expectfs 0.1.3

Declarative validation for files, directories, and system expectations

expectfs

Declarative validation for things that are not data models.

expectfs lets you define clear, readable expectations about files, directories, and system state — without schemas, test frameworks, or boilerplate.

This is for validating the world, not validating Python objects.

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Installation

pip install expectfs

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Quick Example

from expect import expect, validate

expect.file("metrics.json") \
    .is_json() \
    .size_gt(100)

result = validate()

result.print()

If any expectation fails, a clear, actionable error message will be displayed after running validation.

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Why expect?

Most validation tools focus on:

• JSON schemas
• Data models
• API payloads
• Function inputs

But engineers constantly need to validate things like:

• “Does this file exist?”
• “Is this directory populated?”
• “Is this JSON valid?”
• “Did my pipeline actually produce output?”

expectfs exists for that gap.

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Key Features

• Declarative, chainable expectations
• Automatic dependency resolution (rules run in the correct order)
• Rule caching (each rule runs at most once)
• Clear failure messages

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How it Works (Conceptually)

expect.file("output.json").is_json().size_gt(1024)

• is_json automatically ensures the file exists
• size_gt reuses prior results instead of re-running checks
• Dependencies are resolved recursively

Users don’t need to think about ordering.

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Supported Targets

Currently supported:

• Files
• Directories

Planned:

• Globs
• Environment variables
• Command outputs

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Status

This project is in alpha.

• APIs may evolve
• Backwards compatibility is not yet guaranteed
• Feedback and contributions are welcome

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License

MIT