Boilerplate for deploying python shell jobs through shell script.

For developers, it will be useful as script can :

• Create egg file packaging extra py files and external libraries
• Upload main .py and .egg files to s3 bucket
• Deploy python shell job through cloudformation

It also allows deployment for different stages e.g. {developer}, dev, qa, prod.

Currently script allows to deploy one python shell job at a time. With tweak, it can also be used in Jenkins CI/CD to deploy all python shell jobs.

• Any shell tool e.g. Cygwin or Gitbash
• aws cli
• S3 bucket to store .egg and .py files

1. Python shell job files must be kept under /python_shell/src folder.
2. Filename must always have prefix e.g. bp_sample_ps.py for bp project
3. Entry file of python shell job must have naming convnetion as __ps.py e.g. bp_sample_ps.py for bp project, sample python shell job.
4. Egg package setup file must have naming convnetion as __setup.py e.g. bp_sample_ps.py for bp project, sample python.
5. Cloudformation template files for python shell job must be kept under cf//python_shell folder.
6. Cludformation template must have naming convnetion as __job.pjson e.g. bp_sample_job.json for bp project, sample python shell job.

Add ENV configuration in utility/src/config/env.py file for different stages

Example of ENV Configuration:

'aws_region':'us_east_1',
's3_data_lake':'{}-data-lake-{}'.format(project, STAGE),
'incoming_folder':'incoming',
'primary_folder': 'primary',
'glue_role':'{}_glue_role_{}'.format(project, STAGE)

Modify following configuration in deploy/deploy_python_shell.sh

# Specify bucket in which you wish to upload zip and .py files
build_bucket='<specify build artifacts bucket>'
# Project prefix. 
project="<project prefix>"
# Default Stage
stage="dev"
# AWS profile to be used in AWS CLI
aws_profile="default"
# ARN of Glue Role to be used in Glue operation.
glue_role_arn='<specify Glue Role ARN>'
# Egg package version
egg_package_version=<Egg Package version. Default: 0.1>

## Usage

### To Deploy: ./deploy/deploy_python_shell.sh <python_shell_job> -stage <stage>
### To Sync S3 only: ./deploy/deploy_python_shell.sh <python_shell_job> -stage <stage> -sync

## Arguments

### python_shell_job    mandatory
###                     python shell job name if selective python shell job should be deployed. It should be _ps.py file name without _ps.py 
###                     e.g. for bp_sample_ps.python_shell_job will be *bp_sample*.

### -stage              mandatory
###                     To define stage

### stage               mandatory with -stage
###                     it will be used to pass stage environment parameters.
###                     it can be {developer name}, dev, qa or prod.
###                     {developer name} is useful in case of multiple developers are working on same job in same region.

### -sync               optional
###                     if specified, only files will be synced to s3 and CF will not be deployed/updated.
###                     it is useful during development where modifications are frequent in source code than in cloudformation template.

Always run script from project root folder instead of from deploy folder.

If Python shell job is already deployed through Cloudformation and you wish to only sync Python shell source code with S3 bucket, add -sync parameter. It will sync S3 but will not attempt to update CF.

./deploy/deploy_python_shell.sh bp_sample -stage sandeep

1. It will deploy bp_sample_ps.py python shell job along with its depedencies using sandeep stage environment and bp_sample_job.json kept at cf/ingestion/python_shell location.
2. In S3, files will be stored at <build_bucket>/sandeep location.
3. In Cloudformation, bp-sample-sandeep stack will be deployed
4. Python shel job bp-sample-sandeep will be created.

Bonus: You may also use clean.sh to clean temp files created during build. It may be useful during pushing code to git or distributing/sharing to others.