DescribeDataSources
Command API Reference / Input / Output
DescribeEvaluations
Command API Reference / Input / Output
DescribeMLModels
Command API Reference / Input / Output
DescribeTags
Command API Reference / Input / Output
GetBatchPrediction
Command API Reference / Input / Output
GetDataSource
Command API Reference / Input / Output
GetEvaluation
Command API Reference / Input / Output
GetMLModel
Command API Reference / Input / Output
Predict
Command API Reference / Input / Output
UpdateBatchPrediction
Command API Reference / Input / Output
UpdateDataSource
Command API Reference / Input / Output
UpdateEvaluation
Command API Reference / Input / Output
UpdateMLModel
Command API Reference / Input / Output