def export_csv_for_model(model, dataset):
model_cls = getattr(udata_models, model.capitalize(), None)
if not model_cls:
log.error('Unknow model %s' % model)
return
queryset = get_queryset(model_cls)
adapter = csv.get_adapter(model_cls)
if not adapter:
log.error('No adapter found for %s' % model)
return
adapter = adapter(queryset)
log.info('Exporting CSV for %s...' % model)
csvfile = NamedTemporaryFile(delete=False)
try:
# write adapter results into a tmp file
writer = csv.get_writer(csvfile)
writer.writerow(adapter.header())
for row in adapter.rows():
writer.writerow(row)
csvfile.seek(0)
# make a resource from this tmp file
created, resource = store_resource(csvfile, model, dataset)
# add it to the dataset
if created:
dataset.add_resource(resource)
dataset.last_modified = datetime.now()
dataset.save()
finally:
os.unlink(csvfile.name)
def export_csv_for_model(model, dataset):
model_cls = getattr(udata_models, model.capitalize(), None)
if not model_cls:
log.error('Unknow model %s' % model)
return
queryset = get_queryset(model_cls)
adapter = csv.get_adapter(model_cls)
if not adapter:
log.error('No adapter found for %s' % model)
return
adapter = adapter(queryset)
log.info('Exporting CSV for %s...' % model)
csvfile = NamedTemporaryFile(mode='w', encoding='utf8', delete=False)
try:
# write adapter results into a tmp file
writer = csv.get_writer(csvfile)
writer.writerow(adapter.header())
for row in adapter.rows():
writer.writerow(row)
# make a resource from this tmp file
created, resource = store_resource(csvfile, model, dataset)
# add it to the dataset
if created:
dataset.add_resource(resource)
dataset.last_modified = datetime.now()
dataset.save()
finally:
csvfile.close()
os.unlink(csvfile.name)
def datasets_csv():
params = multi_to_dict(request.args)
# redirect to EXPORT_CSV dataset if feature is enabled and no filter is set
exported_models = current_app.config.get('EXPORT_CSV_MODELS', [])
if not params and 'dataset' in exported_models:
return redirect(get_export_url('dataset'))
params['facets'] = False
datasets = search.iter(Dataset, **params)
adapter = csv.get_adapter(Dataset)
return csv.stream(adapter(datasets), 'datasets')
def datasets_csv():
params = multi_to_dict(request.args)
# redirect to EXPORT_CSV dataset if feature is enabled and no filter is set
exported_models = current_app.config.get('EXPORT_CSV_MODELS', [])
if not params and 'dataset' in exported_models:
return redirect(get_export_url('dataset'))
params['facets'] = False
datasets = search.iter(Dataset, **params)
adapter = csv.get_adapter(Dataset)
return csv.stream(adapter(datasets), 'datasets')
def datasets_csv():
params = multi_to_dict(request.args)
params['facets'] = False
datasets = search.iter(Dataset, **params)
adapter = csv.get_adapter(Dataset)
return csv.stream(adapter(datasets), 'datasets')
def from_adapter():
cls = csv.get_adapter(Fake)
adapter = cls(Fake.objects)
return csv.stream(adapter)
def with_basename():
cls = csv.get_adapter(Fake)
adapter = cls(Fake.objects)
return csv.stream(adapter, 'test')
def from_adapter():
cls = csv.get_adapter(Fake)
adapter = cls(Fake.objects)
return csv.stream(adapter)
def with_basename():
cls = csv.get_adapter(Fake)
adapter = cls(Fake.objects)
return csv.stream(adapter, 'test')
def datasets_csv():
params = multi_to_dict(request.args)
params['facets'] = False
datasets = search.iter(Dataset, **params)
adapter = csv.get_adapter(Dataset)
return csv.stream(adapter(datasets), 'datasets')
