def update(dataset_id, dictionary, author_id):
# TODO(roman): Make author_id argument optional (keep old author if None).
dataset_validator.validate(dictionary)
with db.engine.begin() as connection:
if "description" not in dictionary:
dictionary["description"] = None
connection.execute("""UPDATE dataset
SET (name, description, public, author, last_edited) = (%s, %s, %s, %s, now())
WHERE id = %s""",
(dictionary["name"], dictionary["description"], dictionary["public"], author_id, dataset_id))
# Replacing old classes with new ones
connection.execute("""DELETE FROM dataset_class WHERE dataset = %s""", (dataset_id,))
for cls in dictionary["classes"]:
if "description" not in cls:
cls["description"] = None
result = connection.execute("""INSERT INTO dataset_class (name, description, dataset)
VALUES (%s, %s, %s) RETURNING id""",
(cls["name"], cls["description"], dataset_id))
cls_id = result.fetchone()[0]
for recording_mbid in cls["recordings"]:
connection.execute("INSERT INTO dataset_class_member (class, mbid) VALUES (%s, %s)",
(cls_id, recording_mbid))
def create_from_dict(dictionary, author_id):
"""Creates a new dataset from a dictionary.
Returns:
Tuple with two values: new dataset ID and error. If error occurs first
will be None and second is an exception. If there are no errors, second
value will be None.
"""
dataset_validator.validate(dictionary)
with db.engine.begin() as connection:
if "description" not in dictionary:
dictionary["description"] = None
result = connection.execute("""INSERT INTO dataset (id, name, description, public, author)
VALUES (uuid_generate_v4(), %s, %s, %s, %s) RETURNING id""",
(dictionary["name"], dictionary["description"], dictionary["public"], author_id))
dataset_id = result.fetchone()[0]
for cls in dictionary["classes"]:
if "description" not in cls:
cls["description"] = None
result = connection.execute("""INSERT INTO dataset_class (name, description, dataset)
VALUES (%s, %s, %s) RETURNING id""",
(cls["name"], cls["description"], dataset_id))
cls_id = result.fetchone()[0]
# Removing duplicate recordings
cls["recordings"] = list(set(cls["recordings"]))
for recording_mbid in cls["recordings"]:
connection.execute("INSERT INTO dataset_class_member (class, mbid) VALUES (%s, %s)",
(cls_id, recording_mbid))
return dataset_id
def update(dataset_id, dictionary, author_id):
# TODO(roman): Make author_id argument optional (keep old author if None).
dataset_validator.validate(dictionary)
with db.engine.begin() as connection:
if "description" not in dictionary or dictionary["description"] is None:
dictionary["description"] = ""
connection.execute(
"""UPDATE dataset
SET (name, description, public, author, last_edited) = (%s, %s, %s, %s, now())
WHERE id = %s""",
(dictionary["name"], dictionary["description"],
dictionary["public"], author_id, dataset_id))
# Replacing old classes with new ones
connection.execute("""DELETE FROM dataset_class WHERE dataset = %s""",
(dataset_id, ))
for cls in dictionary["classes"]:
if "description" not in cls or cls["description"] is None:
cls["description"] = ""
result = connection.execute(
"""INSERT INTO dataset_class (name, description, dataset)
VALUES (%s, %s, %s) RETURNING id""",
(cls["name"], cls["description"], dataset_id))
cls_id = result.fetchone()[0]
for recording_mbid in cls["recordings"]:
connection.execute(
"INSERT INTO dataset_class_member (class, mbid) VALUES (%s, %s)",
(cls_id, recording_mbid))
def test_dataset_item_lengths(self):
# Incorrect lengths
with self.assertRaises(dataset_validator.ValidationException) as ar:
dataset_validator.validate({
"name": "", # Smaller than Min Len
"classes": [],
"public": False,
})
self.assertEqual(str(ar.exception), "Dataset name must be between 1 and 100 characters")
with self.assertRaises(dataset_validator.ValidationException) as ar:
dataset_validator.validate({
"name": "abcdefghijklmnopqrstuvwxyzabcdefghijklmnopqrstuvwxyzabcdefghijklmnopqrstuv \
wxyzabcdefghijklmnopqrstuvwxyzabcdefghijklmnopqrstuvwxyzabcdefghj", # Greater than Max Len
"classes": [],
"public": False,
})
self.assertEqual(str(ar.exception), "Dataset name must be between 1 and 100 characters")
with self.assertRaises(dataset_validator.ValidationException) as ar:
dataset_validator.validate({
"name": "this dataset",
"classes": [
{
"name": "", # Smaller than Min Len
"recordings": [],
},
],
"public": False,
})
self.assertEqual(str(ar.exception), "Length of the `name` field in class number 0 doesn't fit the limits. Class name must be between 1 and 100 characters")
with self.assertRaises(dataset_validator.ValidationException) as ar:
dataset_validator.validate({
"name": "this dataset",
"classes": [
{
"name": "abcdefghijklmnopqrstuvwxyzabcdefghijklmnopqrstuvwxyzabcdefghijkl \
mnopqrstuvwxyzabcdefghijklmnopqrstuvwxyzabcdefghijklmnopqrstuvwxyzabcdefghj", #Greater than Max Len
"recordings": [],
},
],
"public": False,
})
self.assertEqual(str(ar.exception), "Length of the `name` field in class number 0 doesn't fit the limits. Class name must be between 1 and 100 characters")
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "test",
"classes": [
{
"name": "Not Rock",
"why": "Because", # this item shouldn't be there
"recordings": [],
},
],
"public": False,
})
def test_dataset_unexpected_items(self):
# Unexpected items
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"i_like": "to test",
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"i": "don't",
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "Dataset",
"surname": "For Testing", # this item shouldn't be there
"classes": [
{
"name": "Not Rock",
"recordings": [],
},
],
"public": False,
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "Dataset",
"classes": [
{
"name": "Rock",
"why": "Because", # this item shouldn't be there
"recordings": [],
},
],
"public": True,
})
def test_dataset_missing_values(self):
# Missing values
with self.assertRaises(dataset_validator.ValidationException):
# Dataset name is missing
dataset_validator.validate({
"classes": [
{
"name": "the one and only",
"recordings": [],
},
],
"public":
False,
})
with self.assertRaises(dataset_validator.ValidationException):
# List of classes is missing
dataset_validator.validate({
"name": "test",
"public": False,
})
with self.assertRaises(dataset_validator.ValidationException):
# Publicity value is missing
dataset_validator.validate({
"name": "test",
"classes": [],
})
with self.assertRaises(dataset_validator.ValidationException):
# Class name is missing
dataset_validator.validate({
"name": "test",
"classes": [
{
"recordings": [],
},
],
"public": False,
})
with self.assertRaises(dataset_validator.ValidationException):
# List of recordings in a class is missing
dataset_validator.validate({
"name": "test",
"classes": [
{
"name": "this",
},
],
"public": False,
})
def test_dataset_missing_values(self):
# Missing values
with self.assertRaises(dataset_validator.ValidationException):
# Dataset name is missing
dataset_validator.validate({
"classes": [
{
"name": "the one and only",
"recordings": [],
},
],
"public": False,
})
with self.assertRaises(dataset_validator.ValidationException):
# List of classes is missing
dataset_validator.validate({
"name": "test",
"public": False,
})
with self.assertRaises(dataset_validator.ValidationException):
# Publicity value is missing
dataset_validator.validate({
"name": "test",
"classes": [],
})
with self.assertRaises(dataset_validator.ValidationException):
# Class name is missing
dataset_validator.validate({
"name": "test",
"classes": [
{
"recordings": [],
},
],
"public": False,
})
with self.assertRaises(dataset_validator.ValidationException):
# List of recordings in a class is missing
dataset_validator.validate({
"name": "test",
"classes": [
{
"name": "this",
},
],
"public": False,
})
def test_dataset_item_lengths(self):
# Incorrect lengths
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "", # incorrect
"classes": [],
"public": False,
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name":
"this dataset",
"classes": [
{
"name": "", # incorrect
"recordings": [],
},
],
"public":
False,
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name":
"test",
"classes": [
{
"name": "Not Rock",
"why": "Because", # this item shouldn't be there
"recordings": [],
},
],
"public":
False,
})
def create_from_dict(dictionary, author_id):
"""Creates a new dataset from a dictionary.
Returns:
Tuple with two values: new dataset ID and error. If error occurs first
will be None and second is an exception. If there are no errors, second
value will be None.
"""
dataset_validator.validate(dictionary)
with db.engine.begin() as connection:
if "description" not in dictionary:
dictionary["description"] = None
result = connection.execute("""INSERT INTO dataset (id, name, description, public, author)
VALUES (uuid_generate_v4(), %s, %s, %s, %s) RETURNING id""",
(dictionary["name"], dictionary["description"], dictionary["public"], author_id))
dataset_id = result.fetchone()[0]
for cls in dictionary["classes"]:
if "description" not in cls:
cls["description"] = None
result = connection.execute("""INSERT INTO dataset_class (name, description, dataset)
VALUES (%s, %s, %s) RETURNING id""",
(cls["name"], cls["description"], dataset_id))
cls_id = result.fetchone()[0]
# Remove duplicate recordings, preserving order
seen = set()
cls["recordings"] = [r for r in cls["recordings"] if not (r in seen or seen.add(r))]
for recording_mbid in cls["recordings"]:
connection.execute("INSERT INTO dataset_class_member (class, mbid) VALUES (%s, %s)",
(cls_id, recording_mbid))
return dataset_id
def test_dataset_unexpected_items(self):
# Unexpected items
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"i_like": "to test",
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"i": "don't",
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name":
"Dataset",
"surname":
"For Testing", # this item shouldn't be there
"classes": [
{
"name": "Not Rock",
"recordings": [],
},
],
"public":
False,
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name":
"Dataset",
"classes": [
{
"name": "Rock",
"why": "Because", # this item shouldn't be there
"recordings": [],
},
],
"public":
True,
})
def test_dataset_incorrect_types(self):
# Incorrect types
# String, not dict
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate("dataset")
# Name should be string
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": ["This", "is", "my", "cool", "dataset"],
"classes": [],
"public":
False,
})
# Desc should be string
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "test",
"description": False,
"classes": [],
"public": False,
})
# Classes should be list
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "test",
"description": "",
"classes": None,
"public": False,
})
# public should be bool
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "test",
"description": "",
"classes": [],
"public": "Nope",
})
# class name should be string
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name":
"test",
"classes": [
{
"name": ("this", "is", "a", "name"),
"recordings": [],
},
],
"public":
False,
})
# class elements should be dict
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "test",
"classes": [
"first",
"second",
],
"public": False,
})
# Class desc should be string
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name":
"test",
"classes": [
{
"name": "first",
"description": False,
"recordings": [],
},
],
"public":
False,
})
# class recordings should be list
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name":
"test",
"classes": [
{
"name": "first",
"recordings": "I don't have any :(",
},
],
"public":
False,
})
# Class recordings should be uuids
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name":
"test",
"classes": [
{
"name": "first",
"recordings": ["my favourite"],
},
],
"public":
False,
})
def test_dataset_item_lengths(self):
# Incorrect lengths
with self.assertRaises(dataset_validator.ValidationException) as ar:
dataset_validator.validate({
"name": "", # Smaller than Min Len
"classes": [],
"public": False,
})
self.assertEqual(six.ensure_text(ar.exception.error),
"Dataset name must be between 1 and 100 characters")
with self.assertRaises(dataset_validator.ValidationException) as ar:
dataset_validator.validate({
"name":
"abcdefghijklmnopqrstuvwxyzabcdefghijklmnopqrstuvwxyzabcdefghijklmnopqrstuv \
wxyzabcdefghijklmnopqrstuvwxyzabcdefghijklmnopqrstuvwxyzabcdefghj", # Greater than Max Len
"classes": [],
"public": False,
})
self.assertEqual(six.ensure_text(ar.exception.error),
"Dataset name must be between 1 and 100 characters")
with self.assertRaises(dataset_validator.ValidationException) as ar:
dataset_validator.validate({
"name":
"this dataset",
"classes": [
{
"name": "", # Smaller than Min Len
"recordings": [],
},
],
"public":
False,
})
self.assertEqual(
six.ensure_text(ar.exception.error),
"Length of the `name` field in class number 0 doesn't fit the limits. Class name must be between 1 and 100 characters"
)
with self.assertRaises(dataset_validator.ValidationException) as ar:
dataset_validator.validate({
"name":
"this dataset",
"classes": [
{
"name":
"abcdefghijklmnopqrstuvwxyzabcdefghijklmnopqrstuvwxyzabcdefghijkl \
mnopqrstuvwxyzabcdefghijklmnopqrstuvwxyzabcdefghijklmnopqrstuvwxyzabcdefghj", #Greater than Max Len
"recordings": [],
},
],
"public":
False,
})
self.assertEqual(
six.ensure_text(ar.exception.error),
"Length of the `name` field in class number 0 doesn't fit the limits. Class name must be between 1 and 100 characters"
)
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name":
"test",
"classes": [
{
"name": "Not Rock",
"why": "Because", # this item shouldn't be there
"recordings": [],
},
],
"public":
False,
})
def test_malformed_datasets(self):
# Unexpected items
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"i_like": "to test",
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"i": "don't",
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name":
"Dataset",
"surname":
"For Testing", # this item shouldn't be there
"classes": [
{
"name": "Not Rock",
"recordings": [],
},
],
"public":
False,
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name":
"Dataset",
"classes": [
{
"name": "Rock",
"why": "Because", # this item shouldn't be there
"recordings": [],
},
],
"public":
True,
})
# Missing values
with self.assertRaises(dataset_validator.ValidationException):
# Dataset name is missing
dataset_validator.validate({
"classes": [
{
"name": "the one and only",
"recordings": [],
},
],
"public":
False,
})
with self.assertRaises(dataset_validator.ValidationException):
# List of classes is missing
dataset_validator.validate({
"name": "test",
"public": False,
})
with self.assertRaises(dataset_validator.ValidationException):
# Publicity value is missing
dataset_validator.validate({
"name": "test",
"classes": [],
})
with self.assertRaises(dataset_validator.ValidationException):
# Class name is missing
dataset_validator.validate({
"name": "test",
"classes": [
{
"recordings": [],
},
],
"public": False,
})
with self.assertRaises(dataset_validator.ValidationException):
# List of recordings in a class is missing
dataset_validator.validate({
"name": "test",
"classes": [
{
"name": "this",
},
],
"public": False,
})
# Incorrect types
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate("dataset")
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": ["This", "is", "my", "cool", "dataset"],
"classes": [],
"public":
False,
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "test",
"description": False,
"classes": [],
"public": False,
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "test",
"description": "",
"classes": None,
"public": False,
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "test",
"description": "",
"classes": [],
"public": "Nope",
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name":
"test",
"classes": [
{
"name": ("this", "is", "a", "name"),
"recordings": [],
},
],
"public":
False,
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "test",
"classes": [
"first",
"second",
],
"public": False,
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name":
"test",
"classes": [
{
"name": "first",
"description": False,
"recordings": [],
},
],
"public":
False,
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name":
"test",
"classes": [
{
"name": "first",
"recordings": "I don't have any :(",
},
],
"public":
False,
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name":
"test",
"classes": [
{
"name": "first",
"recordings": ["my favourite"],
},
],
"public":
False,
})
# Incorrect lengths
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "", # incorrect
"classes": [],
"public": False,
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name":
"this dataset",
"classes": [
{
"name": "", # incorrect
"recordings": [],
},
],
"public":
False,
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name":
"test",
"classes": [
{
"name": "Not Rock",
"why": "Because", # this item shouldn't be there
"recordings": [],
},
],
"public":
False,
})
def test_dataset_incorrect_types(self):
# Incorrect types
# String, not dict
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate("dataset")
# Name should be string
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": ["This", "is", "my", "cool", "dataset"],
"classes": [],
"public": False,
})
# Desc should be string
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "test",
"description": False,
"classes": [],
"public": False,
})
# Classes should be list
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "test",
"description": "",
"classes": None,
"public": False,
})
# public should be bool
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "test",
"description": "",
"classes": [],
"public": "Nope",
})
# class name should be string
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "test",
"classes": [
{
"name": ("this", "is", "a", "name"),
"recordings": [],
},
],
"public": False,
})
# class elements should be dict
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "test",
"classes": [
"first",
"second",
],
"public": False,
})
# Class desc should be string
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "test",
"classes": [
{
"name": "first",
"description": False,
"recordings": [],
},
],
"public": False,
})
# class recordings should be list
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "test",
"classes": [
{
"name": "first",
"recordings": "I don't have any :(",
},
],
"public": False,
})
# Class recordings should be uuids
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "test",
"classes": [
{
"name": "first",
"recordings": [
"my favourite"
],
},
],
"public": False,
})
def test_malformed_datasets(self):
# Unexpected items
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"i_like": "to test",
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"i": "don't",
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "Dataset",
"surname": "For Testing", # this item shouldn't be there
"classes": [
{
"name": "Not Rock",
"recordings": [],
},
],
"public": False,
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "Dataset",
"classes": [
{
"name": "Rock",
"why": "Because", # this item shouldn't be there
"recordings": [],
},
],
"public": True,
})
# Missing values
with self.assertRaises(dataset_validator.ValidationException):
# Dataset name is missing
dataset_validator.validate({
"classes": [
{
"name": "the one and only",
"recordings": [],
},
],
"public": False,
})
with self.assertRaises(dataset_validator.ValidationException):
# List of classes is missing
dataset_validator.validate({
"name": "test",
"public": False,
})
with self.assertRaises(dataset_validator.ValidationException):
# Publicity value is missing
dataset_validator.validate({
"name": "test",
"classes": [],
})
with self.assertRaises(dataset_validator.ValidationException):
# Class name is missing
dataset_validator.validate({
"name": "test",
"classes": [
{
"recordings": [],
},
],
"public": False,
})
with self.assertRaises(dataset_validator.ValidationException):
# List of recordings in a class is missing
dataset_validator.validate({
"name": "test",
"classes": [
{
"name": "this",
},
],
"public": False,
})
# Incorrect types
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate("dataset")
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": ["This", "is", "my", "cool", "dataset"],
"classes": [],
"public": False,
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "test",
"description": False,
"classes": [],
"public": False,
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "test",
"description": "",
"classes": None,
"public": False,
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "test",
"description": "",
"classes": [],
"public": "Nope",
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "test",
"classes": [
{
"name": ("this", "is", "a", "name"),
"recordings": [],
},
],
"public": False,
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "test",
"classes": [
"first",
"second",
],
"public": False,
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "test",
"classes": [
{
"name": "first",
"description": False,
"recordings": [],
},
],
"public": False,
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "test",
"classes": [
{
"name": "first",
"recordings": "I don't have any :(",
},
],
"public": False,
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "test",
"classes": [
{
"name": "first",
"recordings": [
"my favourite"
],
},
],
"public": False,
})
# Incorrect lengths
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "", # incorrect
"classes": [],
"public": False,
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "this dataset",
"classes": [
{
"name": "", # incorrect
"recordings": [],
},
],
"public": False,
})
with self.assertRaises(dataset_validator.ValidationException):
dataset_validator.validate({
"name": "test",
"classes": [
{
"name": "Not Rock",
"why": "Because", # this item shouldn't be there
"recordings": [],
},
],
"public": False,
})
