Hazard post-processing pipeline as serverless AWS infrastructure.
- Documentation: https://gns-science.github.io/toshi-hazard-post
- GitHub: https://github.com/gns-science/toshi-hazard-post
- PyPI: https://pypi.org/project/toshi-hazard-post/
- Free software: AGPL
- Run hazard aggregation task LOCAL or DOCKER or LAMBDA
python3 -m toshi_hazard_post.cli
docker build . -t toshi-hazard-post
docker run --rm -it toshi-hazard-post -s bash
/app$> python toshi_hazard_post.cli --help
TODO -> DOCKER_BUILD.md
docker run -it --rm \
--memory=30g --memory-swap=30g \
--env-file docker_environ \
-v $HOME/.aws/credentials:/root/.aws/credentials:ro \
toshi-hazard-post:latest \
-s bash
then ...
thp --help
In order to deploy the example, you need to run the following command:
$ serverless deploy
After running deploy, you should see output similar to:
Deploying aws-python-project to stage dev (us-east-1)
✔ Service deployed to stack aws-python-project-dev (112s)
functions:
hello: aws-python-project-dev-hello (1.5 kB)
After successful deployment, you can invoke the deployed function by using the following command:
serverless invoke --function hello
Which should result in response similar to the following:
{
"statusCode": 200,
"body": "{\"message\": \"Go Serverless v3.0! Your function executed successfully!\", \"input\": {}}"
}
You can invoke your function locally by using the following command:
serverless invoke local --function hello
Which should result in response similar to the following:
{
"statusCode": 200,
"body": "{\"message\": \"Go Serverless v3.0! Your function executed successfully!\", \"input\": {}}"
}
In case you would like to include third-party dependencies, you will need to use a plugin called serverless-python-requirements
. You can set it up by running the following command:
serverless plugin install -n serverless-python-requirements
Running the above will automatically add serverless-python-requirements
to plugins
section in your serverless.yml
file and add it as a devDependency
to package.json
file. The package.json
file will be automatically created if it doesn't exist beforehand. Now you will be able to add your dependencies to requirements.txt
file (Pipfile
and pyproject.toml
is also supported but requires additional configuration) and they will be automatically injected to Lambda package during build process. For more details about the plugin's configuration, please refer to official documentation.
This package was created with Cookiecutter and the waynerv/cookiecutter-pypackage project template.