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aws-cdk.aws-lambda-python-alpha-2.9.0a0
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The CDK Construct Library for AWS Lambda in Python
| ویژگی | مقدار |
|---|---|
| سیستم عامل | OS Independent |
| نام فایل | aws-cdk.aws-lambda-python-alpha-2.9.0a0 |
| نام | aws-cdk.aws-lambda-python-alpha |
| نسخه کتابخانه | 2.9.0a0 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Amazon Web Services |
| ایمیل نویسنده | - |
| آدرس صفحه اصلی | https://github.com/aws/aws-cdk |
| آدرس اینترنتی | https://pypi.org/project/aws-cdk.aws-lambda-python-alpha/ |
| مجوز | Apache-2.0 |
# Amazon Lambda Python Library
<!--BEGIN STABILITY BANNER-->---
> 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 your source code when upgrading to a newer version of this package.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-->
This library provides constructs for Python Lambda functions.
To use this module, you will need to have Docker installed.
## Python Function
Define a `PythonFunction`:
```python
python.PythonFunction(self, "MyFunction",
entry="/path/to/my/function", # required
runtime=Runtime.PYTHON_3_8, # required
index="my_index.py", # optional, defaults to 'index.py'
handler="my_exported_func"
)
```
All other properties of `lambda.Function` are supported, see also the [AWS Lambda construct library](https://github.com/aws/aws-cdk/tree/main/packages/%40aws-cdk/aws-lambda).
## Python Layer
You may create a python-based lambda layer with `PythonLayerVersion`. If `PythonLayerVersion` detects a `requirements.txt`
or `Pipfile` or `poetry.lock` with the associated `pyproject.toml` at the entry path, then `PythonLayerVersion` will include the dependencies inline with your code in the
layer.
Define a `PythonLayerVersion`:
```python
python.PythonLayerVersion(self, "MyLayer",
entry="/path/to/my/layer"
)
```
A layer can also be used as a part of a `PythonFunction`:
```python
python.PythonFunction(self, "MyFunction",
entry="/path/to/my/function",
runtime=Runtime.PYTHON_3_8,
layers=[
python.PythonLayerVersion(self, "MyLayer",
entry="/path/to/my/layer"
)
]
)
```
## Packaging
If `requirements.txt`, `Pipfile` or `poetry.lock` exists at the entry path, the construct will handle installing all required modules in a [Lambda compatible Docker container](https://gallery.ecr.aws/sam/build-python3.7) according to the `runtime` and with the Docker platform based on the target architecture of the Lambda function.
Python bundles are only recreated and published when a file in a source directory has changed.
Therefore (and as a general best-practice), it is highly recommended to commit a lockfile with a
list of all transitive dependencies and their exact versions. This will ensure that when any dependency version is updated, the bundle asset is recreated and uploaded.
To that end, we recommend using [`pipenv`] or [`poetry`] which have lockfile support.
* [`pipenv`](https://pipenv-fork.readthedocs.io/en/latest/basics.html#example-pipfile-lock)
* [`poetry`](https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control)
Packaging is executed using the `Packaging` class, which:
1. Infers the packaging type based on the files present.
2. If it sees a `Pipfile` or a `poetry.lock` file, it exports it to a compatible `requirements.txt` file with credentials (if they're available in the source files or in the bundling container).
3. Installs dependencies using `pip`.
4. Copies the dependencies into an asset that is bundled for the Lambda package.
**Lambda with a requirements.txt**
```plaintext
.
├── lambda_function.py # exports a function named 'handler'
├── requirements.txt # has to be present at the entry path
```
**Lambda with a Pipfile**
```plaintext
.
├── lambda_function.py # exports a function named 'handler'
├── Pipfile # has to be present at the entry path
├── Pipfile.lock # your lock file
```
**Lambda with a poetry.lock**
```plaintext
.
├── lambda_function.py # exports a function named 'handler'
├── pyproject.toml # your poetry project definition
├── poetry.lock # your poetry lock file has to be present at the entry path
```
## Custom Bundling
Custom bundling can be performed by passing in additional build arguments that point to index URLs to private repos, or by using an entirely custom Docker images for bundling dependencies. The build args currently supported are:
* `PIP_INDEX_URL`
* `PIP_EXTRA_INDEX_URL`
* `HTTPS_PROXY`
Additional build args for bundling that refer to PyPI indexes can be specified as:
```python
entry = "/path/to/function"
image = DockerImage.from_build(entry)
python.PythonFunction(self, "function",
entry=entry,
runtime=Runtime.PYTHON_3_8,
bundling=python.BundlingOptions(
build_args={"PIP_INDEX_URL": "https://your.index.url/simple/", "PIP_EXTRA_INDEX_URL": "https://your.extra-index.url/simple/"}
)
)
```
If using a custom Docker image for bundling, the dependencies are installed with `pip`, `pipenv` or `poetry` by using the `Packaging` class. A different bundling Docker image that is in the same directory as the function can be specified as:
```python
entry = "/path/to/function"
image = DockerImage.from_build(entry)
python.PythonFunction(self, "function",
entry=entry,
runtime=Runtime.PYTHON_3_8,
bundling=python.BundlingOptions(image=image)
)
```
## Custom Bundling with Code Artifact
To use a Code Artifact PyPI repo, the `PIP_INDEX_URL` for bundling the function can be customized (requires AWS CLI in the build environment):
```python
from child_process import exec_sync
entry = "/path/to/function"
image = DockerImage.from_build(entry)
domain = "my-domain"
domain_owner = "111122223333"
repo_name = "my_repo"
region = "us-east-1"
code_artifact_auth_token = exec_sync(f"aws codeartifact get-authorization-token --domain {domain} --domain-owner {domainOwner} --query authorizationToken --output text").to_string().trim()
index_url = f"https://aws:{codeArtifactAuthToken}@{domain}-{domainOwner}.d.codeartifact.{region}.amazonaws.com/pypi/{repoName}/simple/"
python.PythonFunction(self, "function",
entry=entry,
runtime=Runtime.PYTHON_3_8,
bundling=python.BundlingOptions(
environment={"PIP_INDEX_URL": index_url}
)
)
```
The index URL or the token are only used during bundling and thus not included in the final asset. Setting only environment variable for `PIP_INDEX_URL` or `PIP_EXTRA_INDEX_URL` should work for accesing private Python repositories with `pip`, `pipenv` and `poetry` based dependencies.
If you also want to use the Code Artifact repo for building the base Docker image for bundling, use `buildArgs`. However, note that setting custom build args for bundling will force the base bundling image to be rebuilt every time (i.e. skip the Docker cache). Build args can be customized as:
```python
from child_process import exec_sync
entry = "/path/to/function"
image = DockerImage.from_build(entry)
domain = "my-domain"
domain_owner = "111122223333"
repo_name = "my_repo"
region = "us-east-1"
code_artifact_auth_token = exec_sync(f"aws codeartifact get-authorization-token --domain {domain} --domain-owner {domainOwner} --query authorizationToken --output text").to_string().trim()
index_url = f"https://aws:{codeArtifactAuthToken}@{domain}-{domainOwner}.d.codeartifact.{region}.amazonaws.com/pypi/{repoName}/simple/"
python.PythonFunction(self, "function",
entry=entry,
runtime=Runtime.PYTHON_3_8,
bundling=python.BundlingOptions(
build_args={"PIP_INDEX_URL": index_url}
)
)
```
نیازمندی
| مقدار | نام |
|---|---|
| <3.0.0,>=2.49.0 | aws-cdk-lib |
| <11.0.0,>=10.0.0 | constructs |
| <2.0.0,>=1.70.0 | jsii |
| >=0.0.3 | publication |
| ~=2.13.3 | typeguard |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| ~=3.7 | Python |
نحوه نصب
نصب پکیج whl aws-cdk.aws-lambda-python-alpha-2.9.0a0:
pip install aws-cdk.aws-lambda-python-alpha-2.9.0a0.whl
نصب پکیج tar.gz aws-cdk.aws-lambda-python-alpha-2.9.0a0:
pip install aws-cdk.aws-lambda-python-alpha-2.9.0a0.tar.gz