Mypy Boto3 Timestream Write Stubs

Warnings

• breaking Python 3.8 support has been removed for all `mypy-boto3` packages with `mypy-boto3-builder` version 8.12.0. Users on Python 3.8 should update to Python 3.9 or newer.
  Fix: Upgrade your Python environment to 3.9 or higher.
• breaking All `mypy-boto3` packages, including `mypy-boto3-timestream-write`, migrated to PEP 561-compliant packaging with `mypy-boto3-builder` version 8.12.0. This changes how type checkers locate stubs. While usually seamless with `pip`, ensure your build tools and environments correctly discover PEP 561 packages.
  Fix: Ensure your environment and type checker (e.g., `mypy`, `pyright`) are up-to-date and configured to find PEP 561 stub packages in your `site-packages`.
• breaking Some `TypeDef` names were shortened (e.g., `CreateDistributionRequestRequestTypeDef` became `CreateDistributionRequestTypeDef`) and conflicting `Extra` postfixes moved with `mypy-boto3-builder` version 8.9.0. If you explicitly import `TypeDef`s, these changes may break your code.
  Fix: Review and update `TypeDef` import paths and names in your codebase according to the latest documentation or the generated stub files.
• gotcha This package provides *only* type annotations for `boto3` and `botocore`. It does not include `boto3` itself, which must be installed separately for your code to run at runtime.
  Fix: Always ensure you have `boto3` installed (`pip install boto3`) in addition to `mypy-boto3-timestream-write`.
• gotcha For optimal type checking and IDE autocompletion, especially in VSCode and PyCharm, it is highly recommended to explicitly annotate the type of `boto3.client()` calls (e.g., `client: TimestreamWriteClient = boto3.client(...)`). While some IDEs offer implicit type discovery, explicit annotations provide the most consistent experience.
  Fix: Add explicit type annotations for `boto3` clients and resources (e.g., `client: TimestreamWriteClient = boto3.client("timestream-write")`).
• gotcha PyCharm users might experience slow performance or high CPU usage due to how it handles `Literal` overloads in `mypy-boto3` packages. Using `boto3-stubs-lite` (if available for the service) or disabling PyCharm's internal type checker in favor of `mypy` or `pyright` is often recommended as a workaround.
  Fix: Consider `pip install boto3-stubs-lite[timestream-write]` (if available) or configure PyCharm to use external type checkers like `mypy` or `pyright`.

Install

• pip install mypy-boto3-timestream-write boto3 Install with pip

Imports

• TimestreamWriteClient

  from mypy_boto3_timestream_write.client import TimestreamWriteClient

• WriteRecordsRequestRequestTypeDef

  from mypy_boto3_timestream_write.type_defs import WriteRecordsRequestRequestTypeDef

  Example TypedDict for request parameters.
• RecordsOutputTypeDef

  from mypy_boto3_timestream_write.type_defs import RecordsOutputTypeDef

  Example TypedDict for response output.

Quickstart

This quickstart demonstrates how to initialize a `boto3` client with `mypy-boto3-timestream-write` type annotations and make a basic API call like `describe_endpoints`. It also shows how to import and use generated `TypedDict` definitions. Remember to install `boto3` alongside the stub package.

import boto3
import os
from typing import TYPE_CHECKING

if TYPE_CHECKING:
    from mypy_boto3_timestream_write.client import TimestreamWriteClient
    from mypy_boto3_timestream_write.type_defs import DescribeEndpointsResponseTypeDef

# It's recommended to install boto3 in addition to mypy-boto3-timestream-write
# pip install boto3 mypy-boto3-timestream-write

# Initialize a boto3 client with explicit type annotation
# This helps IDEs and type checkers provide accurate suggestions
client: TimestreamWriteClient = boto3.client(
    "timestream-write",
    region_name=os.environ.get('AWS_REGION', 'us-east-1'),
    aws_access_key_id=os.environ.get('AWS_ACCESS_KEY_ID', 'YOUR_ACCESS_KEY'),
    aws_secret_access_key=os.environ.get('AWS_SECRET_ACCESS_KEY', 'YOUR_SECRET_KEY')
)

try:
    # Use a simple method to demonstrate type checking
    response: DescribeEndpointsResponseTypeDef = client.describe_endpoints()
    print("Timestream Write Endpoints:")
    for endpoint in response.get('Endpoints', []):
        print(f"  Address: {endpoint.get('Address')}, CachePeriodInMinutes: {endpoint.get('CachePeriodInMinutes')}")
except Exception as e:
    print(f"Error describing endpoints: {e}")

# Example of using a TypedDict
# from mypy_boto3_timestream_write.type_defs import WriteRecordsRequestRequestTypeDef
# write_request: WriteRecordsRequestRequestTypeDef = {
#     "DatabaseName": "my_database",
#     "TableName": "my_table",
#     "Records": [
#         {
#             "MeasureName": "cpu_utilization",
#             "MeasureValue": "10.5",
#             "MeasureValueType": "DOUBLE",
#             "Time": "1678886400000",
#             "TimeUnit": "MILLISECONDS"
#         }
#     ]
# }
# print(f"\nSample WriteRecordsRequestRequestTypeDef: {write_request}")