Syrupy is a pytest plugin for snapshot testing that captures the state of code output at a specific point in time and compares it against future runs to ensure stability.

What are the requirements for using Syrupy?

Syrupy requires Python 3.10 or higher and pytest version 8 or later to function correctly.

Does this skill support JSON API testing?

Absolutely. Syrupy includes a specialized JSONSnapshotExtension that stores snapshots in a machine-readable format, making it ideal for testing REST API responses.

Can Syrupy handle dynamic data like timestamps or IDs?

Yes, Syrupy provides matchers like path_type and path_value that allow you to validate the structure of dynamic data without failing tests due to changing values.

How do I update snapshots using this skill?

You can update your snapshots by running pytest with the --snapshot-update flag, which replaces existing snapshot files with the current computed results.

Syrupy Pytest Snapshot Testing

Name: Syrupy Pytest Snapshot Testing
Author: anam-org

byanam-org

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安全与测试

Simplifies snapshot testing in Python by asserting the immutability of complex data structures and managing snapshot files within pytest.

关于

Syrupy is a zero-dependency pytest plugin designed to make snapshot testing idiomatic and extensible. It allows developers to capture the state of complex data structures, API responses, or UI components and compare them against saved snapshots in future test runs. By providing built-in matchers for non-deterministic data—such as IDs or timestamps—and supporting various serialization formats like JSON, PNG, and SVG, Syrupy streamlines the testing of stable computed results while keeping your test suite clean and maintainable. This skill helps Claude guide you through implementing robust regression testing workflows using the Syrupy ecosystem.

主要功能

Idiomatic pytest assertion syntax for seamless integration.
Developer-friendly CLI options for updating, auditing, and cleaning snapshots.
Automatic snapshot management within dedicated __snapshots__ directories.
Custom matchers and filters for handling dynamic data like UUIDs and timestamps.
Built-in support for multiple serialization formats including JSON, PNG, and SVG.
12 GitHub stars

使用场景

Ensuring consistency in UI components and graphics through PNG and SVG snapshotting.
Managing large configuration objects or datasets that must remain stable over time.
Testing complex API responses and JSON payloads for unexpected regressions.

关于

主要功能

Idiomatic pytest assertion syntax for seamless integration.
Developer-friendly CLI options for updating, auditing, and cleaning snapshots.
Automatic snapshot management within dedicated __snapshots__ directories.
Custom matchers and filters for handling dynamic data like UUIDs and timestamps.
Built-in support for multiple serialization formats including JSON, PNG, and SVG.
12 GitHub stars

使用场景

Ensuring consistency in UI components and graphics through PNG and SVG snapshotting.
Managing large configuration objects or datasets that must remain stable over time.
Testing complex API responses and JSON payloads for unexpected regressions.