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Mount the dreamdock-data PVC in the k8s profile, and probe for it

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The PVC holding chembl_36.db and protein_seq.zarr was never mounted into task
pods: WES's injected profile.config supplies no storage config (verified across
a full run's logs). Without /mnt/dreamdock-data, sqlite3 raises 'unable to open
database file' and every GET_FINAL_METABOLITES_STATIC task exits 1.

Restore storageClaimName/storageMountPath, and add a probe that reports what is
visible before opening sqlite so the failure names its own cause.
This commit is contained in:
Olamide Isreal
2026-07-28 11:04:46 +01:00
parent 73e2eea4be
commit 724c7d8987
2 changed files with 41 additions and 6 deletions
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26
main_biotransformer.nf
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@@ -302,11 +302,35 @@ process GET_FINAL_METABOLITES_STATIC {
import numpy as np
import pandas as pd
import sqlite3
import os, sys
# --- diagnostic probe -------------------------------------------------
# The ChEMBL DB lives on the dreamdock-data PVC. If that PVC is not mounted
# into the task pod, sqlite3 fails with a generic "unable to open database
# file" that is indistinguishable from a corrupt/locked DB. Report what is
# actually visible before touching sqlite, so the failure names its cause.
_db = '$chembl_db'
print('[probe] chembl_db path : %s' % _db, file=sys.stderr)
print('[probe] exists : %s' % os.path.exists(_db), file=sys.stderr)
for _p in ('/mnt/dreamdock-data', os.path.dirname(_db)):
print('[probe] dir %-22s exists=%s' % (_p, os.path.isdir(_p)), file=sys.stderr)
if os.path.exists(_db):
print('[probe] size : %d bytes' % os.path.getsize(_db), file=sys.stderr)
print('[probe] readable : %s' % os.access(_db, os.R_OK), file=sys.stderr)
else:
sys.exit(
"[probe] FATAL: %s is not visible inside this task container.\n"
"[probe] The dreamdock-data PVC is not mounted. Check that the k8s\n"
"[probe] profile sets k8s.storageClaimName/storageMountPath and that\n"
"[probe] the WES-injected profile.config does not override them."
% _db
)
# --- end probe --------------------------------------------------------
# Connect to ChEMBL database
conn = sqlite3.connect('file:$chembl_db?mode=ro&immutable=1', uri=True)
# conn = sqlite3.connect('$chembl_db')
cursor = conn.cursor()
# Load biotransformer output