Airflow-aws-executors

This release is a fix-up of 1.1.2. Due to the issues outlined below, I yanked `1.1.2` to prevent further use of the binary. It's not something that is actively encouraged in PyPi, and I apologize for the harm this may have caused to your system. It won't happen again. Please change your `requirements.txt` to point to the `1.1.3` release. Thank you for your time.

Reasoning:
1. https://github.com/aelzeiny/airflow-aws-executors/issues/21
2. https://github.com/aelzeiny/airflow-aws-executors/issues/13

Adding more extensibility to AWS Batch - meaning that you have more control over how your AWS Batch tasks are launched at runtime. Specifically, you have control over what to do with airflow's executor_config variable.

Airflow 2.0 Released, with that came an upgrade in Marshmallow from 2 to 3.
So now this works with Airflow 1.10.5 to Airflow 2.0 on Python 3.6 or greater.
Neat!

Nope, I'm not selling lemons here. I have a high standard for components not being a routine bother. The nice thing about using an AWS Executor is that there are a lot of things that are managed for you. Scheduling, container placement, monitoring, alerting, provisioning, and auto-scaling to name a few.