python:{LOCAL_PYTHON_VERSION}-slim-bookworm
.
LOCAL_PYTHON_VERSION
represents the Python version in your current Python environment.
Functions can depend on any Python or system packages installed into their container images. Tensorlake provides a declarative API
to define function container images with their dependencies. When you deploy an application, the function container images
are automatically built as part of the deployment process.
How to define images
Tensorlake gives you a library to define your own custom images when you need to customize the environment in which your functions run.1
Define your image
An image is defined using the
Image
class from the tensorlake
module. You can modify the base image, run commands to install dependencies at build time, and modify some image’s attributes, like its name.2
Associate your function to the image defined
In the function decorator, we pass the
image
object. This tells Tensorlake to run the function in the specified image.