mirror
/
repo2docker
kopia lustrzana https://github.com/jupyterhub/repo2docker
1
0
Forkuj 0
Kod Zgłoszenia Projekty Wydania Wiki Aktywność

Support fetcing single files in dataverse

pull/1390/head
YuviPanda 2024-12-16 17:02:25 -08:00
rodzic 172f8b017d
commit 1260a5a394
2 zmienionych plików z 118 dodań i 37 usunięć
Pokaż statystyki Ściągnij plik aktualizacji Ściągnij plik porównania Expand all files Collapse all files

42
repo2docker/contentproviders/dataverse.py
Wyświetl plik

@ -106,7 +106,7 @@ class Dataverse(DoiProvider):
)
return data["items"][0]["dataset_persistent_id"]
elif parsed_url.path.startswith("/file.xhtml"):
file_persistent_id = qs['persistentId'][0]
file_persistent_id = qs["persistentId"][0]
dataset_persistent_id = file_persistent_id.rsplit("/", 1)[0]
if file_persistent_id == dataset_persistent_id:
# We can't figure this one out, throw an error
@ -115,6 +115,38 @@ class Dataverse(DoiProvider):
raise ValueError(f"Could not determine persistent id for dataverse URL {url}")
def get_datafiles(self, host: str, persistent_id: str) -> list[dict]:
"""
Return a list of dataFiles for given persistent_id
"""
dataset_url = f"{host}/api/datasets/:persistentId?persistentId={persistent_id}"
resp = self._request(dataset_url, headers={"accept": "application/json"})
# Assume it's a dataset
is_dataset = True
if resp.status_code == 404:
# It's possible this is a *file* persistent_id, not a dataset one
file_url = f"{host}/api/files/:persistentId?persistentId={persistent_id}"
resp = self._request(file_url, headers={"accept": "application/json"})
if resp.status_code == 404:
# This persistent id is just not here
raise ValueError(f"{persistent_id} on {host} is not found")
# It's not a dataset, it's a file!
is_dataset = False
# We already handled 404, raise error for everything else
resp.raise_for_status()
data = resp.json()["data"]
if is_dataset:
return data["latestVersion"]["files"]
else:
# Only one file object
return [data]
def fetch(self, spec, output_dir, yield_output=False):
"""Fetch and unpack a Dataverse dataset."""
url = spec["url"]
@ -123,13 +155,8 @@ class Dataverse(DoiProvider):
persistent_id = self.get_persistent_id_from_url(url)
yield f"Fetching Dataverse record {persistent_id}.\n"
url = f'{host["url"]}/api/datasets/:persistentId?persistentId={persistent_id}'
resp = self.urlopen(url, headers={"accept": "application/json"})
print(resp.json())
record = resp.json()["data"]
for fobj in deep_get(record, "latestVersion.files"):
for fobj in self.get_datafiles(host["url"], persistent_id):
file_url = (
# without format=original you get the preservation format (plain text, tab separated)
f'{host["url"]}/api/access/datafile/{deep_get(fobj, "dataFile.id")}?format=original'
@ -155,7 +182,6 @@ class Dataverse(DoiProvider):
copytree(os.path.join(output_dir, d), output_dir)
shutil.rmtree(os.path.join(output_dir, d))
# Save persistent id
self.persitent_id = persistent_id

113
tests/contentproviders/test_dataverse.py
Wyświetl plik

@ -10,19 +10,50 @@ test_dv = Dataverse()
harvard_dv = next(_ for _ in test_dv.hosts if _["name"] == "Harvard Dataverse")
cimmyt_dv = next(_ for _ in test_dv.hosts if _["name"] == "CIMMYT Research Data")
@pytest.mark.parametrize(
("doi", "resolved"),
[
("doi:10.7910/DVN/6ZXAGT/3YRRYJ", {"host": harvard_dv, "url": "https://dataverse.harvard.edu/file.xhtml?persistentId=doi:10.7910/DVN/6ZXAGT/3YRRYJ"}),
("10.7910/DVN/6ZXAGT/3YRRYJ", {"host": harvard_dv, "url": "https://dataverse.harvard.edu/file.xhtml?persistentId=doi:10.7910/DVN/6ZXAGT/3YRRYJ"}),
("10.7910/DVN/TJCLKP", {"host": harvard_dv, "url": "https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/TJCLKP"}),
("https://dataverse.harvard.edu/api/access/datafile/3323458", {"host": harvard_dv, "url": "https://dataverse.harvard.edu/api/access/datafile/3323458"}),
("https://data.cimmyt.org/dataset.xhtml?persistentId=hdl:11529/10016", {"host": cimmyt_dv, "url": "https://data.cimmyt.org/dataset.xhtml?persistentId=hdl:11529/10016"}),
(
"doi:10.7910/DVN/6ZXAGT/3YRRYJ",
{
"host": harvard_dv,
"url": "https://dataverse.harvard.edu/file.xhtml?persistentId=doi:10.7910/DVN/6ZXAGT/3YRRYJ",
},
),
(
"10.7910/DVN/6ZXAGT/3YRRYJ",
{
"host": harvard_dv,
"url": "https://dataverse.harvard.edu/file.xhtml?persistentId=doi:10.7910/DVN/6ZXAGT/3YRRYJ",
},
),
(
"10.7910/DVN/TJCLKP",
{
"host": harvard_dv,
"url": "https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/TJCLKP",
},
),
(
"https://dataverse.harvard.edu/api/access/datafile/3323458",
{
"host": harvard_dv,
"url": "https://dataverse.harvard.edu/api/access/datafile/3323458",
},
),
(
"https://data.cimmyt.org/dataset.xhtml?persistentId=hdl:11529/10016",
{
"host": cimmyt_dv,
"url": "https://data.cimmyt.org/dataset.xhtml?persistentId=hdl:11529/10016",
},
),
("/some/random/string", None),
("https://example.com/path/here", None),
# Non dataverse DOIs
("https://doi.org/10.21105/joss.01277", None)
]
("https://doi.org/10.21105/joss.01277", None),
],
)
def test_detect(doi, resolved):
assert Dataverse().detect(doi) == resolved
@ -31,37 +62,61 @@ def test_detect(doi, resolved):
@pytest.mark.parametrize(
("url", "persistent_id"),
[
("https://dataverse.harvard.edu/file.xhtml?persistentId=doi:10.7910/DVN/6ZXAGT/3YRRYJ", "doi:10.7910/DVN/6ZXAGT"),
("https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/TJCLKP", "doi:10.7910/DVN/TJCLKP"),
("https://dataverse.harvard.edu/api/access/datafile/3323458", "doi:10.7910/DVN/3MJ7IR"),
("https://data.cimmyt.org/dataset.xhtml?persistentId=hdl:11529/10016", "hdl:11529/10016"),
]
(
"https://dataverse.harvard.edu/file.xhtml?persistentId=doi:10.7910/DVN/6ZXAGT/3YRRYJ",
"doi:10.7910/DVN/6ZXAGT",
),
(
"https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/TJCLKP",
"doi:10.7910/DVN/TJCLKP",
),
(
"https://dataverse.harvard.edu/api/access/datafile/3323458",
"doi:10.7910/DVN/3MJ7IR",
),
(
"https://data.cimmyt.org/dataset.xhtml?persistentId=hdl:11529/10016",
"hdl:11529/10016",
),
],
)
def test_get_persistent_id(url, persistent_id):
assert Dataverse().get_persistent_id_from_url(url) == persistent_id
def test_dataverse_fetch():
@pytest.mark.parametrize(
("spec", "md5tree"),
[
(
"doi:10.7910/DVN/TJCLKP",
{
"data/primary/primary-data.zip": "a8f6fc3fc58f503cd48e23fa8b088694",
"data/2023-01-03.tsv": "6fd497bf13dab9a06fe737ebc22f1917",
"code/language.py": "9d61582bcf497c83bbd1ed0eed3c772e",
},
),
(
# A citation targeting a single file
"https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/6ZXAGT/3YRRYJ",
{
"ARCHAEOGLOBE_CONSENSUS_ASSESSMENT.tab": "17a91888ed8e91dfb63acbbab6127ac5"
}
)
],
)
def test_fetch(spec, md5tree):
dv = Dataverse()
spec = dv.detect("doi:10.7910/DVN/TJCLKP")
with TemporaryDirectory() as d:
output = []
for l in dv.fetch(spec, d):
for l in dv.fetch(dv.detect(spec), d):
output.append(l)
# Verify two directories
assert set(os.listdir(d)) == {"data", "code"}
# Verify sha256sum of three files
expected_sha = {
'data/primary/primary-data.zip': '880f99a1e1d54a2553be61301f92e06b29236785b8d4d1b7ad0b4595d9d7512b',
'data/2023-01-03.tsv': 'cc9759e8e6bc076dd7c1a8eb53a7ea3d38e8697fa9f544d15768db308516cc5f',
'code/language.py': '1ffb3b3cdc9de01279779f3fc88824672c8ec3ab1c41ecdd5c1b59a9b0202215'
}
for subpath, expected_sha in expected_sha.items():
with open(os.path.join(d, subpath), 'rb') as f:
h = hashlib.sha256()
# Verify md5 sum of the files we expect to find
# We are using md5 instead of something more secure because that is what
# dataverse itself uses
for subpath, expected_sha in md5tree.items():
with open(os.path.join(d, subpath), "rb") as f:
h = hashlib.md5()
h.update(f.read())
assert h.hexdigest() == expected_sha
assert h.hexdigest() == expected_sha