arcexpect 0.0.4

Helper for ARC validation scripts

[!NOTE] This GitHub repo is only a placeholder during development and testing. The code contained will be moved into a proper in the DataPLANT organization, e.g. into https://github.com/nfdi4plants/arc-validate.

ArcExpect

ArcExpect helps authors write ARC validation packages in Python. A package is a normal Python script with validation metadata, a list of checks, and a standard result folder containing a JSON summary, JUnit report, and SVG badge.

Write a validation package

Install the package and its runtime dependencies in your Python environment, then write a script such as example-validator.py. The frontmatter at the top is used when the package is indexed and is parsed by the package itself; keep it as the first content in the file.

"""
---
Name: example-python-validator
MajorVersion: 1
MinorVersion: 0
PatchVersion: 0
Summary: Checks the basic structure of an ARC.
Description: |
  A minimal native-Python ARC validation package.
Publish: true
Authors:
  - FullName: ARC validation team
    Email: [e-mail]
Tags:
  - Name: example
  - Name: python
ReleaseNotes: |
  - Initial version.
---
"""

from __future__ import annotations

import argparse
from pathlib import Path

from arcexpect import Execute, Expect, Setup, test_case, test_list


parser = argparse.ArgumentParser(description="Validate the basic structure of an ARC.")
parser.add_argument("--input", "-i", required=True, type=Path, help="Path to the ARC directory")
parser.add_argument("--output", "-o", required=True, type=Path, help="Directory for validation results")
args = parser.parse_args()


def input_directory_exists() -> None:
    Expect.is_true(args.input.is_dir(), "The input path must be an ARC directory")


def has_readme() -> None:
    Expect.is_true((args.input / "README.md").is_file(), "The ARC must contain README.md")


def has_investigation_or_study() -> None:
    has_investigation = (args.input / "investigation" / "isa.investigation.xlsx").is_file()
    has_study = (args.input / "studies").is_dir()
    Expect.is_true(has_investigation or has_study, "The ARC must contain an investigation or a study")


package = Setup.validation_package_from_script(
    __file__,
    critical=[
        test_list(
            "basic ARC structure",
            [
                test_case("input directory exists", input_directory_exists),
                test_case("README.md exists", has_readme),
                test_case("contains investigation or study", has_investigation_or_study),
            ],
        )
    ],
)

# Runs every check and writes validation_summary.json, validation_report.xml,
# and badge.svg below the output directory.
Execute.validation_pipeline(package, str(args.output))

Run the script with an ARC input directory and an output directory:

python example-validator.py --input ./my-arc --output ./results

The script creates the standard result layout:

results/
└── .arc-validate-results/
    └── example-python-validator@1.0.0/
        ├── badge.svg
        ├── validation_report.xml
        └── validation_summary.json

The JSON summary records critical and non-critical totals and outcomes. The XML file is a JUnit report suitable for CI systems, and the badge summarizes the validation result. A failing non-critical check is recorded in the report but does not make the badge a critical-error badge; failing or errored critical checks do.

Core API

• Setup.validation_package_from_script(__file__, critical=[...], non_critical=[...]) parses the script's frontmatter and combines it with its checks. This is the usual entry point for a native Python package.
• Setup.metadata(...) and Setup.validation_package(...) remain available when metadata is supplied by another source.
• test_case(name, check) and test_list(name, checks) declare validation cases; use pending_test_case for a skipped case.
• Expect.is_true, Expect.is_false, Expect.equal, and related methods report a validation failure with a useful message.
• Execute.validation_pipeline(package, output_path) is the usual script entry point. Execute.validation(package) returns an in-memory summary when files are not needed.

See the legacy standalone Python packages in references for additional domain-specific examples.