Helper for ARC validation scripts
Project description
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: validation@example.org
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(...)andSetup.validation_package(...)remain available when metadata is supplied by another source.test_case(name, check)andtest_list(name, checks)declare validation cases; usepending_test_casefor 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.
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