Pdf To Html Python Library
Tanja Freeze
For Lambda functions that use the Python runtime, a dependency can be any Python package or module. When you deploy your function using a .zip archive, you can either add these dependencies to your .zip file with your function code or use a Lambda layer. A layer is a separate .zip file that can contain additional code and other content. To learn more about using Lambda layers in Python, see Working with layers for Python Lambda functions.
The Lambda Python runtimes include the AWS SDK for Python (Boto3) and its dependencies. Lambda provides the SDK in the runtime for deployment scenarios where you are unable to add your own dependencies. These scenarios include creating functions in the console using the built-in code editor or using inline functions in AWS Serverless Application Model (AWS SAM) or AWS CloudFormation templates.
Lambda periodically updates the libraries in the Python runtime to include the latest updates and security patches. If your function uses the version of the Boto3 SDK included in the runtime but your deployment package includes SDK dependencies, this can cause version misalignment issues. For example, your deployment package could include the SDK dependency urllib3. When Lambda updates the SDK in the runtime, compatibility issues between the new version of the runtime and the version of urllib3 in your deployment package can cause your function to fail.
Under the AWS shared responsibility model, you are responsible for the management of any dependencies in your functions' deployment packages. This includes applying updates and security patches. To update dependencies in your function's deployment package, first create a new .zip file and then upload it to Lambda. See Creating a .zip deployment package with dependencies and Creating and updating Python Lambda functions using .zip files for more information.
If your function code depends on additional packages or modules, you can either add these dependencies to your .zip file with your function code or use a Lambda layer. The instructions in this section show you how to include your dependencies in your .zip deployment package. For Lambda to run your code, the .py file containing your handler code and all of your function's dependencies must be installed at the root of the .zip file.
Suppose your function code is saved in a file named lambda_function.py. The following example CLI commands create a .zip file named my_deployment_package.zip containing your function code and its dependencies. You can either install your dependencies directly to a folder in your project directory or use a Python virtual environment.
Note that for a .zip deployment package, Lambda expects your source code and its dependencies all to be at the root of the .zip file. However, installing dependencies directly in your project directory can introduce a large number of new files and folders and make navigating around your IDE difficult. You create a separate package directory here to keep your dependencies separate from your source code.
Install your dependencies in the package directory. The example below installs the Boto3 SDK from the Python Package Index using pip. If your function code uses Python packages you have created yourself, save them in the package directory.
The folder in which pip installs your libraries may be named site-packages or dist-packages. This folder may be located in either the lib/python3.x or lib64/python3.x directory (where python3.x represents the version of Python you are using).
Navigate into the directory containing the dependencies you installed with pip and create a .zip file in your project directory with the installed dependencies at the root. In this example, pip has installed your dependencies in the my_virtual_env/lib/python3.12/site-packages directory.
Navigate to the root of your project directory where the .py file containing your handler code is located and add that file to the root of your .zip package. In this example, your function code file is named lambda_function.py.
When you use an import statement in your code, the Python runtime searches the directories in its search path until it finds the module or package. By default, the first location the runtime searches is the directory into which your .zip deployment package is decompressed and mounted (/var/task). If you include a version of a runtime-included library in your deployment package, your version will take precedence over the version that's included in the runtime. Dependencies in your deployment package also have precedence over dependencies in layers.
When you add a dependency to a layer, Lambda extracts this to /opt/python/lib/python3.x/site-packages (where python3.x represents the version of the runtime you're using) or /opt/python. In the search path, these directories have precedence over the directories containing the runtime-included libraries and pip-installed libraries (/var/runtime and /var/lang/lib/python3.x/site-packages). Libraries in function layers therefore have precedence over versions included in the runtime.
You can also add dependencies in a separate folder inside your .zip package. For example, you might add a version of the Boto3 SDK to a folder in your .zip package called common. When your .zip package is decompressed and mounted, this folder is placed inside the /var/task directory. To use a dependency from a folder in your .zip deployment package in your code, use an import from statement. For example, to use a version of Boto3 from a folder named common in your .zip package, use the following statement.
We recommend that you don't include __pycache__ folders in your function's deployment package. Python bytecode that's compiled on a build machine with a different architecture or operating system might not be compatible with the Lambda execution environment.
If your Lambda function uses the x86_64 instruction set architecture, run the following pip install command to install a compatible wheel in your package directory. Replace --python 3.x with the version of the Python runtime you are using.
If your package is only available as a source distribution, you need to build the C/C++ libraries yourself. To make your package compatible with the Lambda execution environment, you need to build it in an environment that uses the same Amazon Linux 2 operating system. You can do this by building your package in an Amazon EC2 Linux instance.
Once you have created your .zip deployment package, you can use it to create a new Lambda function or update an existing one. You can deploy your .zip package using the Lambda console, the AWS Command Line Interface, and the Lambda API. You can also create and update Lambda functions using AWS Serverless Application Model (AWS SAM) and AWS CloudFormation.
The Lambda runtime needs permission to read the files in your deployment package. In Linux permissions octal notation, Lambda needs 644 permissions for non-executable files (rw-r--r--) and 755 permissions (rwxr-xr-x) for directories and executable files.
In Linux and MacOS, use the chmod command to change file permissions on files and directories in your deployment package. For example, to give an executable file the correct permissions, run the following command.
To create a new function, you must first create the function in the console, then upload your .zip archive. To update an existing function, open the page for your function, then follow the same procedure to add your updated .zip file.
If your .zip file is less than 50MB, you can create or update a function by uploading the file directly from your local machine. For .zip files greater than 50MB, you must upload your package to an Amazon S3 bucket first. For instructions on how to upload a file to an Amazon S3 bucket using the AWS Management Console, see Getting started with Amazon S3. To upload files using the AWS CLI, see Move objects in the AWS CLI User Guide.
You cannot change the deployment package type (.zip or container image) for an existing function. For example, you cannot convert a container image function to use a .zip file archive. You must create a new function.
(Optional) For Architecture, choose the instruction set architecture for your function. The default architecture is x86_64. Ensure that the .zip deployment package for your function is compatible with the instruction set architecture you select.
You can can use the AWS CLI to create a new function or to update an existing one using a .zip file. Use the create-function and update-function-code commands to deploy your .zip package. If your .zip file is smaller than 50MB, you can upload the .zip package from a file location on your local build machine. For larger files, you must upload your .zip package from an Amazon S3 bucket. For instructions on how to upload a file to an Amazon S3 bucket using the AWS CLI, see Move objects in the AWS CLI User Guide.
You must also specify the location of your .zip file. If your .zip file is located in a folder on your local build machine, use the --zip-file option to specify the file path, as shown in the following example command.
To specify the location of .zip file in an Amazon S3 bucket, use the --code option as shown in the following example command. You only need to use the S3ObjectVersion parameter for versioned objects.
To update an existing function using the CLI, you specify the the name of your function using the --function-name parameter. You must also specify the location of the .zip file you want to use to update your function code. If your .zip file is located in a folder on your local build machine, use the --zip-file option to specify the file path, as shown in the following example command.
To specify the location of .zip file in an Amazon S3 bucket, use the --s3-bucket and --s3-key options as shown in the following example command. You only need to use the --s3-object-version parameter for versioned objects.
The AWS Serverless Application Model (AWS SAM) is a toolkit that helps streamline the process of building and running serverless applications on AWS. You define the resources for your application in a YAML or JSON template and use the AWS SAM command line interface (AWS SAM CLI) to build, package, and deploy your applications. When you build a Lambda function from an AWS SAM template, AWS SAM automatically creates a .zip deployment package or container image with your function code and any dependencies you specify. To learn more about using AWS SAM to build and deploy Lambda functions, see Getting started with AWS SAM in the AWS Serverless Application Model Developer Guide.
d3342ee215