Registry /
type-stubs / mypy-boto3-frauddetector
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
muslpy 3.10–3.95 runs
installs and imports cleanly · install 0.0s · import 0.624s · 52MB
glibcpy 3.10–3.95 runs
installs and imports cleanly · install 3.9s · import 0.602s · 53MB
50MB installed
● package 50MB
Code
Verified usage
Verified import paths — ran on the pinned version, not inferred.
FraudDetectorClient
✓ from mypy_boto3_frauddetector import FraudDetectorClient
AsyncJobStatusType
✓ from mypy_boto3_frauddetector.literals import AsyncJobStatusType
For literal types like enum values.
ATIMetricDataPointTypeDef
✓ from mypy_boto3_frauddetector.type_defs import ATIMetricDataPointTypeDef
For TypedDicts representing service request/response structures.
This example demonstrates how to initialize a FraudDetector client with explicit type annotations and make a simple API call (`get_event_types`). The `TYPE_CHECKING` guard ensures the type stub package is only imported for static analysis, avoiding a runtime dependency. Replace `DUMMY_KEY` and `DUMMY_SECRET` with actual credentials or ensure standard AWS credential providers are configured.
import os
from typing import TYPE_CHECKING
from boto3.session import Session
# Only import type stubs during type checking
if TYPE_CHECKING:
from mypy_boto3_frauddetector import FraudDetectorClient
from mypy_boto3_frauddetector.type_defs import GetEventTypesResultTypeDef
# Instantiate a boto3 session (credentials are handled by boto3's default chain)
session = Session(
aws_access_key_id=os.environ.get('AWS_ACCESS_KEY_ID', 'DUMMY_KEY'),
aws_secret_access_key=os.environ.get('AWS_SECRET_ACCESS_KEY', 'DUMMY_SECRET'),
region_name=os.environ.get('AWS_DEFAULT_REGION', 'us-east-1')
)
# Get the FraudDetector client with type annotations
client: 'FraudDetectorClient' = session.client("frauddetector")
try:
# Example API call with type-hinted response
response: 'GetEventTypesResultTypeDef' = client.get_event_types()
print("Successfully retrieved FraudDetector event types.")
for event_type in response.get('EventTypes', []):
print(f" - Event Type: {event_type.get('Name')}")
except Exception as e:
print(f"Error retrieving FraudDetector event types: {e}")
Debug
Known issues
breaking`mypy-boto3-builder` 8.12.0 and later versions removed support for Python 3.8 across all generated packages. This package (1.42.3) requires Python 3.9 or newer.fixUpgrade your Python environment to version 3.9 or later.
affects: mypy-boto3-builder >= 8.12.0
breakingStarting with `mypy-boto3-builder` 8.9.0, TypedDict names for method arguments may have changed (e.g., `CreateDistributionRequestRequestTypeDef` -> `CreateDistributionRequestTypeDef`). Additionally, conflicting `Extra` postfixes were moved (`CreateDistributionExtraRequestTypeDef` -> `CreateDistributionRequestExtraTypeDef`).fixUpdate your TypedDict imports and usage to reflect the new naming conventions, consulting the service's documentation if necessary.
affects: mypy-boto3-builder >= 8.9.0
gotchaWhen using `if TYPE_CHECKING:` to prevent runtime stub imports, Pylint might report 'undefined variable' errors for the type-hinted objects.fixTo fix this, assign `object` to the type-hinted variables in the `else` branch: `if TYPE_CHECKING: from mypy_boto3_frauddetector import FraudDetectorClient else: FraudDetectorClient = object`.
affects: All versions
gotchaPyCharm has known performance issues with `Literal` overloads (issue PY-40997) when using full `mypy-boto3-*` packages.fixIf experiencing performance problems in PyCharm, consider installing the `boto3-stubs-lite` version (e.g., `pip install 'boto3-stubs-lite[frauddetector]'`) which is more RAM-friendly but requires explicit type annotations for session clients/resources.
affects: All versions with PyCharm
gotchaWhile `boto3-stubs` often auto-discovers types for `session.client()` or `boto3.client()`, explicit type annotations for the client object (e.g., `client: FraudDetectorClient = ...`) are highly recommended for optimal IDE auto-completion and strict type checking, especially with `boto3-stubs-lite` variants.fixAlways add explicit type annotations for `boto3` client and resource objects.
affects: All versions
Upgrade
Version history
1.43.0latest on PyPI · released Apr 29, 2026
Audit
Dependencies
boto3requiredRuntime dependency for the AWS SDK for Python.
typing-extensionsoptionalRequired for older Python versions (e.g., <3.11) to support advanced typing features if used in generated stubs.