types-pyyaml

library6.0.12.20260815pypypi✓ verified 26d ago

This package provides static type annotations (stubs) for the PyYAML library. PyYAML is a full-featured YAML parser and emitter for Python, enabling seamless interaction with YAML data for configurations and structured data. Types-PyYAML allows static type checkers like mypy and pyright to analyze code using PyYAML, improving code quality and catching potential type errors before runtime. This package is part of the typeshed project and aims to provide accurate annotations for PyYAML versions 6.0.*.

type-stubs

pip install types-PyYAML

github ↗package ↗changelog ↗

INSTALL

IMPORT

SIG · TYPES-PYYAML

types-pyyaml

type-stubspythonv6.0.12.20260815

Install

2.6s avg

Import

—

Disk

82MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v6.0.12.20260815 · 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 3.10–3.910 runs

installs and imports cleanly · install 0.0s · import 0.000s · 85MB

glibc

py 3.10–3.910 runs

installs and imports cleanly · install 2.6s · import 0.000s · 83MB

82MB installed

● package 82MB

Code

Verified usage

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

yaml

✓ import yaml-stubs

✗ import yaml

This quickstart demonstrates how `types-PyYAML` enables static type checking for `PyYAML` code using `mypy`. After installing `PyYAML`, `types-PyYAML`, and `mypy`, save the code to `app.py` and run `mypy app.py`. Mypy will detect the deliberate type error where an integer is assigned to a key expected to hold a string, thanks to the type information provided by `types-PyYAML`.

import yaml from typing import Any def process_config(config_str: str) -> dict[str, Any]: data: dict[str, Any] = yaml.safe_load(config_str) # Introduce a deliberate type error for demonstration # 'name' is expected to be a string, but we assign a number # mypy should flag this if types-PyYAML is correctly used. if 'name' in data: # type: ignore[reportUntypedBaseMembers] data['name'] = 123 # Intentionally wrong type for demo return data config_data = """ name: Alice age: 30 """ # This would normally be executed, but the focus is on static analysis # processed_data = process_config(config_data) # print(processed_data) # To run mypy and see the type error: # 1. pip install PyYAML types-PyYAML mypy # 2. Save this code as `app.py` # 3. Run: `mypy app.py` # Expected output should include a type error about data['name'] assignment.

Debug

Known issues

breakingUpdates to type stubs, even without changes to your runtime code, can introduce new type-checking errors. This is because typeshed aims to improve the accuracy of type annotations, which might expose previously unflagged type inconsistencies in your codebase.

fix

Consider pinning your `types-PyYAML` version in your `requirements.txt` (e.g., `types-PyYAML==6.0.12.20250915`) and regularly testing updates. You can also temporarily ignore specific errors using `type: ignore` comments if a stub change is overly strict or controversial, while contributing fixes to typeshed.

affects: All versions

gotchaWhen attempting to use the C-accelerated `CLoader` or `CDumper` from PyYAML with a fallback to pure Python `Loader`/`Dumper`, type checkers like mypy can report `Incompatible import` errors. This happens because `CLoader` and `Loader` are distinct types, even though they often serve a similar purpose.

fix

If strict type checking is desired, you may need to use `typing.cast` or `type: ignore` to suppress these specific errors. Alternatively, structure your code to use a single `Loader`/`Dumper` definition to avoid type checker confusion, or refactor to reduce direct exposure of the `Loader` type.

affects: All versions

gotchaPyYAML (and thus its stubs) is based on the older YAML 1.1 specification. This can lead to unexpected implicit type conversions (e.g., 'yes', 'no' become booleans; '010' becomes an octal integer; `59:59` interpreted as seconds) compared to the stricter YAML 1.2 specification common in other parsers. The stubs accurately reflect these 1.1 behaviors.

fix

Be aware of YAML 1.1's implicit typing rules when writing or consuming YAML files with PyYAML. For stricter YAML 1.2 compliance, consider alternative libraries like `ruamel.yaml` if the `types-PyYAML` stubs' accuracy for PyYAML's behavior is undesirable for your use case.

affects: All versions

gotchaThe versioning of `types-PyYAML` is independent of `PyYAML` itself, though the stubs target specific `PyYAML` versions (e.g., `types-PyYAML 6.0.x.YYYYMMDD` targets `PyYAML==6.0.*`). This means updating one does not automatically update the other, and an older stub version might not fully cover a newer PyYAML, or vice versa.

fix

It is recommended to explicitly install both `PyYAML` and `types-PyYAML` and to regularly update both, while ensuring their compatibility. Typeshed recommends either using the same version bounds for stubs as for the package or pinning the stubs to a known good version.

affects: All versions

Upgrade

Version history

6.0.12.20260815latest on PyPI · released Aug 15, 2026

Audit

Dependencies

PyYAMLrequiredThis package provides type stubs for PyYAML; PyYAML itself is required at runtime for any functionality.

pythonrequiredRequires Python 3.9 or newer.

Agent activity

46 hits · last 30 days

node

OpenAI (training)

Resources

githubhttps://github.com/typeshed-internal/stub_uploader ↗

packagehttps://pypi.org/project/types-pyyaml/ ↗

changeloghttps://github.com/typeshed-internal/stub_uploader/blob/main/data/changelogs/PyYAML.md ↗