This documentation aims at being a quick-straight-to-the-point-hands-on AWS resources manipulation with [boto3][0].
First of all, you'll need to install [boto3][0]. Installing it along with [awscli][1] is probably a good idea as
| #!/usr/bin/env python | |
| # Simple [boto3](https://github.com/boto/boto3) based EC2 manipulation tool | |
| # | |
| # To start an instance, create a yaml file with the following format: | |
| # | |
| # frankfurt: | |
| # - subnet-azb: | |
| # - type: t2.micro | |
| # image: image-tagname |
Asynchronous programming can be tricky for beginners, therefore I think it's useful to iron some basic concepts to avoid common pitfalls.
For an explanation about generic asynchronous programming, I recommend you one of the [many][2] [resources][3] [online][4].
I will focus on solely on asynchronous programming in [Tornado][1]. From Tornado's homepage:
| #!/usr/bin/env python | |
| """ | |
| A script to query the Amazon Web Services usage reports programmatically. | |
| Ideally this wouldn't exist, and Amazon would provide an API we can use | |
| instead, but hey - that's life. | |
| Basically takes your AWS account username and password, logs into the | |
| website as you, and grabs the data out. Always gets the 'All Usage Types' |
| #!/usr/bin/env python | |
| """This is a demonstration of sharing file descriptors across processes. | |
| It uses Tornado (need a recent post-2.0 version from github) and the | |
| multiprocessing module (from python 2.6+). To run it, start one copy | |
| of fdserver.py and one or more copies of testserver.py (in different | |
| terminals, or backgrounded, etc). Fetch http://localhost:8000 and | |
| you'll see the requests getting answered by different processes (it's | |
| normal for several requests to go to the same process under light | |
| load, but under heavier load it tends to even out). |
