Metadata-Version: 2.1
Name: aws_jupyter_proxy
Version: 0.1.0
Summary: A Jupyter server extension to proxy requests with AWS SigV4 authentication
Home-page: https://github.com/aws/aws-jupyter-proxy
Author: Amazon Web Services
License: Apache License 2.0
Description: # AWS Jupyter Proxy
        
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        ![Version](https://img.shields.io/pypi/v/aws_jupyter_proxy.svg)
        ![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)
        
        A Jupyter server extension to proxy requests with AWS SigV4 authentication.
        
        ## Overview
        
        This server extension enables the usage of the [AWS JavaScript/TypeScript SDK](https://github.com/aws/aws-sdk-js) without having to export AWS credentials to the browser.
        
        A single `/awsproxy` endpoint is added on the Jupyter server which receives incoming requests from the browser, uses the credentials on the server to add [SigV4](https://docs.aws.amazon.com/general/latest/gr/signature-version-4.html) authentication to the request, and then proxies the request to the actual AWS service endpoint.
        
        All requests are proxied back-and-forth as-is, e.g., a 4xx status code from the AWS service will be relayed back as-is to the browser.
        
        NOTE: This project is still under active development
        
        ## Install
        
        Installing the package from PyPI will install and enable the server extension on the Jupyter server.
        
        ```bash
        pip install aws-jupyter-proxy
        ```
        
        ## Usage
        
        Using this requries no additional dependencies in the client-side code. Just use the regular AWS JavaScript/TypeScript SDK methods and add any dummy credentials and change the endpoint to the `/awsproxy` endpoint.
        
        ```typescript
            import * as AWS from 'aws-sdk';
            import SageMaker from 'aws-sdk/clients/sagemaker';
        
        
            // These credentials are *not* used for the actual AWS service call but you have
            // to provide any dummy credentials (Not real ones!)
            AWS.config.secretAccessKey = 'IGNOREDIGNORE/IGNOREDIGNOREDIGNOREDIGNOR';
            AWS.config.accessKeyId = 'IGNOREDIGNO';
        
            // Change the endpoint in the client to the "awsproxy" endpoint on the Jupyter server.
            const proxyEndpoint = 'http://localhost:8888/awsproxy';
        
            const sageMakerClient = new SageMaker({
                region: 'us-west-2',
                endpoint: proxyEndpoint,
            });
        
            // Make the API call!
            await proxySageMaker
                .listNotebookInstances({
                    NameContains: 'jaipreet'
                })
                .promise();
        ```
        
        ### Usage with S3
        
        For S3, use the `s3ForcePathStyle` parameter during the client initialization
        
        ```typescript
            import S3 from 'aws-sdk/clients/s3';
        
            const s3Client = new S3({
                region: 'us-west-2',
                endpoint: proxyEndpoint,
                s3ForcePathStyle: true
            });
        
            await s3Client.getObject({
                Bucket: 'my-bucket',
                Key: 'my-object'
            }).promise();
        ```
        
        ## Development
        
        Install all dev dependencies
        
        ```bash
        pip install -e ".[dev]"
        jupyter serverextension enable --py aws_jupyter_proxy
        ```
        
        Run unit tests using pytest
        
        ```bash
        pytest tests/unit
        ```
        
        ## License
        
        This library is licensed under the Apache 2.0 License.
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Provides-Extra: dev
