Metadata-Version: 2.1
Name: aws-cdk.aws-s3-assets
Version: 1.62.0
Summary: Deploy local files and directories to S3
Home-page: https://github.com/aws/aws-cdk
Author: Amazon Web Services
License: Apache-2.0
Project-URL: Source, https://github.com/aws/aws-cdk.git
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: JavaScript
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Typing :: Typed
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: aws-cdk.assets (==1.62.0)
Requires-Dist: aws-cdk.aws-iam (==1.62.0)
Requires-Dist: aws-cdk.aws-kms (==1.62.0)
Requires-Dist: aws-cdk.aws-s3 (==1.62.0)
Requires-Dist: aws-cdk.core (==1.62.0)
Requires-Dist: aws-cdk.cx-api (==1.62.0)
Requires-Dist: constructs (<4.0.0,>=3.0.4)
Requires-Dist: jsii (<2.0.0,>=1.11.0)
Requires-Dist: publication (>=0.0.3)

## AWS CDK Assets

<!--BEGIN STABILITY BANNER-->---


![cdk-constructs: Experimental](https://img.shields.io/badge/cdk--constructs-experimental-important.svg?style=for-the-badge)

> The APIs of higher level constructs in this module are experimental and under active development. They are subject to non-backward compatible changes or removal in any future version. These are not subject to the [Semantic Versioning](https://semver.org/) model and breaking changes will be announced in the release notes. This means that while you may use them, you may need to update your source code when upgrading to a newer version of this package.

---
<!--END STABILITY BANNER-->

Assets are local files or directories which are needed by a CDK app. A common
example is a directory which contains the handler code for a Lambda function,
but assets can represent any artifact that is needed for the app's operation.

When deploying a CDK app that includes constructs with assets, the CDK toolkit
will first upload all the assets to S3, and only then deploy the stacks. The S3
locations of the uploaded assets will be passed in as CloudFormation Parameters
to the relevant stacks.

The following JavaScript example defines an directory asset which is archived as
a .zip file and uploaded to S3 during deployment.

```python
# Example automatically generated. See https://github.com/aws/jsii/issues/826
asset = assets.Asset(self, "SampleAsset",
    path=path.join(__dirname, "sample-asset-directory")
)
```

The following JavaScript example defines a file asset, which is uploaded as-is
to an S3 bucket during deployment.

```python
# Example automatically generated. See https://github.com/aws/jsii/issues/826
asset = assets.Asset(self, "SampleAsset",
    path=path.join(__dirname, "file-asset.txt")
)
```

## Attributes

`Asset` constructs expose the following deploy-time attributes:

* `s3BucketName` - the name of the assets S3 bucket.
* `s3ObjectKey` - the S3 object key of the asset file (whether it's a file or a zip archive)
* `s3ObjectUrl` - the S3 object URL of the asset (i.e. s3://mybucket/mykey.zip)
* `httpUrl` - the S3 HTTP URL of the asset (i.e. https://s3.us-east-1.amazonaws.com/mybucket/mykey.zip)

In the following example, the various asset attributes are exported as stack outputs:

```python
# Example automatically generated. See https://github.com/aws/jsii/issues/826
asset = assets.Asset(self, "SampleAsset",
    path=path.join(__dirname, "sample-asset-directory")
)

cdk.CfnOutput(self, "S3BucketName", value=asset.s3_bucket_name)
cdk.CfnOutput(self, "S3ObjectKey", value=asset.s3_object_key)
cdk.CfnOutput(self, "S3HttpURL", value=asset.http_url)
cdk.CfnOutput(self, "S3ObjectURL", value=asset.s3_object_url)
```

## Permissions

IAM roles, users or groups which need to be able to read assets in runtime will should be
granted IAM permissions. To do that use the `asset.grantRead(principal)` method:

The following examples grants an IAM group read permissions on an asset:

```python
# Example automatically generated. See https://github.com/aws/jsii/issues/826
group = iam.Group(self, "MyUserGroup")
asset.grant_read(group)
```

## How does it work?

When an asset is defined in a construct, a construct metadata entry
`aws:cdk:asset` is emitted with instructions on where to find the asset and what
type of packaging to perform (`zip` or `file`). Furthermore, the synthesized
CloudFormation template will also include two CloudFormation parameters: one for
the asset's bucket and one for the asset S3 key. Those parameters are used to
reference the deploy-time values of the asset (using `{ Ref: "Param" }`).

Then, when the stack is deployed, the toolkit will package the asset (i.e. zip
the directory), calculate an MD5 hash of the contents and will render an S3 key
for this asset within the toolkit's asset store. If the file doesn't exist in
the asset store, it is uploaded during deployment.

> The toolkit's asset store is an S3 bucket created by the toolkit for each
> environment the toolkit operates in (environment = account + region).

Now, when the toolkit deploys the stack, it will set the relevant CloudFormation
Parameters to point to the actual bucket and key for each asset.

## Asset Bundling

When defining an asset, you can use the `bundling` option to specify a command
to run inside a docker container. The command can read the contents of the asset
source from `/asset-input` and is expected to write files under `/asset-output`
(directories mapped inside the container). The files under `/asset-output` will
be zipped and uploaded to S3 as the asset.

The following example uses custom asset bundling to convert a markdown file to html:

```python
# Example automatically generated. See https://github.com/aws/jsii/issues/826
asset = assets.Asset(self, "BundledAsset",
    path=path.join(__dirname, "markdown-asset"), # /asset-input and working directory in the container
    bundling=BundlingOptions(
        image=BundlingDockerImage.from_asset(path.join(__dirname, "alpine-markdown")), # Build an image
        command=["sh", "-c", "\n            markdown index.md > /asset-output/index.html\n          "
        ]
    )
)
```

The bundling docker image (`image`) can either come from a registry (`BundlingDockerImage.fromRegistry`)
or it can be built from a `Dockerfile` located inside your project (`BundlingDockerImage.fromAsset`).

You can set the `CDK_DOCKER` environment variable in order to provide a custom
docker program to execute. This may sometime be needed when building in
environments where the standard docker cannot be executed (see
https://github.com/aws/aws-cdk/issues/8460 for details).

Use `local` to specify a local bundling provider. The provider implements a
method `tryBundle()` which should return `true` if local bundling was performed.
If `false` is returned, docker bundling will be done:

```python
# Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826
assets.Asset(self, "BundledAsset",
    path="/path/to/asset",
    bundling={
        "local": {
            def try_bundle(output_dir, options):
                if can_run_locally: return Truereturn False
        },
        # Docker bundling fallback
        "image": BundlingDockerImage.from_registry("alpine"),
        "command": ["bundle"]
    }
)
```

Although optional, it's recommended to provide a local bundling method which can
greatly improve performance.

## CloudFormation Resource Metadata

> NOTE: This section is relevant for authors of AWS Resource Constructs.

In certain situations, it is desirable for tools to be able to know that a certain CloudFormation
resource is using a local asset. For example, SAM CLI can be used to invoke AWS Lambda functions
locally for debugging purposes.

To enable such use cases, external tools will consult a set of metadata entries on AWS CloudFormation
resources:

* `aws:asset:path` points to the local path of the asset.
* `aws:asset:property` is the name of the resource property where the asset is used

Using these two metadata entries, tools will be able to identify that assets are used
by a certain resource, and enable advanced local experiences.

To add these metadata entries to a resource, use the
`asset.addResourceMetadata(resource, property)` method.

See https://github.com/aws/aws-cdk/issues/1432 for more details


