def test_downloadable_files_data_category_prefix():
"""Check that data_category_prefix's are derived as expected"""
file_w_category = DownloadableFiles(facet_group="/wes/r1_L.fastq.gz")
assert file_w_category.data_category_prefix == "WES"
file_no_category = DownloadableFiles()
assert file_no_category.data_category_prefix == None
def test_upload_manifest_twice(cidc_api, clean_db, monkeypatch):
"""Ensure that doing upload_manifest twice will produce only one DownloadableFiles"""
user_id = setup_trial_and_user(cidc_api, monkeypatch)
mocks = UploadMocks(monkeypatch)
client = cidc_api.test_client()
grant_upload_permission(user_id, "pbmc", cidc_api)
make_nci_biobank_user(user_id, cidc_api)
res = client.post(MANIFEST_UPLOAD,
data=form_data("pbmc.xlsx", io.BytesIO(b"a"), "pbmc"))
assert res.status_code == 200
# Check that we tried to publish a patient/sample update
mocks.publish_patient_sample_update.assert_called_once()
with cidc_api.app_context():
assert not DownloadableFiles.list() # manifest is not stored
# uploading second time
res = client.post(MANIFEST_UPLOAD,
data=form_data("pbmc.xlsx", io.BytesIO(b"b"), "pbmc"))
assert res.status_code == 200
assert mocks.upload_xlsx.call_count == 0 # manifest is not stored
with cidc_api.app_context():
assert not DownloadableFiles.list() # manifest is not stored
def test_downloadable_files_additional_metadata_default(clean_db):
TrialMetadata.create(TRIAL_ID, METADATA)
df = DownloadableFiles(
trial_id=TRIAL_ID,
upload_type="wes_bam",
object_url="10021/Patient 1/sample 1/aliquot 1/wes_forward.fastq",
file_size_bytes=1,
md5_hash="hash1234",
uploaded_timestamp=datetime.now(),
)
# Check no value passed
df.insert()
assert df.additional_metadata == {}
for nullish_value in [None, "null", {}]:
df.additional_metadata = nullish_value
df.update()
assert df.additional_metadata == {}
# Non-nullish value doesn't get overridden
non_nullish_value = {"foo": "bar"}
df.additional_metadata = non_nullish_value
df.update()
assert df.additional_metadata == non_nullish_value
def test_create_downloadable_file_from_metadata(db, monkeypatch):
"""Try to create a downloadable file from artifact_core metadata"""
# fake file metadata
file_metadata = {
"artifact_category": "Assay Artifact from CIMAC",
"object_url": "10021/Patient 1/sample 1/aliquot 1/wes_forward.fastq",
"file_name": "wes_forward.fastq",
"file_size_bytes": 1,
"md5_hash": "hash1234",
"uploaded_timestamp": datetime.now(),
"foo": "bar", # unsupported column - should be filtered
}
# Create the trial (to avoid violating foreign-key constraint)
TrialMetadata.patch_trial_metadata(TRIAL_ID, METADATA)
# Create the file
DownloadableFiles.create_from_metadata(TRIAL_ID, "wes", file_metadata)
# Check that we created the file
new_file = (db.query(DownloadableFiles).filter_by(
file_name=file_metadata["file_name"]).first())
assert new_file
del file_metadata["foo"]
for k in file_metadata.keys():
assert getattr(new_file, k) == file_metadata[k]
def test_create_downloadable_file_from_metadata(clean_db, monkeypatch):
"""Try to create a downloadable file from artifact_core metadata"""
# fake file metadata
file_metadata = {
"object_url": "10021/Patient 1/sample 1/aliquot 1/wes_forward.fastq",
"file_size_bytes": 1,
"md5_hash": "hash1234",
"uploaded_timestamp": datetime.now(),
"foo": "bar", # unsupported column - should be filtered
}
additional_metadata = {"more": "info"}
# Mock artifact upload publishing
publisher = MagicMock()
monkeypatch.setattr("cidc_api.models.models.publish_artifact_upload", publisher)
# Create the trial (to avoid violating foreign-key constraint)
TrialMetadata.create(TRIAL_ID, METADATA)
# Create files with empty or "null" additional metadata
for nullish_value in ["null", None, {}]:
df = DownloadableFiles.create_from_metadata(
TRIAL_ID, "wes_bam", file_metadata, additional_metadata=nullish_value
)
clean_db.refresh(df)
assert df.additional_metadata == {}
# Create the file
DownloadableFiles.create_from_metadata(
TRIAL_ID, "wes_bam", file_metadata, additional_metadata=additional_metadata
)
# Check that we created the file
new_file = (
clean_db.query(DownloadableFiles)
.filter_by(object_url=file_metadata["object_url"])
.first()
)
assert new_file
del file_metadata["foo"]
for k in file_metadata.keys():
assert getattr(new_file, k) == file_metadata[k]
assert new_file.additional_metadata == additional_metadata
# Check that no artifact upload event was published
publisher.assert_not_called()
# Check that artifact upload publishes
DownloadableFiles.create_from_metadata(
TRIAL_ID,
"wes_bam",
file_metadata,
additional_metadata=additional_metadata,
alert_artifact_upload=True,
)
publisher.assert_called_once_with(file_metadata["object_url"])
def create_df(facet_group, additional_metadata={}) -> DownloadableFiles:
df = DownloadableFiles(
facet_group=facet_group,
additional_metadata=additional_metadata,
trial_id=TRIAL_ID,
uploaded_timestamp=datetime.now(),
file_size_bytes=0,
object_url=facet_group, # just filler, not relevant to the test
upload_type="",
)
df.insert()
clean_db.refresh(df)
return df
def test_info_data_overview(cidc_api, clean_db):
"""Check that the data overview has expected structure and values"""
def insert_trial(trial_id, num_participants, num_samples):
TrialMetadata(
trial_id=trial_id,
metadata_json={
prism.PROTOCOL_ID_FIELD_NAME:
trial_id,
"allowed_cohort_names": [""],
"allowed_collection_event_names": [""],
"participants": [{
"cimac_participant_id":
f"CTTTPP{p}",
"participant_id":
"x",
"samples": [{
"cimac_id": f"CTTTPP1SS.0{s}",
"sample_location": "",
"type_of_primary_container": "Other",
"type_of_sample": "Other",
"collection_event_name": "",
"parent_sample_id": "",
} for s in range(num_samples[p])],
} for p in range(num_participants)],
},
).insert()
# 3 trials
# 15 participants
# 40 samples
# 3 files
with cidc_api.app_context():
insert_trial("1", 6, [0] * 6)
insert_trial("2", 4, [5, 6, 7, 8])
insert_trial("3", 5, [3, 2, 1, 1, 7])
for i in range(3):
DownloadableFiles(
trial_id="1",
upload_type="wes",
object_url=str(i),
facet_group=
"/wes/r2_L.fastq.gz", # this is what makes this file "related"
uploaded_timestamp=datetime.now(),
file_size_bytes=2,
).insert()
client = cidc_api.test_client()
res = client.get("/info/data_overview")
assert res.status_code == 200
assert res.json == {
"num_assays": len(prism.SUPPORTED_ASSAYS),
"num_trials": 3,
"num_participants": 15,
"num_samples": 40,
"num_files": 3,
"num_bytes": 6,
}
def make_file(trial_id, object_url, upload_type,
facet_group) -> DownloadableFiles:
return DownloadableFiles(
trial_id=trial_id,
upload_type=upload_type,
object_url=f"{trial_id}/{object_url}",
facet_group=facet_group,
uploaded_timestamp=datetime.now(),
file_size_bytes=int(51 * 1e6), # 51MB
)
def setup_db_records(cidc_api):
extra = {"_etag": ETAG}
with cidc_api.app_context():
Users(**users["json"], **extra).insert(compute_etag=False)
TrialMetadata(**trial_metadata["json"], **extra).insert(compute_etag=False)
DownloadableFiles(**downloadable_files["json"], **extra).insert(
compute_etag=False
)
Permissions(**permissions["json"], **extra).insert(compute_etag=False)
UploadJobs(**upload_jobs["json"], **extra).insert(compute_etag=False)
def test_get_related_files(cidc_api, clean_db, monkeypatch):
"""Check that the related_files endpoint calls `get_related_files`"""
user_id = setup_user(cidc_api, monkeypatch)
file_id_1, file_id_2 = setup_downloadable_files(cidc_api)
client = cidc_api.test_client()
# Add an additional file that is related to file 1
object_url = "/foo/bar"
with cidc_api.app_context():
DownloadableFiles(
trial_id=trial_id_1,
upload_type="wes",
object_url=object_url,
facet_group=
"/wes/r2_L.fastq.gz", # this is what makes this file "related"
uploaded_timestamp=datetime.now(),
file_size_bytes=0,
).insert()
# Non-admins get 401s when requesting related files they don't have permission to view
res = client.get(f"/downloadable_files/{file_id_1}/related_files")
assert res.status_code == 401
# Give the user one permission
with cidc_api.app_context():
perm = Permissions(
granted_to_user=user_id,
trial_id=trial_id_1,
upload_type=upload_types[0],
granted_by_user=user_id,
)
perm.insert()
# Non-admins can get related files that they have permision to view
res = client.get(f"/downloadable_files/{file_id_1}/related_files")
assert res.status_code == 200
assert len(res.json["_items"]) == 1 # file 1 has 1 related file
assert res.json["_items"][0]["object_url"] == object_url
# Admins can get related files without permissions
make_admin(user_id, cidc_api)
res = client.get(f"/downloadable_files/{file_id_2}/related_files")
assert res.status_code == 200
assert len(res.json["_items"]) == 0 # file 2 has 0 related file
def vis_preprocessing(event: dict, context: BackgroundContext):
with sqlalchemy_session() as session:
object_url = extract_pubsub_data(event)
file_record: DownloadableFiles = DownloadableFiles.get_by_object_url(
object_url, session=session)
if not file_record:
raise Exception(
f"No downloadable file with object URL {object_url} found.")
metadata_df = _get_metadata_df(file_record.trial_id)
# Apply the transformations and get derivative data for visualization.
for transform_name, transform in _get_transforms().items():
vis_json = transform(file_record, metadata_df)
if vis_json:
# Add the vis config to the file_record
setattr(file_record, transform_name, vis_json)
# Save the derivative data additions to the database.
session.commit()
def _derive_files_from_upload(trial_id: str, upload_type: str, session):
# Get trial metadata JSON for the associated trial
trial_record: TrialMetadata = TrialMetadata.find_by_trial_id(
trial_id, session=session)
# Run the file derivation
derivation_context = unprism.DeriveFilesContext(trial_record.metadata_json,
upload_type,
fetch_artifact)
derivation_result = unprism.derive_files(derivation_context)
# TODO: consider parallelizing this step if necessary
for artifact in derivation_result.artifacts:
# Save to GCS
blob = upload_to_data_bucket(artifact.object_url, artifact.data)
# Build basic facet group
facet_group = f"{artifact.data_format}|{artifact.file_type}"
# Save to database
df_record = DownloadableFiles.create_from_blob(
trial_record.trial_id,
artifact.file_type,
artifact.data_format,
facet_group,
blob,
session=session,
alert_artifact_upload=True,
)
df_record.additional_metadata = artifact.metadata
# Assume that a derived file will be directly useful for data analysis
df_record.analysis_friendly = True
# Update the trial metadata blob (in case the file derivation modified it)
trial_record.metadata_json = derivation_result.trial_metadata
session.commit()
def test_list_trials(cidc_api, clean_db, monkeypatch):
"""Check that listing trials works as expected"""
mock_gcloud_client(monkeypatch)
user_id = setup_user(cidc_api, monkeypatch)
trial_1, trial_2 = setup_trial_metadata(cidc_api, user_id)
client = cidc_api.test_client()
# A CIMAC user can list trials that they're allowed to see via
# granular permissions
res = client.get("/trial_metadata")
assert res.status_code == 200
assert len(res.json["_items"]) == 1
assert res.json["_items"][0]["id"] == trial_1
assert "file_bundle" not in res.json["_items"][0]
assert "num_participants" not in res.json["_items"][0]
assert "num_samples" not in res.json["_items"][0]
# A CIMAC user with a cross-trial permission can list all trials
with cidc_api.app_context():
Permissions(granted_by_user=user_id,
granted_to_user=user_id,
upload_type="ihc").insert()
res = client.get("/trial_metadata")
assert res.status_code == 200
assert len(res.json["_items"]) == 2
# Allowed users can get all trials
for role in trial_modifier_roles:
make_role(user_id, role, cidc_api)
res = client.get("/trial_metadata")
assert res.status_code == 200
assert len(res.json["_items"]) == 2
assert res.json["_meta"]["total"] == 2
assert set([t["id"]
for t in res.json["_items"]]) == set([trial_1, trial_2])
assert not any("file_bundle" in t for t in res.json["_items"])
# Passing the URL param include_file_bundles=true works on an
# as-available basis - if trials have no files associated with them,
# they won't have a file bundle in the response
res = client.get("/trial_metadata?include_file_bundles=true")
assert res.status_code == 200
assert len(res.json["_items"]) == 2
assert "file_bundle" not in res.json["_items"][0]
# Add some files...
with cidc_api.app_context():
# for trial 1
for id, (type, facet_group) in enumerate([
("cytof_10021_9204", "/cytof_10021_9204/spike_in.fcs"),
("cytof_10021_9204", "/cytof_10021_9204/source_.fcs"),
(
"cytof_10021_9204",
"/cytof_analysis/combined_cell_counts_profiling.csv",
),
("wes", "/wes/r1_L.fastq.gz"),
]):
DownloadableFiles(
id=id,
trial_id="test-trial-1",
facet_group=facet_group,
object_url=f"test-trial-1/{facet_group}",
upload_type=type,
file_size_bytes=0,
uploaded_timestamp=datetime.now(),
).insert()
# for trial 2
for id_minus_4, (type, facet_group) in enumerate([
("participants info", "csv|participants info"),
("mif", "/mif/roi_/cell_seg_data.txt"),
]):
DownloadableFiles(
id=id_minus_4 + 4,
trial_id="test-trial-2",
facet_group=facet_group,
object_url=f"test-trial-2/{facet_group}",
upload_type=type,
file_size_bytes=0,
uploaded_timestamp=datetime.now(),
).insert()
# Listing trials with populated file bundles (also, check that sorting and counting participants/samples works)
res = client.get(
"/trial_metadata?include_file_bundles=true&include_counts=true&sort_field=trial_id&sort_direction=asc"
)
assert res.status_code == 200
assert len(res.json["_items"]) == 2
assert res.json["_items"][0]
[trial_json_1, trial_json_2] = res.json["_items"]
assert set(trial_json_1["file_bundle"]["CyTOF"]["source"]) == set([0, 1])
assert trial_json_1["file_bundle"]["CyTOF"]["analysis"] == [2]
assert trial_json_1["file_bundle"]["WES"]["source"] == [3]
assert trial_json_1["num_samples"] == 1
assert trial_json_1["num_participants"] == 1
assert trial_json_2["file_bundle"]["Participants Info"]["clinical"] == [4]
assert trial_json_2["file_bundle"]["mIF"]["analysis"] == [5]
assert trial_json_2["num_samples"] == 0
assert trial_json_2["num_participants"] == 0
# Filtering by trial id seems to work when file bundles are included
res = client.get(
"/trial_metadata?include_file_bundles=true&trial_ids=test-trial-1")
assert res.status_code == 200
assert len(res.json["_items"]) == 1
assert res.json["_items"][0]["trial_id"] == "test-trial-1"
# Pagination seems to work when file bundles are included
res = client.get("/trial_metadata?include_file_bundles=true&page_size=1")
assert res.status_code == 200
assert len(res.json["_items"]) == 1
# Metadata blobs are pruned as expected
res = client.get("/trial_metadata")
assert res.status_code == 200
metadata_json = res.json["_items"][0]["metadata_json"]
assert metadata_json.get("participants") is None
assert metadata_json.get("assays") is None
assert metadata_json.get("analysis") is None
assert metadata_json.get("shipments") is None
def test_create_compressed_batch(cidc_api, clean_db, monkeypatch):
user_id = setup_user(cidc_api, monkeypatch)
file_id_1, file_id_2 = setup_downloadable_files(cidc_api)
with cidc_api.app_context():
url_1 = DownloadableFiles.find_by_id(file_id_1).object_url
url_2 = DownloadableFiles.find_by_id(file_id_2).object_url
client = cidc_api.test_client()
url = "/downloadable_files/compressed_batch"
# A JSON body containing a file ID list must be provided
res = client.post(url)
assert res.status_code == 422
# User has no permissions, so no files should be found
short_file_list = {"file_ids": [file_id_1, file_id_2]}
res = client.post(url, json=short_file_list)
assert res.status_code == 404
# Give the user one permission
with cidc_api.app_context():
perm = Permissions(
granted_to_user=user_id,
trial_id=trial_id_1,
upload_type=upload_types[0],
granted_by_user=user_id,
)
perm.insert()
# Mock GCS client
blob = MagicMock()
bucket = MagicMock()
bucket.blob.return_value = blob
monkeypatch.setattr(
"cidc_api.resources.downloadable_files.gcloud_client._get_bucket",
lambda _: bucket,
)
signed_url = "fake/signed/url"
monkeypatch.setattr(
"cidc_api.resources.downloadable_files.gcloud_client.get_signed_url",
lambda *_: signed_url,
)
# User has one permission, s0 the endpoint should try to create
# a compressed batch file with the single file the user has
# access to in it.
res = client.post(url, json=short_file_list)
assert res.status_code == 200
assert res.json == signed_url
print(bucket.get_blob.call_args_list)
bucket.get_blob.assert_called_with(url_1)
blob.upload_from_filename.assert_called_once()
bucket.reset_mock()
blob.reset_mock()
make_admin(user_id, cidc_api)
# Admin has access to both files, but together they are too large
res = client.post(url, json=short_file_list)
assert res.status_code == 400
assert "batch too large" in res.json["_error"]["message"]
bucket.get_blob.assert_not_called()
blob.upload_from_filename.assert_not_called()
# Decrease the size of one of the files and try again
with cidc_api.app_context():
df = DownloadableFiles.find_by_id(file_id_1)
df.file_size_bytes = 1
df.update()
res = client.post(url, json=short_file_list)
assert res.status_code == 200
assert res.json == signed_url
assert call(url_1) in bucket.get_blob.call_args_list
assert call(url_2) in bucket.get_blob.call_args_list
blob.upload_from_filename.assert_called_once()
def test_get_filelist(cidc_api, clean_db, monkeypatch):
"""Check that getting a filelist.tsv works as expected"""
user_id = setup_user(cidc_api, monkeypatch)
file_id_1, file_id_2 = setup_downloadable_files(cidc_api)
client = cidc_api.test_client()
url = "/downloadable_files/filelist"
# A JSON body containing a file ID list must be provided
res = client.post(url)
assert res.status_code == 422
# User has no permissions, so no files should be found
short_file_list = {"file_ids": [file_id_1, file_id_2]}
res = client.post(url, json=short_file_list)
assert res.status_code == 404
# Give the user one permission
with cidc_api.app_context():
perm = Permissions(
granted_to_user=user_id,
trial_id=trial_id_1,
upload_type=upload_types[0],
granted_by_user=user_id,
)
perm.insert()
# User has one permission, so the filelist should contain a single file
res = client.post(url, json=short_file_list)
assert res.status_code == 200
assert "text/tsv" in res.headers["Content-Type"]
assert "filename=filelist.tsv" in res.headers["Content-Disposition"]
assert res.data.decode("utf-8") == (
f"gs://{GOOGLE_DATA_BUCKET}/{trial_id_1}/wes/.../reads_123.bam\t{trial_id_1}_wes_..._reads_123.bam\n"
)
# Admins don't need permissions to get files
make_admin(user_id, cidc_api)
res = client.post(url, json=short_file_list)
assert res.status_code == 200
assert res.data.decode("utf-8") == (
f"gs://{GOOGLE_DATA_BUCKET}/{trial_id_1}/wes/.../reads_123.bam\t{trial_id_1}_wes_..._reads_123.bam\n"
f"gs://{GOOGLE_DATA_BUCKET}/{trial_id_2}/cytof/.../analysis.zip\t{trial_id_2}_cytof_..._analysis.zip\n"
)
# Clear inserted file records
with cidc_api.app_context():
clean_db.query(DownloadableFiles).delete()
# Filelists don't get paginated
ids = []
with cidc_api.app_context():
for id in range(1000):
df = DownloadableFiles(
trial_id=trial_id_1,
object_url=str(id),
upload_type="",
file_size_bytes=0,
uploaded_timestamp=datetime.now(),
)
df.insert()
ids.append(df.id)
res = client.post(url, json={"file_ids": ids})
assert res.status_code == 200
# newly inserted files + EOF newline
assert len(res.data.decode("utf-8").split("\n")) == len(ids) + 1
def test_create_downloadable_file_from_blob(clean_db, monkeypatch):
"""Try to create a downloadable file from a GCS blob"""
fake_blob = MagicMock()
fake_blob.name = "name"
fake_blob.md5_hash = "12345"
fake_blob.crc32c = "54321"
fake_blob.size = 5
fake_blob.time_created = datetime.now()
clean_db.add(
TrialMetadata(
trial_id="id",
metadata_json={
"protocol_identifier": "id",
"allowed_collection_event_names": [],
"allowed_cohort_names": [],
"participants": [],
},
)
)
df = DownloadableFiles.create_from_blob(
"id", "pbmc", "Shipping Manifest", "pbmc/shipping", fake_blob
)
# Mock artifact upload publishing
publisher = MagicMock()
monkeypatch.setattr("cidc_api.models.models.publish_artifact_upload", publisher)
# Check that the file was created
assert 1 == clean_db.query(DownloadableFiles).count()
df_lookup = DownloadableFiles.find_by_id(df.id)
assert df_lookup.object_url == fake_blob.name
assert df_lookup.data_format == "Shipping Manifest"
assert df_lookup.file_size_bytes == fake_blob.size
assert df_lookup.md5_hash == fake_blob.md5_hash
assert df_lookup.crc32c_hash == fake_blob.crc32c
# uploading second time to check non duplicating entries
fake_blob.size = 6
fake_blob.md5_hash = "6"
df = DownloadableFiles.create_from_blob(
"id", "pbmc", "Shipping Manifest", "pbmc/shipping", fake_blob
)
# Check that the file was created
assert 1 == clean_db.query(DownloadableFiles).count()
df_lookup = DownloadableFiles.find_by_id(df.id)
assert df_lookup.file_size_bytes == 6
assert df_lookup.md5_hash == "6"
# Check that no artifact upload event was published
publisher.assert_not_called()
# Check that artifact upload publishes
DownloadableFiles.create_from_blob(
"id",
"pbmc",
"Shipping Manifest",
"pbmc/shipping",
fake_blob,
alert_artifact_upload=True,
)
publisher.assert_called_once_with(fake_blob.name)
def test_trial_metadata_get_summaries(clean_db, monkeypatch):
"""Check that trial data summaries are computed as expected"""
# Add some trials
records = [{"fake": "record"}]
cytof_record_with_output = [{"output_files": {"foo": "bar"}}]
tm1 = {
**METADATA,
# deliberately override METADATA['protocol_identifier']
"protocol_identifier": "tm1",
"participants": [{"samples": [1, 2]}, {"samples": [3]}],
"expected_assays": ["ihc", "olink"],
"assays": {
"wes": [
{"records": records * 6},
{"records": records * 5},
], # 6 + 5 11 = 7 for wes + 4 for wes_tumor_only
"rna": [{"records": records * 2}],
"mif": [
{"records": records * 3},
{"records": records},
{"records": records},
],
"elisa": [{"assay_xlsx": {"number_of_samples": 7}}],
"nanostring": [
{"runs": [{"samples": records * 2}]},
{"runs": [{"samples": records * 1}]},
],
"hande": [{"records": records * 5}],
},
"analysis": {
"wes_analysis": {
"pair_runs": [
# 7 here for wes_assay: t0/1/2, n0/1/2/3
{
"tumor": {"cimac_id": "t0"},
"normal": {"cimac_id": "n0"},
}, # no analysis data
{
"tumor": {"cimac_id": "t1"},
"normal": {"cimac_id": "n1"},
"report": {"report": "foo"},
},
{
"tumor": {"cimac_id": "t1"},
"normal": {"cimac_id": "n2"},
"report": {"report": "foo"},
},
{
"tumor": {"cimac_id": "t2"},
"normal": {"cimac_id": "n3"},
"report": {"report": "foo"},
},
],
# these are excluded, so not adding fake assay data
"excluded_samples": records * 2,
},
"wes_tumor_only_analysis": {
"runs": records * 4, # need 4
# these are excluded, so not adding fake assay data
"excluded_samples": records * 3,
},
},
"clinical_data": {
"records": [
{"clinical_file": {"participants": ["a", "b", "c"]}},
{"clinical_file": {"participants": ["a", "b", "d"]}},
{"clinical_file": {"participants": ["e", "f", "g"]}},
]
},
}
tm2 = {
**METADATA,
# deliberately override METADATA['protocol_identifier']
"protocol_identifier": "tm1",
"participants": [{"samples": []}],
"assays": {
"cytof_10021_9204": [
{
"records": cytof_record_with_output * 2,
"excluded_samples": records * 2,
},
{"records": records * 2},
{"records": records},
],
"cytof_e4412": [
{
"participants": [
{"samples": records},
{"samples": cytof_record_with_output * 5},
{"samples": records * 2},
],
"excluded_samples": records,
}
],
"olink": {
"batches": [
{
"records": [
{"files": {"assay_npx": {"number_of_samples": 2}}},
{"files": {"assay_npx": {"number_of_samples": 3}}},
]
},
{"records": [{"files": {"assay_npx": {"number_of_samples": 3}}}]},
]
},
},
"analysis": {
"rna_analysis": {"level_1": records * 10, "excluded_samples": records * 2},
"tcr_analysis": {
"batches": [
{"records": records * 4, "excluded_samples": records * 3},
{"records": records * 2, "excluded_samples": records * 1},
]
},
},
}
TrialMetadata(trial_id="tm1", metadata_json=tm1).insert(validate_metadata=False)
TrialMetadata(trial_id="tm2", metadata_json=tm2).insert(validate_metadata=False)
# Add some files
for i, (tid, fs) in enumerate([("tm1", 3), ("tm1", 2), ("tm2", 4), ("tm2", 6)]):
DownloadableFiles(
trial_id=tid,
file_size_bytes=fs,
object_url=str(i),
facet_group="",
uploaded_timestamp=datetime.now(),
upload_type="",
).insert()
sorter = lambda s: s["trial_id"]
received = sorted(TrialMetadata.get_summaries(), key=sorter)
expected = sorted(
[
{
"expected_assays": [],
"cytof": 13.0,
"olink": 8.0,
"trial_id": "tm2",
"file_size_bytes": 10,
"total_participants": 1,
"total_samples": 0,
"clinical_participants": 0.0,
"rna": 0.0,
"nanostring": 0.0,
"elisa": 0.0,
"h&e": 0.0,
"mif": 0.0,
"cytof_analysis": 7.0,
"rna_level1_analysis": 10.0,
"tcr_analysis": 6.0,
"wes_analysis": 0.0,
"wes_tumor_only_analysis": 0.0,
"wes": 0.0,
"wes_tumor_only": 0.0,
"excluded_samples": {
"tcr_analysis": records * 4,
"rna_level1_analysis": records * 2,
"cytof_analysis": records * 3,
},
},
{
"expected_assays": ["ihc", "olink"],
"elisa": 7.0,
"cytof": 0.0,
"olink": 0.0,
"trial_id": "tm1",
"file_size_bytes": 5,
"total_participants": 2,
"total_samples": 3,
"clinical_participants": 7.0,
"rna": 2.0,
"nanostring": 3.0,
"h&e": 5.0,
"mif": 5.0,
"cytof_analysis": 0.0,
"rna_level1_analysis": 0.0,
"tcr_analysis": 0.0,
"wes_analysis": 5.0,
"wes_tumor_only_analysis": 4.0,
"wes": 7.0,
"wes_tumor_only": 4.0,
"excluded_samples": {
"wes_analysis": records * 2,
"wes_tumor_only_analysis": records * 3,
},
},
],
key=sorter,
)
assert received == expected
assert all("misc_data" not in entry for entry in received)
def ingest_upload(event: dict, context: BackgroundContext):
"""
When a successful upload event is published, move the data associated
with the upload job into the download bucket and merge the upload metadata
into the appropriate clinical trial JSON.
"""
storage_client = storage.Client()
job_id = int(extract_pubsub_data(event))
logger.info(f"ingest_upload execution started on upload job id {job_id}")
with sqlalchemy_session() as session:
job: UploadJobs = UploadJobs.find_by_id(job_id, session=session)
# Check ingestion pre-conditions
if not job:
raise Exception(f"No assay upload job with id {job_id} found.")
if UploadJobStatus(job.status) != UploadJobStatus.UPLOAD_COMPLETED:
raise Exception(
f"Received ID for job with status {job.status}. Aborting ingestion."
)
trial_id = job.metadata_patch.get(prism.PROTOCOL_ID_FIELD_NAME)
if not trial_id:
# We should never hit this, since metadata should be pre-validated.
with saved_failure_status(job, session):
raise Exception(
f"Invalid assay metadata: missing protocol identifier ({prism.PROTOCOL_ID_FIELD_NAME})."
)
logger.info(
f"Found completed upload job (job_id={job_id}) with uploader {job.uploader_email}"
)
url_bundles = [
URLBundle(*bundle) for bundle in job.upload_uris_with_data_uris_with_uuids()
]
# Copy GCS blobs in parallel
logger.info("Copying artifacts from upload bucket to data bucket.")
with ThreadPoolExecutor(THREADPOOL_THREADS) as executor, saved_failure_status(
job, session
):
destination_objects = executor.map(
lambda url_bundle: _gcs_copy(
storage_client,
GOOGLE_UPLOAD_BUCKET,
url_bundle.upload_url,
GOOGLE_DATA_BUCKET,
url_bundle.target_url,
),
url_bundles,
)
metadata_patch = job.metadata_patch
logger.info("Adding artifact metadata to metadata patch.")
metadata_patch, downloadable_files = TrialMetadata.merge_gcs_artifacts(
metadata_patch,
job.upload_type,
zip([ub.artifact_uuid for ub in url_bundles], destination_objects),
)
# Add metadata for this upload to the database
logger.info(
"Merging metadata from upload %d into trial %s: " % (job.id, trial_id),
metadata_patch,
)
with saved_failure_status(job, session):
trial = TrialMetadata.patch_assays(
trial_id, metadata_patch, session=session
)
# Save downloadable files to the database
# NOTE: this needs to happen after TrialMetadata.patch_assays
# in order to avoid violating a foreign-key constraint on the trial_id
# in the event that this is the first upload for a trial.
logger.info("Saving artifact records to the downloadable_files table.")
for artifact_metadata, additional_metadata in downloadable_files:
logger.debug(
f"Saving metadata to downloadable_files table: {artifact_metadata}"
)
DownloadableFiles.create_from_metadata(
trial_id,
job.upload_type,
artifact_metadata,
additional_metadata=additional_metadata,
session=session,
commit=False,
)
# Additionally, make the metadata xlsx a downloadable file
with saved_failure_status(job, session):
_, xlsx_blob = _get_bucket_and_blob(
storage_client, GOOGLE_DATA_BUCKET, job.gcs_xlsx_uri
)
full_uri = f"gs://{GOOGLE_DATA_BUCKET}/{xlsx_blob.name}"
data_format = "Assay Metadata"
facet_group = f"{job.upload_type}|{data_format}"
logger.info(f"Saving {full_uri} as a downloadable_file.")
DownloadableFiles.create_from_blob(
trial_id,
job.upload_type,
data_format,
facet_group,
xlsx_blob,
session=session,
)
# Update the job metadata to include artifacts
job.metadata_patch = metadata_patch
# Making files downloadable by a specified biofx analysis team group
assay_prefix = job.upload_type.split("_")[0] # 'wes_bam' -> 'wes'
if assay_prefix in GOOGLE_ANALYSIS_PERMISSIONS_GROUPS_DICT:
analysis_group_email = GOOGLE_ANALYSIS_PERMISSIONS_GROUPS_DICT[assay_prefix]
_gcs_add_prefix_reader_permission(
storage_client,
analysis_group_email, # to whom give access to
f"{trial_id}/{assay_prefix}", # to what sub-folder
)
# Save the upload success and trigger email alert if transaction succeeds
job.ingestion_success(trial, session=session, send_email=True, commit=True)
# Trigger post-processing on uploaded data files
logger.info(f"Publishing object URLs to 'artifact_upload' topic")
with ThreadPoolExecutor(THREADPOOL_THREADS) as executor:
executor.map(
lambda url_bundle: publish_artifact_upload(url_bundle.target_url),
url_bundles,
)
# Trigger post-processing on entire upload
report = _encode_and_publish(str(job.id), GOOGLE_ASSAY_OR_ANALYSIS_UPLOAD_TOPIC)
if report:
report.result()
# Google won't actually do anything with this response; it's
# provided for testing purposes only.
return jsonify(
dict((bundle.upload_url, bundle.target_url) for bundle in url_bundles)
)