def lookup_assembly(name):
pwdb.connect(reuse_if_open=True)
try:
assy = AssemblyModel.get(AssemblyModel.name == name)
except AssemblyModel.DoesNotExist as e:
raise AssemblyLookupError("A DataAssembly named " + name +
" was not found.")
return assy
def add_stimulus_set_lookup_to_db(stimulus_set_name, bucket_name, zip_file_name,
image_store_unique_name, zip_sha1):
_logger.debug(f"Adding stimulus set {stimulus_set_name} to db")
pwdb.connect(reuse_if_open=True)
stim_set_model, created = StimulusSetModel.get_or_create(name=stimulus_set_name)
image_store_model, created = ImageStoreModel.get_or_create(location_type="S3", store_type="zip",
location=f"https://{bucket_name}.s3.amazonaws.com/{zip_file_name}",
unique_name=image_store_unique_name,
sha1=zip_sha1)
return (stim_set_model, image_store_model)
def add_stimulus_set_metadata_and_lookup_to_db(stimuli, stimulus_set_name,
bucket_name, zip_file_name,
image_store_unique_name,
zip_sha1):
pwdb.connect(reuse_if_open=True)
stim_set_model, created = StimulusSetModel.get_or_create(
name=stimulus_set_name)
image_store, created = ImageStoreModel.get_or_create(
location_type="S3",
store_type="zip",
location=f"https://{bucket_name}.s3.amazonaws.com/{zip_file_name}",
unique_name=image_store_unique_name,
sha1=zip_sha1)
add_image_metadata_to_db(stimuli, stim_set_model, image_store)
return stim_set_model
def test_add_image_metadata_to_db(transaction):
pwdb.connect(reuse_if_open=True)
proto = prep_proto_stim()
stim_set_model, created = StimulusSetModel.get_or_create(
name=f"test_stimulus_set.{now()}")
image_store_model, created = ImageStoreModel.get_or_create(
location_type="test_loc_type",
store_type="test_store_type",
location="test_loc",
unique_name=f"test_store.{now()}",
sha1=f"foo.{now()}")
add_image_metadata_to_db(proto, stim_set_model, image_store_model)
pw_query = ImageModel.select() \
.join(StimulusSetImageMap) \
.join(StimulusSetModel) \
.where(StimulusSetModel.name == stim_set_model.name)
print(f"Length of select query: {len(pw_query)}")
assert len(pw_query) == 25
def add_image_metadata_to_db(proto_stimulus_set, stim_set_model, image_store_model):
pwdb.connect(reuse_if_open=True)
stimulus_set_specific_attributes = extract_specific(proto_stimulus_set)
eav_attributes = {}
for name in stimulus_set_specific_attributes:
target_type = type(proto_stimulus_set[name].values.item(0)).__name__
eav_attribute, created = AttributeModel.get_or_create(name=name, type=target_type)
eav_attributes[name] = eav_attribute
for image in tqdm(proto_stimulus_set.itertuples(), desc='images->db', total=len(proto_stimulus_set)):
pw_image, created = ImageModel.get_or_create(image_id=image.image_id)
StimulusSetImageMap.get_or_create(stimulus_set=stim_set_model, image=pw_image)
file_name = image.image_path_within_store if hasattr(image,
'image_path_within_store') else image.image_file_name
ImageStoreMap.get_or_create(image=pw_image, image_store=image_store_model, path=file_name)
for name in eav_attributes:
ImageMetaModel.get_or_create(image=pw_image, attribute=eav_attributes[name],
value=str(getattr(image, name)))
def add_image_metadata_to_db(stimuli, stim_set_model, image_store):
pwdb.connect(reuse_if_open=True)
eav_image_sample_obj, created = AttributeModel.get_or_create(
name="image_sample_obj", type="str")
eav_image_label, created = AttributeModel.get_or_create(name="image_label",
type="str")
for image in stimuli.itertuples():
pw_image, created = ImageModel.get_or_create(image_id=image.image_id)
pw_stimulus_set_image_map, created = StimulusSetImageMap.get_or_create(
stimulus_set=stim_set_model, image=pw_image)
pw_image_image_store_map, created = ImageStoreMap.get_or_create(
image=pw_image,
image_store=image_store,
path=image.image_path_within_store)
ImageMetaModel.get_or_create(image=pw_image,
attribute=eav_image_sample_obj,
value=str(image.image_sample_obj))
ImageMetaModel.get_or_create(image=pw_image,
attribute=eav_image_label,
value=str(image.image_label))