scancode-config.yml in an input archive is detected differently by scan_codebase and scan_single_package
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Nadie ha tomado este issue todavía.
Evaluación
- Dificultad
- 4/5
- Tiempo estimado
- 3-5 días
- Aptitud para principiantes
- 48/100
Línea de trabajo
Start by reading the config discovery logic in scanpipe/models.py and the archive extraction paths in scanpipe/pipes/scancode.py and scanpipe/pipelines/scan_single_package.py. Then review the one-level search test in scanpipe/tests/test_models.py and compare behavior for flat and single-folder archives in both pipelines. Done means the supported layout behaves consistently and any agreed warning appears when a config is found but ignored; the issue leaves those decisions open.
Escrito por el modelo de indexación a partir del texto del issue.
Descripción
Describe the bug
A scancode-config.yml placed inside an input archive is used or ignored depending on the pipeline and on the archive layout. When it is ignored, there is no warning.
System configuration
- Version: v38.2.0 (
mainat 237ea33c) - Docker: yes, dev stack (
docker-compose.yml+docker-compose.dev.yml) - OS: macOS (Apple Silicon)
- Inputs:
flat.zipandwrapped.zip(attached) - Pipelines:
scan_codebaseandscan_single_package
To Reproduce
Two archives with the same content, different layout:
flat.zip: package.json, scancode-config.yml
wrapped.zip: my-app/package.json, my-app/scancode-config.yml
scancode-config.yml:
ignored_dependency_scopes:
- package_type: npm
scope: devDependencies
Run each pipeline on each archive (zips copied to /tmp in the web container):
for pipeline in scan_codebase scan_single_package; do
for zip in flat wrapped; do
docker compose exec -T web ./manage.py create-project "test-$pipeline-$zip" \
--input-file /tmp/$zip.zip --pipeline $pipeline --execute
done
done
docker compose exec -T web ./manage.py shell -c "
from scanpipe.models import Project
for p in Project.objects.filter(name__startswith='test-').order_by('name'):
print(p.name, '->', p.get_env('ignored_dependency_scopes'))
"
Output:
test-scan_codebase-flat -> [{'package_type': 'npm', 'scope': 'devDependencies'}]
test-scan_codebase-wrapped -> None
test-scan_single_package-flat -> None
test-scan_single_package-wrapped -> [{'package_type': 'npm', 'scope': 'devDependencies'}]
| flat.zip | wrapped.zip | |
|---|---|---|
scan_codebase |
loaded | ignored |
scan_single_package |
ignored | loaded |
Cause
The config is only searched in immediate codebase/ subdirectories:
https://github.com/aboutcode-org/scancode.io/blob/237ea33c9ce119e0756fd12d93a0216c47880f43/scanpipe/models.py#L894-L899
But the two pipelines extract archives to different places:
scan_codebaseextracts tocodebase/<name>-extract/, so only a config at the archive top level is found:
https://github.com/aboutcode-org/scancode.io/blob/237ea33c9ce119e0756fd12d93a0216c47880f43/scanpipe/pipes/scancode.py#L132-L140scan_single_packageextracts directly intocodebase/, so only a config inside a single top folder is found:
https://github.com/aboutcode-org/scancode.io/blob/237ea33c9ce119e0756fd12d93a0216c47880f43/scanpipe/pipelines/scan_single_package.py#L96-L106
The one-level search looks intentional (#1236 and this test):
https://github.com/aboutcode-org/scancode.io/blob/237ea33c9ce119e0756fd12d93a0216c47880f43/scanpipe/tests/test_models.py#L746-L753
Most real source archives (GitHub release tarballs, sdists, npm tarballs) have a single top folder, so with scan_codebase their config is silently ignored.
Expected behavior
The same archive should behave the same way in both pipelines. Questions:
- Which layout should be supported: top level, single top folder, or both?
- Should a warning be logged when a
scancode-config.ymlexists in the codebase but is not used?
Related
#2215 may be a real case of this (config inside a source archive). Note: in my test jest is still listed as a dependency even when the config is loaded; that is the separate package_type issue fixed in #2218.
I'm happy to work on a fix once the expected behavior is agreed.
AI disclosure: I used Claude Code to help explore the codebase and investigate. I ran the reproduction above myself and checked the results.
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Preparar el entorno
- Incluye un Dockerfile o un archivo de Docker Compose
- Tiene una plantilla de pull request
- Leer la guía de contribución
Primeros pasos
- Lee el issue completo y luego la guía de contribución del proyecto.
- Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
- Haz un fork del repositorio y trabaja en una rama.
- Abre un pull request que haga referencia al número del issue.
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