def filter_granted(self, queryset):
""" Filter a queryset to only include records explicitly granted.
"""
return Dataset.filter_by_user(self.request.user)
def filter_granted(self, queryset):
""" Filter a queryset to only include records explicitly granted.
"""
return Dataset.filter_by_user(self.request.user)
def dataset_view(request, dataset_id):
"""
Display the file associated with the dataset in the browser, or update its name/description.
"""
return_to_run = request.GET.get('run_id', None)
is_view_results = "view_results" in request.GET
is_view_run = "view_run" in request.GET
return_url = reverse("datasets")
if return_to_run is not None:
if is_view_run:
return_url = reverse('view_run', kwargs={'run_id': return_to_run})
elif is_view_results:
return_url = reverse('view_results', kwargs={'run_id': return_to_run})
try:
if admin_check(request.user):
accessible_datasets = Dataset.objects
else:
accessible_datasets = Dataset.filter_by_user(request.user)
dataset = accessible_datasets.prefetch_related(
'structure',
'structure__compounddatatype',
'structure__compounddatatype__members',
'structure__compounddatatype__members__datatype',
'structure__compounddatatype__members__datatype__basic_constraints'
).get(pk=dataset_id)
except ObjectDoesNotExist:
raise Http404("ID {} cannot be accessed".format(dataset_id))
# Figure out which users and groups could be given access to this Dataset.
# If the Dataset is uploaded, it's anyone who doesn't already have access;
# if it was generated, it's anyone who had access to the generating run.
addable_users, addable_groups = dataset.other_users_groups()
if dataset.file_source is None:
generating_run = None
else:
generating_run = dataset.file_source.top_level_run
container_dataset = dataset.containers.filter(argument__type='O').first() # Output from which runs?
if container_dataset is None:
container_run = None
else:
container_run = container_dataset.run
inputs_count = dataset.containers.filter(
argument__type='I').values('run_id').distinct().count()
if request.method == "POST":
# We are going to try and update this Dataset.
dataset_form = DatasetDetailsForm(
request.POST,
access_limits=dataset.get_access_limits(),
instance=dataset
)
try:
if dataset_form.is_valid():
dataset.name = dataset_form.cleaned_data["name"]
dataset.description = dataset_form.cleaned_data["description"]
dataset.clean()
dataset.save()
with transaction.atomic():
dataset.grant_from_json(dataset_form.cleaned_data["permissions"])
dataset.validate_restrict_access(dataset.get_access_limits())
return HttpResponseRedirect(return_url)
except (AttributeError, ValidationError, ValueError) as e:
LOGGER.exception(e.message)
dataset_form.add_error(None, e)
else:
# A DatasetForm which we can use to make submission and editing easier.
dataset_form = DatasetDetailsForm(
access_limits=dataset.get_access_limits(),
initial={"name": dataset.name, "description": dataset.description}
)
c = {
"is_admin": admin_check(request.user),
"is_owner": dataset.user == request.user,
"dataset": dataset,
"return": return_url,
"dataset_form": dataset_form,
"generating_run": generating_run,
"inputs_count": inputs_count,
"container_run": container_run
}
if not dataset.has_data():
t = loader.get_template("librarian/missing_dataset_view.html")
if dataset.external_path:
c["missing_data_message"] = "This dataset's external file is missing or has "\
"been modified (MD5 mismatch). " \
"Please consult your system administrator if this is unexpected."
elif dataset.is_redacted():
c["missing_data_message"] = "Data has been redacted."
else:
c["missing_data_message"] = "Data was not retained or has been purged."
rendered_response = t.render(c, request)
elif dataset.is_raw():
t = loader.get_template("librarian/raw_dataset_view.html")
# Test whether this is a binary file or not.
# Read 1000 characters.
data_handle = dataset.get_open_file_handle('r')
if data_handle is None:
c["missing_data_message"] = "Data has been removed or renamed."
else:
with data_handle:
sample_content = data_handle.read(1000)
c.update({"sample_content": sample_content})
c["is_binary"] = False
try:
rendered_response = t.render(c, request)
except DjangoUnicodeDecodeError as e:
c["is_binary"] = True
del c["sample_content"]
rendered_response = t.render(c, request)
else:
extra_errors = []
# If we have a mismatched output, we do an alignment
# over the columns.
if dataset.content_matches_header:
col_matching, processed_rows = None, dataset.rows(
True,
limit=settings.DATASET_DISPLAY_MAX,
extra_errors=extra_errors)
else:
col_matching, insert = dataset.column_alignment()
processed_rows = dataset.rows(data_check=True,
insert_at=insert,
limit=settings.DATASET_DISPLAY_MAX,
extra_errors=extra_errors)
t = loader.get_template("librarian/csv_dataset_view.html")
processed_rows = list(processed_rows)
c.update(
{
'column_matching': col_matching,
'processed_rows': processed_rows,
'extra_errors': extra_errors,
"are_rows_truncated": len(processed_rows) >= settings.DATASET_DISPLAY_MAX
}
)
rendered_response = t.render(c, request)
return HttpResponse(rendered_response)
def dataset_view(request, dataset_id):
"""
Display the file associated with the dataset in the browser, or update its name/description.
"""
return_url = reverse("datasets")
try:
if admin_check(request.user):
accessible_datasets = Dataset.objects
else:
accessible_datasets = Dataset.filter_by_user(request.user)
dataset = accessible_datasets.get(pk=dataset_id)
except ObjectDoesNotExist:
raise Http404("ID {} cannot be accessed".format(dataset_id))
# Figure out which users and groups could be given access to this Dataset.
# If the Dataset is uploaded, it's anyone who doesn't already have access;
# if it was generated, it's anyone who had access to the generating run.
addable_users, addable_groups = dataset.other_users_groups()
generating_run = None
container_dataset = dataset.containers.filter(
argument__type='O').first() # Output from which runs?
if container_dataset is None:
container_run = None
else:
container_run = container_dataset.run
inputs_count = dataset.containers.filter(
argument__type='I').values('run_id').distinct().count()
if request.method == "POST":
# We are going to try and update this Dataset.
dataset_form = DatasetDetailsForm(
request.POST,
access_limits=dataset.get_access_limits(),
instance=dataset)
try:
if dataset_form.is_valid():
dataset.name = dataset_form.cleaned_data["name"]
dataset.description = dataset_form.cleaned_data["description"]
dataset.clean()
dataset.save()
with transaction.atomic():
dataset.grant_from_json(
dataset_form.cleaned_data["permissions"])
dataset.validate_restrict_access(
dataset.get_access_limits())
return HttpResponseRedirect(return_url)
except (AttributeError, ValidationError, ValueError) as e:
LOGGER.exception(e.message)
dataset_form.add_error(None, e)
else:
# A DatasetForm which we can use to make submission and editing easier.
dataset_form = DatasetDetailsForm(
access_limits=dataset.get_access_limits(),
initial={
"name": dataset.name,
"description": dataset.description
})
c = {
"is_admin": admin_check(request.user),
"is_owner": dataset.user == request.user,
"dataset": dataset,
"return": return_url,
"dataset_form": dataset_form,
"generating_run": generating_run,
"inputs_count": inputs_count,
"container_run": container_run
}
if not dataset.has_data():
t = loader.get_template("librarian/missing_dataset_view.html")
if dataset.external_path:
c["missing_data_message"] = "This dataset's external file is missing or has "\
"been modified (MD5 mismatch). " \
"Please consult your system administrator if this is unexpected."
elif dataset.is_redacted():
c["missing_data_message"] = "Data has been redacted."
else:
c["missing_data_message"] = "Data was not retained or has been purged."
rendered_response = t.render(c, request)
else:
t = loader.get_template("librarian/raw_dataset_view.html")
# Test whether this is a binary file or not.
# Read 1000 characters.
data_handle = dataset.get_open_file_handle('r')
if data_handle is None:
c["missing_data_message"] = "Data has been removed or renamed."
else:
with data_handle:
sample_content = data_handle.read(1000)
c.update({"sample_content": sample_content})
c["is_binary"] = False
try:
rendered_response = t.render(c, request)
except DjangoUnicodeDecodeError:
c["is_binary"] = True
del c["sample_content"]
rendered_response = t.render(c, request)
return HttpResponse(rendered_response)
def dataset_view(request, dataset_id):
"""
Display the file associated with the dataset in the browser, or update its name/description.
"""
return_to_run = request.GET.get('run_id', None)
is_view_results = "view_results" in request.GET
is_view_run = "view_run" in request.GET
return_url = reverse("datasets")
if return_to_run is not None:
if is_view_run:
return_url = reverse('view_run', kwargs={'run_id': return_to_run})
elif is_view_results:
return_url = reverse('view_results',
kwargs={'run_id': return_to_run})
try:
if admin_check(request.user):
accessible_datasets = Dataset.objects
else:
accessible_datasets = Dataset.filter_by_user(request.user)
dataset = accessible_datasets.prefetch_related(
'structure', 'structure__compounddatatype',
'structure__compounddatatype__members',
'structure__compounddatatype__members__datatype',
'structure__compounddatatype__members__datatype__basic_constraints'
).get(pk=dataset_id)
except ObjectDoesNotExist:
raise Http404("ID {} cannot be accessed".format(dataset_id))
# Figure out which users and groups could be given access to this Dataset.
# If the Dataset is uploaded, it's anyone who doesn't already have access;
# if it was generated, it's anyone who had access to the generating run.
addable_users, addable_groups = dataset.other_users_groups()
if dataset.file_source is None:
generating_run = None
else:
generating_run = dataset.file_source.top_level_run
container_dataset = dataset.containers.filter(
argument__type='O').first() # Output from which runs?
if container_dataset is None:
container_run = None
else:
container_run = container_dataset.run
inputs_count = dataset.containers.filter(
argument__type='I').values('run_id').distinct().count()
if request.method == "POST":
# We are going to try and update this Dataset.
dataset_form = DatasetDetailsForm(
request.POST,
access_limits=dataset.get_access_limits(),
instance=dataset)
try:
if dataset_form.is_valid():
dataset.name = dataset_form.cleaned_data["name"]
dataset.description = dataset_form.cleaned_data["description"]
dataset.clean()
dataset.save()
with transaction.atomic():
dataset.grant_from_json(
dataset_form.cleaned_data["permissions"])
dataset.validate_restrict_access(
dataset.get_access_limits())
return HttpResponseRedirect(return_url)
except (AttributeError, ValidationError, ValueError) as e:
LOGGER.exception(e.message)
dataset_form.add_error(None, e)
else:
# A DatasetForm which we can use to make submission and editing easier.
dataset_form = DatasetDetailsForm(
access_limits=dataset.get_access_limits(),
initial={
"name": dataset.name,
"description": dataset.description
})
c = {
"is_admin": admin_check(request.user),
"is_owner": dataset.user == request.user,
"dataset": dataset,
"return": return_url,
"dataset_form": dataset_form,
"generating_run": generating_run,
"inputs_count": inputs_count,
"container_run": container_run
}
if not dataset.has_data():
t = loader.get_template("librarian/missing_dataset_view.html")
if dataset.external_path:
c["missing_data_message"] = "This dataset's external file is missing or has "\
"been modified (MD5 mismatch). " \
"Please consult your system administrator if this is unexpected."
elif dataset.is_redacted():
c["missing_data_message"] = "Data has been redacted."
else:
c["missing_data_message"] = "Data was not retained or has been purged."
rendered_response = t.render(c, request)
elif dataset.is_raw():
t = loader.get_template("librarian/raw_dataset_view.html")
# Test whether this is a binary file or not.
# Read 1000 characters.
data_handle = dataset.get_open_file_handle('r')
if data_handle is None:
c["missing_data_message"] = "Data has been removed or renamed."
else:
with data_handle:
sample_content = data_handle.read(1000)
c.update({"sample_content": sample_content})
c["is_binary"] = False
try:
rendered_response = t.render(c, request)
except DjangoUnicodeDecodeError as e:
c["is_binary"] = True
del c["sample_content"]
rendered_response = t.render(c, request)
else:
extra_errors = []
# If we have a mismatched output, we do an alignment
# over the columns.
if dataset.content_matches_header:
col_matching, processed_rows = None, dataset.rows(
True,
limit=settings.DATASET_DISPLAY_MAX,
extra_errors=extra_errors)
else:
col_matching, insert = dataset.column_alignment()
processed_rows = dataset.rows(data_check=True,
insert_at=insert,
limit=settings.DATASET_DISPLAY_MAX,
extra_errors=extra_errors)
t = loader.get_template("librarian/csv_dataset_view.html")
processed_rows = list(processed_rows)
c.update({
'column_matching':
col_matching,
'processed_rows':
processed_rows,
'extra_errors':
extra_errors,
"are_rows_truncated":
len(processed_rows) >= settings.DATASET_DISPLAY_MAX
})
rendered_response = t.render(c, request)
return HttpResponse(rendered_response)