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| author | Munyoki Kilyungi | 2024-02-15 11:31:34 +0300 |
|---|---|---|
| committer | BonfaceKilz | 2024-02-15 11:35:00 +0300 |
| commit | 1a14fe968149908ecedb71500314f666985dfa27 (patch) | |
| tree | 6aeea3608fe4ea7052ecc5a1f6046f4152ba99c7 /gn3/db/datasets.py | |
| parent | dba5dbd6b43ea088f62426cc2ce6df4787cd9f78 (diff) | |
| download | genenetwork3-1a14fe968149908ecedb71500314f666985dfa27.tar.gz | |
Use correct names for dataset entries in json result.
Since we are appending to an already flattened json-ld file, we don't
need to add the prefixes.
* gn3/api/metadata.py (DATASET_CONTEXT): Add missing "experimentType"
key.
* gn3/db/datasets.py (retrieve_dataset_metadata): Match the __subject
dict with entries from DATASET_CONTEXT.
Signed-off-by: Munyoki Kilyungi <me@bonfacemunyoki.com>
Diffstat (limited to 'gn3/db/datasets.py')
| -rw-r--r-- | gn3/db/datasets.py | 24 |
1 files changed, 12 insertions, 12 deletions
diff --git a/gn3/db/datasets.py b/gn3/db/datasets.py index 6ec2126..043be4c 100644 --- a/gn3/db/datasets.py +++ b/gn3/db/datasets.py @@ -337,18 +337,18 @@ def retrieve_dataset_metadata(name: str) -> dict: """Return the full data given a path, NAME""" result = {} __subject = { - "summary": "dct:description", - "tissue": "gnt:hasTissueInfo", - "specifics": "gnt:hasTissueInfo", - "cases": "gnt:hasCaseInfo", - "platform": "gnt:hasPlatformInfo", - "processing": "gnt:hasDataProcessingInfo", - "notes": "gnt:hasNotes", - "experiment-design": "gnt:hasExperimentDesignInfo", - "acknowledgment": "gnt:hasAcknowledgement", - "citation": "dct:isReferencedBy", - "experiment-type": "gnt:hasExperimentType", - "contributors": "dct:creator", + "summary": "description", + "tissue": "tissueInfo", + "specifics": "specifics", + "cases": "caseInfo", + "platform": "platformInfo", + "processing": "processingInfo", + "notes": "notes", + "experiment-design": "experimentDesignInfo", + "acknowledgment": "acknowledgement", + "citation": "citation", + "experiment-type": "experimentType", + "contributors": "contributors", } for __file in Path(name).glob("*rtf"): with __file.open() as _f: |