Create version that can be directly uploaded to AWS as a zip file #4
Description
I.e., without chalice dependency. Just the normal process.
https://github.com/ACC-HelloWorld/5-data-logging#aws-lambda-function
AccelerationConsortium/ac-dev-lab#231
AccelerationConsortium/ac-dev-lab#271
https://docs.aws.amazon.com/lambda/latest/dg/python-package.html
copying some code from the notebook mentioned in https://github.com/ACC-HelloWorld/5-data-logging#aws-lambda-function
# -*- coding: utf-8 -*-
"""1.5.2-mongodb-aws-lambda-prep.ipynb
Automatically generated by Colab.
Original file is located at
https://colab.research.google.com/github/AccelerationConsortium/ac-microcourses/blob/main/docs/courses/hello-world/1.5.2-mongodb-aws-lambda-prep.ipynb
# Preparing the Python code and dependencies for AWS Lambda
[](https://colab.research.google.com/github/AccelerationConsortium/ac-microcourses/blob/main/docs/courses/hello-world/1.5.2-mongodb-aws-lambda-prep.ipynb)
For simplicity, we'll package `pymongo`, our Python dependency, along with our `lambda_function.py` script per the [guidelines in the AWS docs](https://docs.aws.amazon.com/lambda/latest/dg/python-package.html). See also the [How to Use PyMongo to Connect MongoDB Atlas with AWS Lambda](https://www.mongodb.com/developer/products/atlas/awslambda-pymongo/) MongoDB tutorial and the [Manage Connections with AWS Lambda](https://www.mongodb.com/docs/atlas/manage-connections-aws-lambda/) MongoDB documentation page. This notebook is intended to be run on Google Colab.
"""
# Commented out IPython magic to ensure Python compatibility.
# %mkdir dependencies
# Commented out IPython magic to ensure Python compatibility.
# %pip install --target ./dependencies pymongo
# Commented out IPython magic to ensure Python compatibility.
# %%writefile lambda_function.py
# import os
# import json
# from pymongo import MongoClient
#
# atlas_uri = os.environ['ATLAS_URI']
# client = MongoClient(atlas_uri)
#
# def lambda_handler(event, context):
# try:
# payload = json.loads(event["body"])
# document = payload["document"]
# db_name = payload["database"]
# collection_name = payload["collection"]
# db = client[db_name]
# collection = db[collection_name]
# result = collection.insert_one(document)
# return {
# "statusCode": 200,
# "body": json.dumps({"message": "Document inserted successfully"}),
# }
# except Exception as e:
# return {
# "statusCode": 500,
# "body": json.dumps({"error": str(e)}),
# }
#
# Commented out IPython magic to ensure Python compatibility.
# %cd dependencies
!zip -r ../deployment.zip *
# %cd ..
!zip deployment.zip lambda_function.py
"""Download the file:"""
import sys
if 'google.colab' in sys.modules:
from google.colab import files
files.download('deployment.zip')
"""NOTE: If the above cell doesn't work in Google Colab, you can download `deployment.zip` using the left navigation bar by **hovering over the file**, clicking the three vertical dots, and clicking "download", as shown below. If you don't see the file, you may need to click the refresh icon near the top of the sidebar. You will then upload this `.zip` file to AWS Lambda.
"""
In our case, we don't need to package pymongo. However, we do need the dependencies in https://github.com/AccelerationConsortium/streamingLambda/blob/main/requirements.txt, except for chalice. Write a GitHub action that automatically creates a new deployment.zip for new release versions.
Keep in mind the dependency file within chalicelib/ folder.
The main overall goal is for people outside the AC organization to be able to easily and quickly create a lambda function for their own organization/research group/etc.
See also https://ac-training-lab.readthedocs.io/en/latest/devices/picam.html, which is sort of the entry point. The whole goal is to get a new, fully functioning LAMBDA_FUNCTION_URL (which also means dealing with the YouTube token.pickle and S3)