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mypy-boto3-fis

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library1.43.0pypypi✓ verified 23d ago

mypy-boto3-fis provides comprehensive type annotations for the AWS FIS (Fault Injection Service) client in boto3. It is part of the `boto3-stubs` ecosystem, actively generated and maintained by `mypy-boto3-builder` (version 8.12.0), with frequent releases that align with boto3 updates to ensure up-to-date type checking capabilities for Python >=3.9.

pip install mypy-boto3-fis
INSTALL
IMPORT
SIG · MYPY-BOTO3-FIS
M
mypy-boto3-fis
type-stubspythonv1.43.0
Install
3.3s avg
Import
Disk
18MB
Pass rate
10/ 10
Env Coverage10 / 10
glibc
3.93.13
musl
3.93.13
Install & Compatibility
Where this runs
tested against v1.43.0 · pip install
no network on importno background threads
Install × environment matrix
Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux
musl
py 3.103.910 runs
installs and imports cleanly · install 0.0s · import 0.000s · 19.8MB
glibc
py 3.103.910 runs
installs and imports cleanly · install 3.3s · import 0.000s · 20MB
18MB installed
● package 18MB
Code
Verified usage

Verified import paths — ran on the pinned version, not inferred.

FISClient
from mypy_boto3_fis import FISClient
from mypy_boto3_fis import FISClient
Client
from mypy_boto3_fis import Client
from mypy_boto3_fis import FISClient
FISServiceResource
from mypy_boto3_fis import FISServiceResource
from mypy_boto3_fis import FISClient

This quickstart demonstrates how to obtain a type-hinted FIS client and use it to list experiments. Explicitly annotating the client type (`client: FISClient`) is often recommended for better IDE support and static analysis. It also shows importing and using a TypedDict for the response structure. The `TYPE_CHECKING` block ensures that stub imports are only used during type checking.

import boto3 from typing import TYPE_CHECKING if TYPE_CHECKING: from mypy_boto3_fis import FISClient from mypy_boto3_fis.type_defs import ListExperimentsOutputTypeDef # Example of a TypedDict for a specific request parameter from mypy_boto3_fis.type_defs import ExperimentTemplateSummaryTypeDef def list_fis_experiments() -> list['ExperimentTemplateSummaryTypeDef']: client: FISClient = boto3.client('fis') response: ListExperimentsOutputTypeDef = client.list_experiments() return response.get('experimentSummaries', []) # Example usage (will not be type-checked at runtime by mypy-boto3-fis) if __name__ == "__main__": try: experiments = list_fis_experiments() print(f"Found {len(experiments)} FIS experiments.") for experiment in experiments: print(f" - {experiment.get('id')}: {experiment.get('state', {}).get('status')}") except Exception as e: print(f"Error listing FIS experiments: {e}")
Debug
Known issues
breakingSupport for Python 3.8 was removed in `mypy-boto3-builder` version 8.12.0, affecting all generated `mypy-boto3-*` packages. Ensure your projects use Python 3.9 or higher.
fix
Upgrade your Python environment to 3.9 or newer.
affects: >=8.12.0 of mypy-boto3-builder (corresponding mypy-boto3-fis versions)
breakingTypeDef naming conventions changed in `mypy-boto3-builder` 8.9.0. Specifically, redundant `Request` postfixes were removed (e.g., `CreateDistributionRequestRequestTypeDef` became `CreateDistributionRequestTypeDef`), and `Extra` postfixes moved to the end of the name. This impacts imports and usage of generated TypeDefs.
fix
Review your imports and usage of `TypeDef` objects and update their names according to the new conventions.
affects: >=8.9.0 of mypy-boto3-builder (corresponding mypy-boto3-fis versions)
gotchaFor optimal IDE autocomplete and `mypy` checks, explicitly type-annotate `boto3.client()` and `boto3.session.client()` calls with the imported client type (e.g., `client: FISClient = boto3.client('fis')`). While `mypy` often auto-discovers types, explicit hints provide the best experience across all tools.
fix
Add explicit type annotations when initializing boto3 clients, resources, paginators, and waiters.
affects: All
gotchaThe `mypy-boto3-fis` package provides type stubs, but `mypy` itself (the static type checker) is not a dependency and must be installed and configured separately in your project.
fix
Install `mypy` (`pip install mypy`) and configure it (e.g., via `pyproject.toml` or `mypy.ini`) in your project.
affects: All
gotchaWhen integrating with tools like Pylint, it's recommended to guard stub imports using `if TYPE_CHECKING:` to avoid runtime dependencies in production, as Pylint might otherwise complain about undefined variables if the stubs are not present at runtime.
fix
Wrap type stub imports within `if TYPE_CHECKING:` blocks and provide fallback `object` assignments for runtime compatibility.
affects: All
gotchaPyCharm has known performance issues with `Literal` overloads. If you experience slow performance, consider using the `boto3-stubs-lite` version (e.g., `pip install 'boto3-stubs-lite[fis]'`), which is more RAM-friendly but requires more explicit type annotations.
fix
For PyCharm users, consider `boto3-stubs-lite` if performance is an issue, or ensure you are on the latest PyCharm and Python versions for potential improvements.
affects: All
Upgrade
Version history
1.43.0latest on PyPI · released Apr 29, 2026
Audit
Dependencies
boto3requiredProvides the AWS SDK for Python that these stubs type-check.
mypyoptionalThe static type checker that utilizes these annotations; not a runtime dependency of the stubs themselves.
Agent activity
18 hits · last 30 days
node
16
OpenAI (training)
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Resources
mypy-boto3-fis — pip install mypy-boto3-fis · libregistry