AWS

Amazon Web Services (AWS) offers reliable, scalable, and inexpensive cloud computing services.

Integrate the AWS API with the Python API

Setup the AWS API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate AWS and Python remarkably fast. Free for developers.

Run Python Code with Python API on New Scheduled Tasks from AWS API
AWS + Python
 
Try it
Run Python Code with Python API on New SNS Messages from AWS API
AWS + Python
 
Try it
Run Python Code with Python API on New Inbound SES Emails from AWS API
AWS + Python
 
Try it
Run Python Code with Python API on New Deleted S3 File from AWS API
AWS + Python
 
Try it
Run Python Code with Python API on New DynamoDB Stream Event from AWS API
AWS + Python
 
Try it
New Scheduled Tasks from the AWS API

Creates a Step Function State Machine to publish a message to an SNS topic at a specific timestamp. The SNS topic delivers the message to this Pipedream source, and the source emits it as a new event.

 
Try it
New SNS Messages from the AWS API

Creates an SNS topic in your AWS account. Messages published to this topic are emitted from the Pipedream source.

 
Try it
New Inbound SES Emails from the AWS API

The source subscribes to all emails delivered to a specific domain configured in AWS SES. When an email is sent to any address at the domain, this event source emits that email as a formatted event. These events can trigger a Pipedream workflow and can be consumed via SSE or REST API.

 
Try it
New Deleted S3 File from the AWS API

Emit new event when a file is deleted from a S3 bucket

 
Try it
New DynamoDB Stream Event from the AWS API

Emit new event when a DynamoDB stream receives new events. See the docs here

 
Try it
Run Python Code with the Python API

Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.

 
Try it
CloudWatch Logs - Put Log Event with the AWS API

Uploads a log event to the specified log stream. See docs

 
Try it
DynamoDB - Create Table with the AWS API

Creates a new table to your account. See docs

 
Try it
DynamoDB - Execute Statement with the AWS API

This operation allows you to perform transactional reads or writes on data stored in DynamoDB, using PartiQL. See docs

 
Try it
DynamoDB - Get Item with the AWS API

The Get Item operation returns a set of attributes for the item with the given primary key. If there is no matching item, Get Item does not return any data and there will be no Item element in the response. See docs

 
Try it

Overview of AWS

The AWS API unlocks endless possibilities for automation with Pipedream. With this powerful combo, you can manage your AWS services and resources, automate deployment workflows, process data, and react to events across your AWS infrastructure. Pipedream offers a serverless platform for creating workflows triggered by various events that can execute AWS SDK functions, making it an efficient tool to integrate, automate, and orchestrate tasks across AWS services and other apps.

Connect AWS

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
import AWS from 'aws-sdk'

export default defineComponent({
  props: {
    aws: {
      type: "app",
      app: "aws",
    }
  },
  async run({steps, $}) {
    const { accessKeyId, secretAccessKey } = this.aws.$auth
    
    /* Now, pass the accessKeyId and secretAccessKey to the constructor for your desired service. For example:
    
    const dynamodb = new AWS.DynamoDB({
      accessKeyId, 
      secretAccessKey,
      region: 'us-east-1',
    })
    
    */
  },
})

Overview of Python

Develop, run and deploy your Python code in Pipedream workflows. Integrate seamlessly between no-code steps, with connected accounts, or integrate Data Stores and manipulate files within a workflow.

This includes installing PyPI packages, within your code without having to manage a requirements.txt file or running pip.

Below is an example of using Python to access data from the trigger of the workflow, and sharing it with subsequent workflow steps:

Connect Python

1
2
3
4
5
def handler(pd: "pipedream"):
  # Reference data from previous steps
  print(pd.steps["trigger"]["context"]["id"])
  # Return data for use in future steps
  return {"foo": {"test":True}}