Type Annotations for aiobotocore EC2

Warnings

• breaking Support for Python 3.8 has been removed in `mypy-boto3-builder` version 8.12.0 and subsequent generated packages. Users on Python 3.8 must either upgrade Python or use an older version of `types-aiobotocore-ec2`.
  Fix: Upgrade your Python environment to 3.9 or newer.
• breaking Generated TypeDef naming conventions may have changed in `mypy-boto3-builder` version 8.9.0. For instance, `CreateDistributionRequestRequestTypeDef` might become `CreateDistributionRequestTypeDef`. Code relying on specific TypeDef names may break.
  Fix: Review your type hints and update TypeDef names according to the latest generated types if you experience `NameError` or type resolution issues.
• gotcha Installing `types-aiobotocore-ec2` only provides type annotations. For actual runtime execution, you must also install the `aiobotocore` library itself (`pip install aiobotocore`).
  Fix: Ensure both `aiobotocore` and `types-aiobotocore-ec2` are installed in your environment.
• gotcha When using standalone service packages like `types-aiobotocore-ec2` or `types-aiobotocore-lite`, explicit type annotations (e.g., `client: EC2Client`) are often required for full type checking and IDE support. The main `types-aiobotocore` package with overloads can sometimes infer types implicitly.
  Fix: Add explicit type annotations for clients, resources, paginators, and waiters imported from `types_aiobotocore_ec2`.
• gotcha PyCharm users might experience slow performance or high CPU usage due to the large number of `Literal` overloads in these stub packages (related to PyCharm issue PY-40997).
  Fix: Consider using the `-lite` version of the stubs (`types-aiobotocore-lite-ec2` if available) or disable PyCharm's internal type checker and rely on external tools like MyPy or Pyright instead.

Install

• pip install types-aiobotocore-ec2 Install standalone package
• pip install 'types-aiobotocore[ec2]' Install as part of 'types-aiobotocore' umbrella package

Imports

• EC2Client

  from types_aiobotocore_ec2.client import EC2Client

• DescribeInstancesResultTypeDef

  from types_aiobotocore_ec2.type_defs import DescribeInstancesResultTypeDef

• EC2ServiceResource

  from types_aiobotocore_ec2.service_resource import EC2ServiceResource

Quickstart

This example demonstrates how to set up an `aiobotocore` client for EC2 and apply type annotations using `types-aiobotocore-ec2`. It explicitly types the client and shows how to leverage TypeDefs for response objects, enabling better static analysis and IDE autocompletion for asynchronous AWS calls.

import asyncio
from aiobotocore.session import get_session
from typing import TYPE_CHECKING

if TYPE_CHECKING:
    from types_aiobotocore_ec2.client import EC2Client
    from types_aiobotocore_ec2.type_defs import DescribeInstancesResultTypeDef

async def describe_ec2_instances():
    session = get_session()
    async with session.create_client("ec2") as client:
        # Explicit type annotation for the client
        client: "EC2Client" = client
        response = await client.describe_instances()
        
        print(f"Found {len(response['Reservations'])} reservations.")
        for reservation in response['Reservations']:
            for instance in reservation['Instances']:
                print(f"  Instance ID: {instance['InstanceId']}, State: {instance['State']['Name']}")
        
        # Example of using a TypeDef for a dictionary structure
        example_type_def: "DescribeInstancesResultTypeDef" = response
        print(f"Example TypeDef Reservations key: {example_type_def['Reservations'][0]['ReservationId']}")

if __name__ == "__main__":
    asyncio.run(describe_ec2_instances())