2. Introduction¶
This tutorial will help you get started with FaaS.
Prerequisites
Basic use case: Single function
Deploy a function as a service
Execute the service manually and view the output
Advance use case: Multiple functions
Deploy several functions as a package
Deploy a service of the package
Set trigger events to the functions
Execute the functions and view the output and logs
First, log in to the platform by running the following Python code in the terminal or your IDE:
import dtlpy as dl
if dl.token_expired():
dl.login()
Your browser will open a login screen, allowing you to enter your credentials or log in with Google. Once the “Login Successful” tab appears, you are allowed to close it.
This tutorial requires a project. You can create a new project, or alternatively use an existing one:
# Create a new project
project = dl.projects.create(project_name='project-sdk-tutorial')
# Use an existing project
project = dl.projects.get(project_name='project-sdk-tutorial')
Let’s create a dataset to work with and upload a sample item to it:
dataset = project.datasets.create(dataset_name='dataset-sdk-tutorial')
item = dataset.items.upload(
local_path=[
'https://raw.githubusercontent.com/dataloop-ai/dtlpy-documentation/main/assets/images/hamster.jpg'],
remote_path='/folder_name')
# Remote path is optional, images will go to the main directory by default