def run_operation(self, sessions, collection, operation):
original_collection = collection
name = camel_to_snake(operation['name'])
if name == 'run_command':
name = 'command'
elif name == 'download_by_name':
name = 'open_download_stream_by_name'
elif name == 'download':
name = 'open_download_stream'
database = collection.database
collection = database.get_collection(collection.name)
if 'collectionOptions' in operation:
collection = collection.with_options(
**self.parse_options(operation['collectionOptions']))
object_name = self.get_object_name(operation)
if object_name == 'gridfsbucket':
# Only create the GridFSBucket when we need it (for the gridfs
# retryable reads tests).
obj = GridFSBucket(database,
bucket_name=collection.name,
disable_md5=True)
else:
objects = {
'client': database.client,
'database': database,
'collection': collection,
'testRunner': self
}
objects.update(sessions)
obj = objects[object_name]
# Combine arguments with options and handle special cases.
arguments = operation.get('arguments', {})
arguments.update(arguments.pop("options", {}))
self.parse_options(arguments)
cmd = getattr(obj, name)
with_txn_callback = functools.partial(self.run_operations,
sessions,
original_collection,
in_with_transaction=True)
prepare_spec_arguments(operation, arguments, name, sessions,
with_txn_callback)
if name == 'run_on_thread':
args = {'sessions': sessions, 'collection': collection}
args.update(arguments)
arguments = args
result = cmd(**dict(arguments))
if name == "aggregate":
if arguments["pipeline"] and "$out" in arguments["pipeline"][-1]:
# Read from the primary to ensure causal consistency.
out = collection.database.get_collection(
arguments["pipeline"][-1]["$out"],
read_preference=ReadPreference.PRIMARY)
return out.find()
if name == "map_reduce":
if isinstance(result, dict) and 'results' in result:
return result['results']
if 'download' in name:
result = Binary(result.read())
if isinstance(result, Cursor) or isinstance(result, CommandCursor):
return list(result)
return result
def run_operation(self, sessions, collection, operation):
original_collection = collection
name = camel_to_snake(operation['name'])
if name == 'run_command':
name = 'command'
elif name == 'download_by_name':
name = 'open_download_stream_by_name'
elif name == 'download':
name = 'open_download_stream'
database = collection.database
collection = database.get_collection(collection.name)
if 'collectionOptions' in operation:
collection = collection.with_options(
**self.parse_options(operation['collectionOptions']))
object_name = self.get_object_name(operation)
if object_name == 'gridfsbucket':
# Only create the GridFSBucket when we need it (for the gridfs
# retryable reads tests).
obj = GridFSBucket(database,
bucket_name=collection.name,
disable_md5=True)
else:
objects = {
'client': database.client,
'database': database,
'collection': collection,
'testRunner': self
}
objects.update(sessions)
obj = objects[object_name]
# Combine arguments with options and handle special cases.
arguments = operation.get('arguments', {})
arguments.update(arguments.pop("options", {}))
self.parse_options(arguments)
cmd = getattr(obj, name)
for arg_name in list(arguments):
c2s = camel_to_snake(arg_name)
# PyMongo accepts sort as list of tuples.
if arg_name == "sort":
sort_dict = arguments[arg_name]
arguments[arg_name] = list(iteritems(sort_dict))
# Named "key" instead not fieldName.
if arg_name == "fieldName":
arguments["key"] = arguments.pop(arg_name)
# Aggregate uses "batchSize", while find uses batch_size.
elif ((arg_name == "batchSize" or arg_name == "allowDiskUse")
and name == "aggregate"):
continue
# Requires boolean returnDocument.
elif arg_name == "returnDocument":
arguments[c2s] = arguments.pop(arg_name) == "After"
elif c2s == "requests":
# Parse each request into a bulk write model.
requests = []
for request in arguments["requests"]:
bulk_model = camel_to_upper_camel(request["name"])
bulk_class = getattr(operations, bulk_model)
bulk_arguments = camel_to_snake_args(request["arguments"])
requests.append(bulk_class(**dict(bulk_arguments)))
arguments["requests"] = requests
elif arg_name == "session":
arguments['session'] = sessions[arguments['session']]
elif (name in ('command', 'run_admin_command')
and arg_name == 'command'):
# Ensure the first key is the command name.
ordered_command = SON([(operation['command_name'], 1)])
ordered_command.update(arguments['command'])
arguments['command'] = ordered_command
elif name == 'open_download_stream' and arg_name == 'id':
arguments['file_id'] = arguments.pop(arg_name)
elif name != 'find' and c2s == 'max_time_ms':
# find is the only method that accepts snake_case max_time_ms.
# All other methods take kwargs which must use the server's
# camelCase maxTimeMS. See PYTHON-1855.
arguments['maxTimeMS'] = arguments.pop('max_time_ms')
elif name == 'with_transaction' and arg_name == 'callback':
callback_ops = arguments[arg_name]['operations']
arguments['callback'] = lambda _: self.run_operations(
sessions,
original_collection,
copy.deepcopy(callback_ops),
in_with_transaction=True)
elif name == 'drop_collection' and arg_name == 'collection':
arguments['name_or_collection'] = arguments.pop(arg_name)
elif name == 'create_collection' and arg_name == 'collection':
arguments['name'] = arguments.pop(arg_name)
elif name == 'create_index' and arg_name == 'keys':
arguments['keys'] = list(arguments.pop(arg_name).items())
elif name == 'drop_index' and arg_name == 'name':
arguments['index_or_name'] = arguments.pop(arg_name)
else:
arguments[c2s] = arguments.pop(arg_name)
if name == 'run_on_thread':
args = {'sessions': sessions, 'collection': collection}
args.update(arguments)
arguments = args
result = cmd(**dict(arguments))
if name == "aggregate":
if arguments["pipeline"] and "$out" in arguments["pipeline"][-1]:
# Read from the primary to ensure causal consistency.
out = collection.database.get_collection(
arguments["pipeline"][-1]["$out"],
read_preference=ReadPreference.PRIMARY)
return out.find()
if name == "map_reduce":
if isinstance(result, dict) and 'results' in result:
return result['results']
if 'download' in name:
result = Binary(result.read())
if isinstance(result, Cursor) or isinstance(result, CommandCursor):
return list(result)
return result
def run_operation(self, sessions, collection, operation):
original_collection = collection
name = camel_to_snake(operation['name'])
if name == 'run_command':
name = 'command'
elif name == 'download_by_name':
name = 'open_download_stream_by_name'
elif name == 'download':
name = 'open_download_stream'
def parse_options(opts):
if 'readPreference' in opts:
opts['read_preference'] = parse_read_preference(
opts.pop('readPreference'))
if 'writeConcern' in opts:
opts['write_concern'] = WriteConcern(
**dict(opts.pop('writeConcern')))
if 'readConcern' in opts:
opts['read_concern'] = ReadConcern(
**dict(opts.pop('readConcern')))
return opts
database = collection.database
collection = database.get_collection(collection.name)
if 'collectionOptions' in operation:
collection = collection.with_options(
**dict(parse_options(operation['collectionOptions'])))
object_name = self.get_object_name(operation)
if object_name == 'gridfsbucket':
# Only create the GridFSBucket when we need it (for the gridfs
# retryable reads tests).
obj = GridFSBucket(
database, bucket_name=collection.name,
disable_md5=True)
else:
objects = {
'client': database.client,
'database': database,
'collection': collection,
'testRunner': self
}
objects.update(sessions)
obj = objects[object_name]
# Combine arguments with options and handle special cases.
arguments = operation.get('arguments', {})
arguments.update(arguments.pop("options", {}))
parse_options(arguments)
cmd = getattr(obj, name)
for arg_name in list(arguments):
c2s = camel_to_snake(arg_name)
# PyMongo accepts sort as list of tuples.
if arg_name == "sort":
sort_dict = arguments[arg_name]
arguments[arg_name] = list(iteritems(sort_dict))
# Named "key" instead not fieldName.
if arg_name == "fieldName":
arguments["key"] = arguments.pop(arg_name)
# Aggregate uses "batchSize", while find uses batch_size.
elif arg_name == "batchSize" and name == "aggregate":
continue
# Requires boolean returnDocument.
elif arg_name == "returnDocument":
arguments[c2s] = arguments.pop(arg_name) == "After"
elif c2s == "requests":
# Parse each request into a bulk write model.
requests = []
for request in arguments["requests"]:
bulk_model = camel_to_upper_camel(request["name"])
bulk_class = getattr(operations, bulk_model)
bulk_arguments = camel_to_snake_args(request["arguments"])
requests.append(bulk_class(**dict(bulk_arguments)))
arguments["requests"] = requests
elif arg_name == "session":
arguments['session'] = sessions[arguments['session']]
elif name == 'command' and arg_name == 'command':
# Ensure the first key is the command name.
ordered_command = SON([(operation['command_name'], 1)])
ordered_command.update(arguments['command'])
arguments['command'] = ordered_command
elif name == 'open_download_stream' and arg_name == 'id':
arguments['file_id'] = arguments.pop(arg_name)
elif name == 'with_transaction' and arg_name == 'callback':
callback_ops = arguments[arg_name]['operations']
arguments['callback'] = lambda _: self.run_operations(
sessions, original_collection, copy.deepcopy(callback_ops),
in_with_transaction=True)
else:
arguments[c2s] = arguments.pop(arg_name)
result = cmd(**dict(arguments))
if name == "aggregate":
if arguments["pipeline"] and "$out" in arguments["pipeline"][-1]:
# Read from the primary to ensure causal consistency.
out = collection.database.get_collection(
arguments["pipeline"][-1]["$out"],
read_preference=ReadPreference.PRIMARY)
return out.find()
if name == "map_reduce":
if isinstance(result, dict) and 'results' in result:
return result['results']
if 'download' in name:
result = Binary(result.read())
if isinstance(result, Cursor) or isinstance(result, CommandCursor):
return list(result)
return result
