Creating a Lambda function using Author from scratch mode. ├── lambda_function └── lambda_layers └── python └── lib └── python3.7 └── site-packagesįigure 1. # 1) Create project folder mkdir medium-lambda-tutorial # Change directory cd medium-lambda-tutorial/ # 2) Create environment using conda conda create -name lambda-tutorial python=3.7 conda activate lambda-tutorial # 3) Create one folder for the layers and another for the # lambda_function itself mkdir lambda_function lambda_layers # 4) Create the folder structure to build your lambda layer mkdir -p lambda_layers/python/lib/python3.7/site-packages tree. The folder structure we created is going to help you better understand the concept behind Amazon Lambda and also organize your functions and libraries. Finally, we can create the folder structure to build Lambda Layers so it can be identified by the Amazon Lambda (4). We’ll explain better what Lambda Layers consists later on the article. Next, we create two folders, one to save the python scripts of your Lambda function, and one to build your Lambda Layers (3). We first create a folder for the project (1) and the environment Python 3.7 using conda (you can also use pipenv )(2). I’m sure that after going through this tutorial you’ll have a good idea on migrating part of your local data analysis pipelines to Amazon Lambda.īefore we start messing around with Amazon Lambda, we should first set our working environment. Although using the AWS console for configuring your services is not the best practice approach to work on the cloud, we are going to show each step using the console, because it’s more convenient for beginners to understand the basic structure of Amazon Lambda. We are going to use Python3, boto3 and a few more libraries loaded in Lambda Layers to help us achieve our goal to load a CSV file as a Pandas dataframe, do some data wrangling, and save the metrics and plots on report files on an S3 bucket. The goal of this article is to present you a digestible tutorial for configuring your first Amazon Lambda function with external libraries and doing something more useful than just printing “Hello world!”. One of the main problems about Lambda is that it becomes tricky to set up as soon as your functions and triggers get more complex. It offers a relatively simple and straightforward platform for implementing functions on different languages like Python, Node.js, Java, C# and many more.Īmazon Lambda can be tested through the AWS console or AWS Command Line Interface. Amazon Lambda is probably the most famous serverless service available today offering low cost and practically no cloud infrastructure governance needed.
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