Type annotations for boto3 Batch

Warnings

• breaking Support for Python 3.8 has been removed across all `mypy-boto3-*` packages, starting with `mypy-boto3-builder` version 8.12.0.
  Fix: Upgrade your Python environment to 3.9 or newer.
• breaking TypeDef naming conventions were changed, potentially affecting custom code that directly imports and uses generated TypeDefs. For instance, `CreateDistributionRequestRequestTypeDef` might become `CreateDistributionRequestTypeDef`, and `Extra` postfixes are moved to the end.
  Fix: Review your code for direct `TypeDef` imports and adjust names according to the updated conventions. Refer to the `mypy-boto3-builder` changelog for specific renaming patterns.
• gotcha When using PyCharm, performance issues with `Literal` overloads have been reported (issue PY-40997). This may lead to slow performance and high CPU usage.
  Fix: Consider using `boto3-stubs-lite` (if available for Batch), disabling PyCharm's internal type checker in favor of MyPy or Pyright, or relying on explicit type annotations rather than full overload inference. Install `mypy` or `pyright` and configure PyCharm to use them.
• gotcha For optimal IDE autocompletion and type checking, especially in VSCode without Pylance, explicit type annotations for `boto3.client()` calls are recommended, even if `boto3-stubs` provides some implicit type discovery.
  Fix: Always add explicit type hints like `client: BatchClient = boto3.client('batch')` to leverage the full power of the stubs.
• gotcha To avoid `mypy-boto3-batch` becoming a production dependency and to prevent `pylint` complaints about undefined variables when the stub package is not installed in production, it is recommended to wrap stub imports within a `if TYPE_CHECKING:` block.
  Fix: Enclose all `mypy_boto3_batch` imports within `from typing import TYPE_CHECKING; if TYPE_CHECKING: ...` blocks. For runtime use, fallback to `object` or remove type hints.

Install

• pip install boto3 mypy-boto3-batch Install with pip
• pip install 'boto3-stubs[batch]' Install via boto3-stubs extras

Imports

• BatchClient

  from mypy_boto3_batch.client import BatchClient

  For explicit type annotations of the boto3 Batch client.
• BatchServiceResource

  from mypy_boto3_batch.service_resource import BatchServiceResource

  For explicit type annotations of the boto3 Batch service resource (if applicable).
• ArrayJobDependencyType

  from mypy_boto3_batch.literals import ArrayJobDependencyType

  For type-hinting literal values used in Batch API calls.
• ArrayPropertiesDetailTypeDef

  from mypy_boto3_batch.type_defs import ArrayPropertiesDetailTypeDef

  For type-hinting dictionary structures (TypedDicts) used in Batch API calls.

Quickstart

This quickstart demonstrates how to obtain a type-hinted Batch client and perform basic operations like describing job queues and listing jobs using a paginator. The `TYPE_CHECKING` block ensures that `mypy-boto3-batch` is only a development dependency. Remember that `boto3` itself needs to be configured with AWS credentials to make actual API calls.

import boto3
from typing import TYPE_CHECKING

if TYPE_CHECKING:
    from mypy_boto3_batch.client import BatchClient
    from mypy_boto3_batch.type_defs import DescribeJobQueuesResponseTypeDef

    # Example of a Paginator import
    from mypy_boto3_batch.paginators import ListJobsPaginator


def get_batch_client() -> 'BatchClient':
    """Returns a type-hinted boto3 Batch client."""
    return boto3.client("batch")


def describe_queues() -> 'DescribeJobQueuesResponseTypeDef':
    """Describes Batch job queues with type hints."""
    client: BatchClient = get_batch_client()
    response = client.describe_job_queues()
    print(f"Job Queues: {len(response['jobQueues'])}")
    return response


def list_all_jobs():
    """Lists all jobs using a paginator with type hints."""
    client: BatchClient = get_batch_client()
    paginator: ListJobsPaginator = client.get_paginator('list_jobs')
    for page in paginator.paginate(jobQueue='example-queue'): # Replace 'example-queue' with an actual queue
        for job in page.get('jobSummaryList', []):
            print(f"Job ID: {job['jobId']}, Name: {job['jobName']}")

# Example usage (requires AWS credentials and an existing Batch setup)
if __name__ == '__main__':
    # This code will execute if you have AWS credentials configured
    # and an AWS Batch environment. For type checking, no actual AWS call is needed.
    # To run this, ensure boto3 is configured, e.g., via AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_REGION
    # Or by using 'aws configure'
    try:
        queues_response = describe_queues()
        # You can add more complex logic here
        # list_all_jobs() # Uncomment to test paginator, requires a valid jobQueue
    except Exception as e:
        print(f"Error interacting with AWS Batch (this is expected if AWS credentials/resources are not set up): {e}")