def run(self, query, task_status_id, filename=None, *args, **kwargs):
"""
Execute export.
"""
from panda.models import Dataset, TaskStatus
log = logging.getLogger(self.name)
log.info('Beginning export, query: %s' % query)
task_status = TaskStatus.objects.get(id=task_status_id)
task_status.begin('Preparing to import')
if not filename:
filename = 'search_export_%s' % (now().isoformat())
zip_name = '%s.zip' % filename
path = os.path.join(settings.EXPORT_ROOT, filename)
zip_path = os.path.join(settings.EXPORT_ROOT, zip_name)
try:
os.makedirs(os.path.realpath(path))
except:
pass
zipfile = ZipFile(zip_path, 'w')
response = solr.query_grouped(settings.SOLR_DATA_CORE,
query,
'dataset_slug',
offset=0,
limit=1000,
group_limit=0,
group_offset=0)
groups = response['grouped']['dataset_slug']['groups']
datasets = {}
for group in groups:
dataset_slug = group['groupValue']
count = group['doclist']['numFound']
datasets[dataset_slug] = count
total_n = 0
throttle = config_value('PERF', 'TASK_THROTTLE')
for dataset_slug in datasets:
try:
dataset = Dataset.objects.get(slug=dataset_slug)
except Dataset.DoesNotExist:
log.warning(
'Skipping part of export due to Dataset being deleted, dataset_slug: %s'
% dataset_slug)
continue
filename = '%s.csv' % dataset_slug
file_path = os.path.join(path, filename)
f = open(file_path, 'w')
writer = CSVKitWriter(f)
# Header
writer.writerow([c['name'] for c in dataset.column_schema])
response = solr.query(settings.SOLR_DATA_CORE,
query,
offset=0,
limit=0)
# Update dataset and total counts for progress tracking
datasets[dataset_slug] = response['response']['numFound']
total_count = sum(datasets.values())
n = 0
while n < datasets[dataset_slug]:
response = solr.query(settings.SOLR_DATA_CORE,
'dataset_slug: %s %s' %
(dataset_slug, query),
offset=n,
limit=SOLR_PAGE_SIZE)
results = response['response']['docs']
for row in results:
data = json.loads(row['data'])
writer.writerow(data)
task_status.update(
'%.0f%% complete' %
floor(float(total_n) / float(total_count) * 100))
if self.is_aborted():
task_status.abort(
'Aborted after exporting %.0f%%' %
floor(float(total_n) / float(total_count) * 100))
log.warning('Export aborted, query: %s' % query)
return
n += SOLR_PAGE_SIZE
total_n += response['response']['numFound']
time.sleep(throttle)
f.close()
# Add to zip and nuke temp file
zipfile.write(file_path, filename)
os.remove(file_path)
# Finish zip file and nuke temp directory
zipfile.close()
os.rmdir(path)
task_status.update('100% complete')
log.info('Finished export, query: %s' % query)
return zip_name
def search_all_data(self, request, **kwargs):
"""
List endpoint using Solr. Provides full-text search via the "q" parameter."
"""
self.method_check(request, allowed=["get"])
self.is_authenticated(request)
self.throttle_check(request)
query = request.GET.get("q", "")
category = request.GET.get("category", "")
since = request.GET.get("since", None)
limit = int(request.GET.get("limit", settings.PANDA_DEFAULT_SEARCH_GROUPS))
offset = int(request.GET.get("offset", 0))
group_limit = int(request.GET.get("group_limit", settings.PANDA_DEFAULT_SEARCH_ROWS_PER_GROUP))
group_offset = int(request.GET.get("group_offset", 0))
export = bool(request.GET.get("export", False))
if category:
if category != "uncategorized":
category = Category.objects.get(slug=category)
dataset_slugs = category.datasets.values_list("slug", flat=True)
else:
dataset_slugs = Dataset.objects.filter(categories=None).values_list("slug", flat=True)
query += " dataset_slug:(%s)" % " ".join(dataset_slugs)
if since:
query = "last_modified:[" + since + "Z TO *] AND (%s)" % query
# Because users may have authenticated via headers the request.user may
# not be a full User instance. To be sure, we fetch one.
user = UserProxy.objects.get(id=request.user.id)
if export:
task_type = ExportSearchTask
task = TaskStatus.objects.create(
task_name=task_type.name, task_description='Export search results for "%s".' % query, creator=user
)
task_type.apply_async(args=[query, task.id], kwargs={}, task_id=task.id)
else:
response = solr.query_grouped(
settings.SOLR_DATA_CORE,
query,
"dataset_slug",
offset=offset,
limit=limit,
group_limit=group_limit,
group_offset=group_offset,
)
groups = response["grouped"]["dataset_slug"]["groups"]
page = PandaPaginator(
request.GET,
groups,
resource_uri=request.path_info,
count=response["grouped"]["dataset_slug"]["ngroups"],
).page()
datasets = []
for group in groups:
dataset_slug = group["groupValue"]
results = group["doclist"]
try:
dataset = Dataset.objects.get(slug=dataset_slug)
# In the event that stale data exists in Solr, skip this dataset,
# request the invalid data be purged and return the other results.
# Pagination may be wrong, but this is the most functional solution. (#793)
except Dataset.DoesNotExist:
PurgeDataTask.apply_async(args=[dataset_slug])
solr.delete(settings.SOLR_DATASETS_CORE, "slug:%s" % dataset_slug)
page["meta"]["total_count"] -= 1
continue
dataset_resource = DatasetResource()
dataset_bundle = dataset_resource.build_bundle(obj=dataset, request=request)
dataset_bundle = dataset_resource.full_dehydrate(dataset_bundle)
dataset_bundle = dataset_resource.simplify_bundle(dataset_bundle)
objects = [SolrObject(obj) for obj in results["docs"]]
dataset_search_url = reverse(
"api_dataset_data_list",
kwargs={
"api_name": self._meta.api_name,
"dataset_resource_name": "dataset",
"resource_name": "data",
"dataset_slug": dataset.slug,
},
)
data_page = PandaPaginator(
{"limit": str(group_limit), "offset": str(group_offset), "q": query},
objects,
resource_uri=dataset_search_url,
count=results["numFound"],
).page()
dataset_bundle.data.update(data_page)
dataset_bundle.data["objects"] = []
for obj in objects:
data_bundle = self.build_bundle(obj=obj, request=request)
data_bundle = self.full_dehydrate(data_bundle)
dataset_bundle.data["objects"].append(data_bundle)
datasets.append(dataset_bundle.data)
page["objects"] = datasets
# Log query
SearchLog.objects.create(user=user, dataset=None, query=query)
self.log_throttled_access(request)
if export:
return self.create_response(request, "Export queued.")
else:
return self.create_response(request, page)
def run(self, query, task_status_id, filename=None, *args, **kwargs):
"""
Execute export.
"""
from panda.models import Dataset, TaskStatus
log = logging.getLogger(self.name)
log.info('Beginning export, query: %s' % query)
task_status = TaskStatus.objects.get(id=task_status_id)
task_status.begin('Preparing to import')
if not filename:
filename = 'search_export_%s' % (now().isoformat())
zip_name = '%s.zip' % filename
path = os.path.join(settings.EXPORT_ROOT, filename)
zip_path = os.path.join(settings.EXPORT_ROOT, zip_name)
try:
os.makedirs(os.path.realpath(path))
except:
pass
zipfile = ZipFile(zip_path, 'w')
response = solr.query_grouped(
settings.SOLR_DATA_CORE,
query,
'dataset_slug',
offset=0,
limit=1000,
group_limit=0,
group_offset=0
)
groups = response['grouped']['dataset_slug']['groups']
datasets = {}
for group in groups:
dataset_slug = group['groupValue']
count = group['doclist']['numFound']
datasets[dataset_slug] = count
total_n = 0
throttle = config_value('PERF', 'TASK_THROTTLE')
for dataset_slug in datasets:
try:
dataset = Dataset.objects.get(slug=dataset_slug)
except Dataset.DoesNotExist:
log.warning('Skipping part of export due to Dataset being deleted, dataset_slug: %s' % dataset_slug)
continue
filename = '%s.csv' % dataset_slug
file_path = os.path.join(path, filename)
f = open(file_path, 'w')
writer = CSVKitWriter(f)
# Header
writer.writerow([c['name'] for c in dataset.column_schema])
response = solr.query(
settings.SOLR_DATA_CORE,
query,
offset=0,
limit=0
)
# Update dataset and total counts for progress tracking
datasets[dataset_slug] = response['response']['numFound']
total_count = sum(datasets.values())
n = 0
while n < datasets[dataset_slug]:
response = solr.query(
settings.SOLR_DATA_CORE,
'dataset_slug: %s %s' % (dataset_slug, query),
offset=n,
limit=SOLR_PAGE_SIZE
)
results = response['response']['docs']
for row in results:
data = json.loads(row['data'])
writer.writerow(data)
task_status.update('%.0f%% complete' % floor(float(total_n) / float(total_count) * 100))
if self.is_aborted():
task_status.abort('Aborted after exporting %.0f%%' % floor(float(total_n) / float(total_count) * 100))
log.warning('Export aborted, query: %s' % query)
return
n += SOLR_PAGE_SIZE
total_n += response['response']['numFound']
time.sleep(throttle)
f.close()
# Add to zip and nuke temp file
zipfile.write(file_path, filename)
os.remove(file_path)
# Finish zip file and nuke temp directory
zipfile.close()
os.rmdir(path)
task_status.update('100% complete')
log.info('Finished export, query: %s' % query)
return zip_name
def search_all_data(self, request, **kwargs):
"""
List endpoint using Solr. Provides full-text search via the "q" parameter."
"""
self.method_check(request, allowed=['get'])
self.is_authenticated(request)
self.throttle_check(request)
query = request.GET.get('q', '')
limit = int(request.GET.get('limit', settings.PANDA_DEFAULT_SEARCH_GROUPS))
offset = int(request.GET.get('offset', 0))
group_limit = int(request.GET.get('group_limit', settings.PANDA_DEFAULT_SEARCH_ROWS_PER_GROUP))
group_offset = int(request.GET.get('group_offset', 0))
response = solr.query_grouped(
settings.SOLR_DATA_CORE,
query,
'dataset_slug',
offset=offset,
limit=limit,
group_limit=group_limit,
group_offset=group_offset
)
groups = response['grouped']['dataset_slug']['groups']
page = PandaPaginator(
request.GET,
groups,
resource_uri=request.path_info,
count=response['grouped']['dataset_slug']['ngroups']
).page()
datasets = []
for group in groups:
dataset_slug = group['groupValue']
results = group['doclist']
dataset_resource = DatasetResource()
dataset = Dataset.objects.get(slug=dataset_slug)
dataset_bundle = dataset_resource.build_bundle(obj=dataset, request=request)
dataset_bundle = dataset_resource.full_dehydrate(dataset_bundle)
dataset_bundle = dataset_resource.simplify_bundle(dataset_bundle)
objects = [SolrObject(obj) for obj in results['docs']]
dataset_search_url = reverse('api_dataset_data_list', kwargs={ 'api_name': self._meta.api_name, 'dataset_resource_name': 'dataset', 'resource_name': 'data', 'dataset_slug': dataset.slug })
data_page = PandaPaginator(
{ 'limit': str(group_limit), 'offset': str(group_offset), 'q': query },
objects,
resource_uri=dataset_search_url,
count=results['numFound']
).page()
dataset_bundle.data.update(data_page)
dataset_bundle.data['objects'] = []
for obj in objects:
data_bundle = self.build_bundle(obj=obj, request=request)
data_bundle = self.full_dehydrate(data_bundle)
dataset_bundle.data['objects'].append(data_bundle)
datasets.append(dataset_bundle.data)
page['objects'] = datasets
self.log_throttled_access(request)
return self.create_response(request, page)
def search_all_data(self, request, **kwargs):
"""
List endpoint using Solr. Provides full-text search via the "q" parameter."
"""
self.method_check(request, allowed=['get'])
self.is_authenticated(request)
self.throttle_check(request)
query = request.GET.get('q', '')
category = request.GET.get('category', '')
since = request.GET.get('since', None)
limit = int(
request.GET.get('limit', settings.PANDA_DEFAULT_SEARCH_GROUPS))
offset = int(request.GET.get('offset', 0))
group_limit = int(
request.GET.get('group_limit',
settings.PANDA_DEFAULT_SEARCH_ROWS_PER_GROUP))
group_offset = int(request.GET.get('group_offset', 0))
export = bool(request.GET.get('export', False))
if category:
if category != 'uncategorized':
category = Category.objects.get(slug=category)
dataset_slugs = category.datasets.values_list('slug',
flat=True)
else:
dataset_slugs = Dataset.objects.filter(
categories=None).values_list('slug', flat=True)
query += ' dataset_slug:(%s)' % ' '.join(dataset_slugs)
if since:
query = 'last_modified:[' + since + 'Z TO *] AND (%s)' % query
# Because users may have authenticated via headers the request.user may
# not be a full User instance. To be sure, we fetch one.
user = UserProxy.objects.get(id=request.user.id)
if export:
task_type = ExportSearchTask
task = TaskStatus.objects.create(
task_name=task_type.name,
task_description='Export search results for "%s".' % query,
creator=user)
task_type.apply_async(args=[query, task.id],
kwargs={},
task_id=task.id)
else:
response = solr.query_grouped(settings.SOLR_DATA_CORE,
query,
'dataset_slug',
offset=offset,
limit=limit,
group_limit=group_limit,
group_offset=group_offset)
groups = response['grouped']['dataset_slug']['groups']
page = PandaPaginator(
request.GET,
groups,
resource_uri=request.path_info,
count=response['grouped']['dataset_slug']['ngroups']).page()
datasets = []
for group in groups:
dataset_slug = group['groupValue']
results = group['doclist']
try:
dataset = Dataset.objects.get(slug=dataset_slug)
# In the event that stale data exists in Solr, skip this dataset,
# request the invalid data be purged and return the other results.
# Pagination may be wrong, but this is the most functional solution. (#793)
except Dataset.DoesNotExist:
PurgeDataTask.apply_async(args=[dataset_slug])
solr.delete(settings.SOLR_DATASETS_CORE,
'slug:%s' % dataset_slug)
page['meta']['total_count'] -= 1
continue
dataset_resource = DatasetResource()
dataset_bundle = dataset_resource.build_bundle(obj=dataset,
request=request)
dataset_bundle = dataset_resource.full_dehydrate(
dataset_bundle)
dataset_bundle = dataset_resource.simplify_bundle(
dataset_bundle)
objects = [SolrObject(obj) for obj in results['docs']]
dataset_search_url = reverse('api_dataset_data_list',
kwargs={
'api_name':
self._meta.api_name,
'dataset_resource_name':
'dataset',
'resource_name': 'data',
'dataset_slug': dataset.slug
})
data_page = PandaPaginator(
{
'limit': str(group_limit),
'offset': str(group_offset),
'q': query
},
objects,
resource_uri=dataset_search_url,
count=results['numFound']).page()
dataset_bundle.data.update(data_page)
dataset_bundle.data['objects'] = []
for obj in objects:
data_bundle = self.build_bundle(obj=obj, request=request)
data_bundle = self.full_dehydrate(data_bundle)
dataset_bundle.data['objects'].append(data_bundle)
datasets.append(dataset_bundle.data)
page['objects'] = datasets
# Log query
SearchLog.objects.create(user=user, dataset=None, query=query)
self.log_throttled_access(request)
if export:
return self.create_response(request, 'Export queued.')
else:
return self.create_response(request, page)
def search_all_data(self, request, **kwargs):
"""
List endpoint using Solr. Provides full-text search via the "q" parameter."
"""
self.method_check(request, allowed=["get"])
self.is_authenticated(request)
self.throttle_check(request)
query = request.GET.get("q", "")
limit = int(request.GET.get("limit", settings.PANDA_DEFAULT_SEARCH_GROUPS))
offset = int(request.GET.get("offset", 0))
group_limit = int(request.GET.get("group_limit", settings.PANDA_DEFAULT_SEARCH_ROWS_PER_GROUP))
group_offset = int(request.GET.get("group_offset", 0))
response = solr.query_grouped(
settings.SOLR_DATA_CORE,
query,
"dataset_slug",
offset=offset,
limit=limit,
group_limit=group_limit,
group_offset=group_offset,
)
groups = response["grouped"]["dataset_slug"]["groups"]
page = PandaPaginator(
request.GET, groups, resource_uri=request.path_info, count=response["grouped"]["dataset_slug"]["ngroups"]
).page()
datasets = []
for group in groups:
dataset_slug = group["groupValue"]
results = group["doclist"]
dataset_resource = DatasetResource()
dataset = Dataset.objects.get(slug=dataset_slug)
dataset_bundle = dataset_resource.build_bundle(obj=dataset, request=request)
dataset_bundle = dataset_resource.full_dehydrate(dataset_bundle)
dataset_bundle = dataset_resource.simplify_bundle(dataset_bundle)
objects = [SolrObject(obj) for obj in results["docs"]]
dataset_search_url = reverse(
"api_dataset_data_list",
kwargs={
"api_name": self._meta.api_name,
"dataset_resource_name": "dataset",
"resource_name": "data",
"dataset_slug": dataset.slug,
},
)
data_page = PandaPaginator(
{"limit": str(group_limit), "offset": str(group_offset), "q": query},
objects,
resource_uri=dataset_search_url,
count=results["numFound"],
).page()
dataset_bundle.data.update(data_page)
dataset_bundle.data["objects"] = []
for obj in objects:
data_bundle = self.build_bundle(obj=obj, request=request)
data_bundle = self.full_dehydrate(data_bundle)
dataset_bundle.data["objects"].append(data_bundle)
datasets.append(dataset_bundle.data)
page["objects"] = datasets
self.log_throttled_access(request)
return self.create_response(request, page)
def search_all_data(self, request, **kwargs):
"""
List endpoint using Solr. Provides full-text search via the "q" parameter."
"""
self.method_check(request, allowed=['get'])
self.is_authenticated(request)
self.throttle_check(request)
query = request.GET.get('q', '')
category = request.GET.get('category', '')
since = request.GET.get('since', None)
limit = int(request.GET.get('limit', settings.PANDA_DEFAULT_SEARCH_GROUPS))
offset = int(request.GET.get('offset', 0))
group_limit = int(request.GET.get('group_limit', settings.PANDA_DEFAULT_SEARCH_ROWS_PER_GROUP))
group_offset = int(request.GET.get('group_offset', 0))
if category:
if category != 'uncategorized':
category = Category.objects.get(slug=category)
dataset_slugs = category.datasets.values_list('slug', flat=True)
else:
dataset_slugs = Dataset.objects.filter(categories=None).values_list('slug', flat=True)
query += ' dataset_slug:(%s)' % ' '.join(dataset_slugs)
if since:
query = 'last_modified:[' + since + 'Z TO *] AND (%s)' % query
response = solr.query_grouped(
settings.SOLR_DATA_CORE,
query,
'dataset_slug',
offset=offset,
limit=limit,
group_limit=group_limit,
group_offset=group_offset
)
groups = response['grouped']['dataset_slug']['groups']
page = PandaPaginator(
request.GET,
groups,
resource_uri=request.path_info,
count=response['grouped']['dataset_slug']['ngroups']
).page()
datasets = []
for group in groups:
dataset_slug = group['groupValue']
results = group['doclist']
dataset_resource = DatasetResource()
dataset = Dataset.objects.get(slug=dataset_slug)
dataset_bundle = dataset_resource.build_bundle(obj=dataset, request=request)
dataset_bundle = dataset_resource.full_dehydrate(dataset_bundle)
dataset_bundle = dataset_resource.simplify_bundle(dataset_bundle)
objects = [SolrObject(obj) for obj in results['docs']]
dataset_search_url = reverse('api_dataset_data_list', kwargs={ 'api_name': self._meta.api_name, 'dataset_resource_name': 'dataset', 'resource_name': 'data', 'dataset_slug': dataset.slug })
data_page = PandaPaginator(
{ 'limit': str(group_limit), 'offset': str(group_offset), 'q': query },
objects,
resource_uri=dataset_search_url,
count=results['numFound']
).page()
dataset_bundle.data.update(data_page)
dataset_bundle.data['objects'] = []
for obj in objects:
data_bundle = self.build_bundle(obj=obj, request=request)
data_bundle = self.full_dehydrate(data_bundle)
dataset_bundle.data['objects'].append(data_bundle)
datasets.append(dataset_bundle.data)
page['objects'] = datasets
# Log query
SearchLog.objects.create(user=request.user, dataset=None, query=query)
self.log_throttled_access(request)
return self.create_response(request, page)
def search_all_data(self, request, **kwargs):
"""
List endpoint using Solr. Provides full-text search via the "q" parameter."
"""
self.method_check(request, allowed=['get'])
self.is_authenticated(request)
self.throttle_check(request)
try:
query = '(%s)' % request.GET['q']
except KeyError:
query = ''
category = request.GET.get('category', '')
since = request.GET.get('since', None)
limit = int(request.GET.get('limit', settings.PANDA_DEFAULT_SEARCH_GROUPS))
offset = int(request.GET.get('offset', 0))
group_limit = int(request.GET.get('group_limit', settings.PANDA_DEFAULT_SEARCH_ROWS_PER_GROUP))
group_offset = int(request.GET.get('group_offset', 0))
export = bool(request.GET.get('export', False))
solr_query_bits = [query]
if category:
if category != 'uncategorized':
category = Category.objects.get(slug=category)
dataset_slugs = category.datasets.values_list('slug', flat=True)
else:
dataset_slugs = Dataset.objects.filter(categories=None).values_list('slug', flat=True)
solr_query_bits.append('dataset_slug:(%s)' % ' '.join(dataset_slugs))
if since:
solr_query_bits.append('last_modified:[' + since + 'Z TO *]')
# Because users may have authenticated via headers the request.user may
# not be a full User instance. To be sure, we fetch one.
user = UserProxy.objects.get(id=request.user.id)
if export:
task_type = ExportSearchTask
task = TaskStatus.objects.create(
task_name=task_type.name,
task_description=_('Export search results for "%s".') % query,
creator=user
)
task_type.apply_async(
args=[query, task.id],
kwargs={},
task_id=task.id
)
else:
response = solr.query_grouped(
settings.SOLR_DATA_CORE,
' AND '.join(solr_query_bits),
'dataset_slug',
offset=offset,
limit=limit,
group_limit=group_limit,
group_offset=group_offset
)
groups = response['grouped']['dataset_slug']['groups']
page = PandaPaginator(
request.GET,
groups,
resource_uri=request.path_info,
count=response['grouped']['dataset_slug']['ngroups']
).page()
datasets = []
for group in groups:
dataset_slug = group['groupValue']
results = group['doclist']
try:
dataset = Dataset.objects.get(slug=dataset_slug)
# In the event that stale data exists in Solr, skip this dataset,
# request the invalid data be purged and return the other results.
# Pagination may be wrong, but this is the most functional solution. (#793)
except Dataset.DoesNotExist:
PurgeDataTask.apply_async(args=[dataset_slug])
solr.delete(settings.SOLR_DATASETS_CORE, 'slug:%s' % dataset_slug)
page['meta']['total_count'] -= 1
continue
dataset_resource = DatasetResource()
dataset_bundle = dataset_resource.build_bundle(obj=dataset, request=request)
dataset_bundle = dataset_resource.full_dehydrate(dataset_bundle)
dataset_bundle = dataset_resource.simplify_bundle(dataset_bundle)
objects = [SolrObject(obj) for obj in results['docs']]
dataset_search_url = reverse('api_dataset_data_list', kwargs={ 'api_name': self._meta.api_name, 'dataset_resource_name': 'dataset', 'resource_name': 'data', 'dataset_slug': dataset.slug })
data_page = PandaPaginator(
{ 'limit': str(group_limit), 'offset': str(group_offset), 'q': query },
objects,
resource_uri=dataset_search_url,
count=results['numFound']
).page()
dataset_bundle.data.update(data_page)
dataset_bundle.data['objects'] = []
for obj in objects:
data_bundle = self.build_bundle(obj=obj, request=request)
data_bundle = self.full_dehydrate(data_bundle)
dataset_bundle.data['objects'].append(data_bundle)
datasets.append(dataset_bundle.data)
page['objects'] = datasets
# Log query
SearchLog.objects.create(user=user, dataset=None, query=query)
self.log_throttled_access(request)
if export:
return self.create_response(request, _('Export queued.'))
else:
return self.create_response(request, page)
