mypy-boto3-pricing Type Stubs

1.42.82 · active · verified Sat Apr 11

mypy-boto3-pricing provides static type annotations for the `boto3` AWS Pricing service, enhancing development with type checking and IDE autocompletion. It is currently at version 1.42.82, aligning with its corresponding `boto3` version. This package is part of the `mypy-boto3` ecosystem, which automatically generates and releases stubs for all `boto3` services in sync with upstream AWS SDK updates.

Warnings

breaking Version 8.12.0 of `mypy-boto3-builder` (which generates these stubs) removed support for Python 3.8 across all `mypy-boto3` packages. Projects targeting Python 3.8 must use an older version of `mypy-boto3-pricing` or upgrade to Python 3.9 or newer. [cite: 8.12.0 release notes]
Fix: Upgrade your project's Python version to 3.9 or higher, or pin `mypy-boto3-pricing` to an older version compatible with Python 3.8.
breaking Breaking changes in TypeDef naming conventions were introduced in `mypy-boto3-builder` 8.9.0. Some TypeDefs for method arguments now use shorter names (e.g., `CreateDistributionRequestRequestTypeDef` became `CreateDistributionRequestTypeDef`), and conflicting TypeDef `Extra` postfixes were moved (e.g., `CreateDistributionExtraRequestTypeDef` to `CreateDistributionRequestExtraTypeDef`). If you explicitly reference these TypeDef names, your code may break. [cite: 8.9.0 release notes, 3]
Fix: Update your code to use the new TypeDef names. Consult the specific service's documentation or generated stub files for the correct names.
gotcha PyCharm users might experience slow performance and high CPU usage due to `Literal` overloads. It is recommended to use `boto3-stubs-lite` (if available for the service) or disable PyCharm's internal type checker and rely on external tools like `mypy` or `pyright`.
Fix: Consider `pip install boto3-stubs-lite[pricing]` or configure PyCharm to use `mypy` or `pyright` for type checking, disabling its native checker for improved performance.
gotcha While `mypy` and PyCharm often infer types correctly, VSCode users may need to provide explicit type annotations for `boto3.client`, `boto3.session.client`, `client.get_waiter`, and `client.get_paginator` calls to ensure full code autocompletion and correct type hints.
Fix: Add explicit type annotations, for example: `client: PricingClient = session.client("pricing")`.
gotcha When using `typing.TYPE_CHECKING` to conditionally import type stubs and avoid production dependencies, Pylint may report 'undefined variable' errors for the type-annotated objects in the runtime block.
Fix: In the `else` block (for runtime), assign `object` to the type-annotated variables, e.g., `else: PricingClient = object`.

Install

pip install mypy-boto3-pricing boto3 Install with pip

Imports

PricingClient
```
from mypy_boto3_pricing import PricingClient
```
Used for explicit type annotation of the boto3 Pricing client.
DescribeServicesPaginator
```
from mypy_boto3_pricing.paginator import DescribeServicesPaginator
```
For explicit type annotation of paginators.
AttributeValueTypeDef
```
from mypy_boto3_pricing.type_defs import AttributeValueTypeDef
```
For explicit type annotation of service-specific TypedDicts.

Quickstart

This quickstart demonstrates how to initialize a `boto3` Pricing client with type annotations using `mypy-boto3-pricing`. The `TYPE_CHECKING` block allows type checkers to validate your code while avoiding runtime dependencies on `mypy-boto3-pricing` in production. It then calls `get_products` to retrieve pricing information for Amazon EC2 instances running Linux.

import boto3
from typing import TYPE_CHECKING

if TYPE_CHECKING:
    from mypy_boto3_pricing import PricingClient
    from mypy_boto3_pricing.type_defs import GetProductsOutputTypeDef

    client: PricingClient = boto3.client("pricing")

    response: GetProductsOutputTypeDef = client.get_products(
        ServiceCode="AmazonEC2",
        Filters=[
            {"Type": "TERM_MATCH", "Field": "operatingSystem", "Value": "Linux"}
        ],
    )

    for price_list in response.get("PriceList", []):
        print(price_list)

else:
    client = boto3.client("pricing")
    # In a non-type-checking environment, type annotations are stripped.
    # The actual boto3 client is used directly.
    response = client.get_products(
        ServiceCode="AmazonEC2",
        Filters=[
            {"Type": "TERM_MATCH", "Field": "operatingSystem", "Value": "Linux"}
        ],
    )
    for price_list in response.get("PriceList", []):
        print(price_list)

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