How to use Boto3 to paginate through all triggers present in AWS Glue

Problem Statement: Use boto3 library in Python to paginate through all triggers from AWS Glue Data Catalog that is created in your account

Approach/Algorithm to solve this problem

• Step 1: Import boto3 and botocore exceptions to handle exceptions.

• Step 2: max_items, page_size and starting_token are the optional parameters for this function

  • max_items denote the total number of records to return. If the number of available records > max_items, then a NextToken will be provided in the response to resume pagination.

  • page_size denotes the size of each page.

  • starting_token helps to paginate, and it uses NextToken from a previous response.

• Step 3: Create an AWS session using boto3 lib. Make sure region_name is mentioned in the default profile. If it is not mentioned, then explicitly pass the region_name while creating the session.

• Step 4: Create an AWS client for glue.

• Step 5: Create a paginator object that contains details of all triggers using get_triggers

• Step 6: Call the paginate function and pass the max_items, page_size and starting_token as PaginationConfig parameter

• Step 7: It returns the number of records based on max_size and page_size.

• Step 8: Handle the generic exception if something went wrong while paginating.

Example Code

Use the following code to paginate through all triggers created in user account ?

import boto3
from botocore.exceptions import ClientError

def paginate_through_triggers(max_items=None, page_size=None, starting_token=None):
    session = boto3.session.Session()
    glue_client = session.client('glue')
    try:
        paginator = glue_client.get_paginator('get_triggers')
        response = paginator.paginate(PaginationConfig={
            'MaxItems': max_items,
            'PageSize': page_size,
            'StartingToken': starting_token
        })
        return response
    except ClientError as e:
        raise Exception("boto3 client error in paginate_through_triggers: " + e.__str__())
    except Exception as e:
        raise Exception("Unexpected error in paginate_through_triggers: " + e.__str__())

# Example usage with pagination parameters
page_iterator = paginate_through_triggers(max_items=10, page_size=2)
for page in page_iterator:
    print(page['Triggers'])

Basic Usage Without Pagination Parameters

You can also call the function without any parameters to get all triggers ?

import boto3
from botocore.exceptions import ClientError

# Simple function to get all triggers without pagination limits
def get_all_triggers():
    session = boto3.session.Session()
    glue_client = session.client('glue')
    
    try:
        paginator = glue_client.get_paginator('get_triggers')
        response = paginator.paginate()
        
        all_triggers = []
        for page in response:
            all_triggers.extend(page['Triggers'])
        
        return all_triggers
    except ClientError as e:
        raise Exception("boto3 client error: " + str(e))

# Get all triggers
triggers = get_all_triggers()
print(f"Total triggers found: {len(triggers)}")
for trigger in triggers:
    print(f"Trigger Name: {trigger['Name']}, State: {trigger['State']}")

Parameters

Output

[{'Name': 'file-passed', 'WorkflowName': 'data-tx', 'Type': 'CONDITIONAL', 'State': 'ACTIVATED', 'Actions': [{'JobName': 'data-event'}], 'Predicate': {'Logical': 'ANY', 'Conditions': [{'LogicalOperator': 'EQUALS', 'JobName': 'data-worker', 'State': 'SUCCEEDED'}]}},
{'Name': 'file-passed-to-acc', 'WorkflowName': 'tick-data', 'Type': 'CONDITIONAL', 'State': 'ACTIVATED', 'Actions': [{'JobName': 'tick-data'}], 'Predicate': {'Logical': 'ANY', 'Conditions': [{'LogicalOperator': 'EQUALS', 'JobName': 'tick-data', 'State': 'SUCCEEDED'}]}}]

Conclusion

Use boto3's paginator for efficient handling of large trigger datasets in AWS Glue. The PaginationConfig parameters help control memory usage and API call limits when working with numerous triggers.