def test_on_search_result_agents(self, local):
"""
Test that an agent can do a search for agents.
"""
with setup_test_agents(3, local, prefix="search_agents") as agents:
for a in agents:
a.connect()
agent_0, agent_1, agent_2 = agents
foo_attr = AttributeSchema("foo", int, False, "A foo attribute.")
bar_attr = AttributeSchema("bar", str, False, "A bar attribute.")
dummy_datamodel = DataModel("dummy_datamodel",
[foo_attr, bar_attr])
agent_1.register_agent(
0, Description({
"foo": 15,
"bar": "BAR"
}, dummy_datamodel))
agent_2.register_agent(
0, Description({
"foo": 5,
"bar": "ABC"
}, dummy_datamodel))
agent_0.search_agents(
0, Query([Constraint("foo", Eq(0))], dummy_datamodel))
agent_0.search_agents(
0,
Query([
Constraint("foo", Gt(10)),
Constraint("bar", Gt("B")),
], dummy_datamodel))
agent_0.search_agents(
0, Query([
Constraint("bar", Gt("A")),
], dummy_datamodel))
asyncio.ensure_future(agent_0.async_run())
asyncio.get_event_loop().run_until_complete(
asyncio.sleep(_ASYNCIO_DELAY))
agent_1.unregister_agent(0)
agent_2.unregister_agent(0)
expected_message_01 = (0, [])
expected_message_02 = (0, [agent_1.public_key])
expected_message_03 = (0, [agent_1.public_key, agent_2.public_key])
assert 3 == len(agent_0.received_msg)
assert expected_message_01 == agent_0.received_msg[0]
assert expected_message_02 == agent_0.received_msg[1]
assert expected_message_03 == agent_0.received_msg[2]
def test_raise_exception_when_duplicated_attribute_name(self):
"""Test that if we try to instantiate a DataModel with a list of attributes with not unique names
we raise an exception."""
with pytest.raises(
ValueError,
match=r"Invalid input value for type.*duplicated attribute name"
):
DataModel("bar", [
AttributeSchema("foo", bool, True),
AttributeSchema("foo", str, False)
])
def test_generate_schema_longer_values(self, ):
"""
Test that construct_schema constructs the correct schema from longer dict of values
"""
values = {"foo": "bar", "number": 1234, "float": 123.4, "bool": True}
schema_attributes = [
AttributeSchema("foo", str, True, ""),
AttributeSchema("number", int, True, ""),
AttributeSchema("float", float, True, ""),
AttributeSchema("bool", bool, True, "")
]
generate_schema_checker("foo", values,
DataModel("foo", schema_attributes))
def test_unregister_service(self, local):
"""
Test that the unregistration of services works correctly.
"""
with setup_test_agents(2, local,
prefix="unregister_service") as agents:
for a in agents:
a.connect()
agent_0, agent_1 = agents
dummy_datamodel = DataModel("dummy_datamodel",
[AttributeSchema("foo", int, False)])
dummy_service_description = Description({}, dummy_datamodel)
agent_1.register_service(0, dummy_service_description)
agent_1.unregister_service(0, dummy_service_description)
agent_0.search_services(
0, Query([Constraint("foo", Eq(0))], dummy_datamodel))
asyncio.ensure_future(agent_0.async_run())
asyncio.get_event_loop().run_until_complete(
asyncio.sleep(_ASYNCIO_DELAY))
assert 1 == len(agent_0.received_msg)
assert (0, []) == agent_0.received_msg[0]
def build_datamodel(good_pbks: List[str], is_supply: bool) -> DataModel:
"""
Build a data model for supply and demand (i.e. for offered or requested goods).
:param good_pbks: the list of good public keys
:param is_supply: Boolean indicating whether it is a supply or demand data model
:return: the data model.
"""
goods_quantities_attributes = [
AttributeSchema(good_pbk, int, False) for good_pbk in good_pbks
]
price_attribute = AttributeSchema("price", float, False)
description = TAC_SUPPLY_DATAMODEL_NAME if is_supply else TAC_DEMAND_DATAMODEL_NAME
data_model = DataModel(description,
goods_quantities_attributes + [price_attribute])
return data_model
def test_serialization(self, attribute):
"""Test that serialization and deserialization of AttributeSchema objects work correctly."""
actual_attribute_schema = attribute
actual_attribute_pb = actual_attribute_schema.to_pb(
) # type: query_pb2.Query.Attribute
expected_attribute_schema = AttributeSchema.from_pb(
actual_attribute_pb)
assert actual_attribute_schema == expected_attribute_schema
def attributes_schema(draw):
attr_name = draw(text())
attr_type = draw(attribute_schema_types)
attr_required = draw(booleans())
attr_description = draw(text())
return AttributeSchema(attr_name, attr_type, attr_required,
attr_description)
class TRIP_DATAMODEL(DataModel):
PERSON_ID = AttributeSchema("account_id",
str,
is_attribute_required=True,
attribute_description="Person ID.")
CAN_BE_DRIVER = AttributeSchema(
"can_be_driver",
bool,
is_attribute_required=True,
attribute_description="Can person be driver?")
TRIP_ID = AttributeSchema("trip_id",
str,
is_attribute_required=True,
attribute_description="Person ID.")
FROM_LOCATION_LATITUDE = AttributeSchema(
"from_location_latitude",
float,
is_attribute_required=True,
attribute_description="Latitude of FROM point.")
FROM_LOCATION_LONGITUDE = AttributeSchema(
"from_location_longitude",
float,
is_attribute_required=True,
attribute_description="Longitude of FROM point.")
TO_LOCATION_LATITUDE = AttributeSchema(
"to_location_latitude",
float,
is_attribute_required=True,
attribute_description="Latitude of TO point.")
TO_LOCATION_LONGITUDE = AttributeSchema(
"to_location_longitude",
float,
is_attribute_required=True,
attribute_description="Longitude of TO point.")
DISTANCE_AREA = AttributeSchema(
"distance_area",
float,
is_attribute_required=False,
attribute_description=
"Allowed distance of area from center of way-point.")
def __init__(self):
super().__init__("trip_datamodel", [
self.PERSON_ID, self.CAN_BE_DRIVER, self.TRIP_ID,
self.FROM_LOCATION_LATITUDE, self.FROM_LOCATION_LONGITUDE,
self.TO_LOCATION_LATITUDE, self.TO_LOCATION_LONGITUDE,
self.DISTANCE_AREA
], "Trip create fully.")
def modlify(data):
attributes = data['attributes']
# This is the least restrictive apporach.
# To make attributes required override the specific one with True as the third argument.
attribute_list = []
for key, value in attributes.items():
attribute_list.append(AttributeSchema(key, bool, False, value))
data_model = DataModel(data['name'], attribute_list, data['description'])
return data_model
def test_query_invalid_when_constraint_attribute_name_different_type(self):
"""Test that we raise an exception when at least one constraint attribute name
has a different type wrt the data model."""
with pytest.raises(ValueError, match=""):
a_query = Query(
[Constraint("an_attribute_name", Eq(0))],
DataModel("a_data_model",
[AttributeSchema("an_attribute_name", str, True)]))
def test_generate_schema_single_element(self, schema_name, attribute_name,
value_type_pair, description):
"""
Test that construct_schema constructs the correct schema from single-element attribute values
"""
value, type_ = value_type_pair
generate_schema_checker(
schema_name, {attribute_name: value},
DataModel(
schema_name,
[AttributeSchema(attribute_name, type_, True, description)]))
def load_service(self, metadata, load_path):
dataset_info = metadata['base']
attributes = description = {}
for item in dataset_info['tags']:
attributes[item] = description[item] = 'Tagged: ' + item
attribute_list = []
for key, value in attributes.items():
attribute_list.append(AttributeSchema(key, str, False, value))
data_model = DataModel(dataset_info['name'], attribute_list, dataset_info['description'])
service = Description(description, data_model)
data = Utils.load_json(load_path)
return service, data
def test_group_dialogue_one_client_n_servers(self):
with NetworkOEFNode():
client_proxy = OEFNetworkProxy("client",
oef_addr="127.0.0.1",
port=3333)
client = ClientAgentGroupDialogueTest(client_proxy)
client.connect()
N = 10
server_proxies = [
OEFNetworkProxy("server_{:02d}".format(i),
oef_addr="127.0.0.1",
port=3333) for i in range(N)
]
server_data_model = DataModel("server",
[AttributeSchema("foo", bool, True)])
servers = [
ServerAgentTest(server_proxy, price=random.randint(10, 100))
for server_proxy in server_proxies
]
for server in servers:
server.connect()
server.register_service(
0, Description({"foo": True}, server_data_model))
best_server = ServerAgentTest(OEFNetworkProxy("best_server",
oef_addr="127.0.0.1",
port=3333),
price=5)
best_server.connect()
best_server.register_service(
0, Description({"foo": True}, server_data_model))
servers.append(best_server)
asyncio.get_event_loop().run_until_complete(
asyncio.sleep(_ASYNCIO_DELAY))
query = Query([Constraint("foo", Eq(True))], server_data_model)
client.search_services(0, query)
asyncio.get_event_loop().run_until_complete(
asyncio.gather(client.async_run(),
*[server.async_run() for server in servers]))
assert "best_server" == client.group.best_agent
assert 5 == client.group.best_price
class TRANSPORT_DATAMODEL(DataModel):
PRICE_PER_KM = AttributeSchema(
"price_per_km",
float,
is_attribute_required=True,
attribute_description="Provides the price per kilometer.")
STATE = AttributeSchema(
"state",
str,
is_attribute_required=True,
attribute_description="Current state of transport.")
DRIVER_ID = AttributeSchema("driver_id",
str,
is_attribute_required=False,
attribute_description="Driver.")
PASSENGERS = AttributeSchema("passengers_ids",
str,
is_attribute_required=False,
attribute_description="All passangers.")
LOCATION_LATITUDE = AttributeSchema(
"location_latitude",
float,
is_attribute_required=True,
attribute_description="Latitude of transport.")
LOCATION_LONGITUDE = AttributeSchema(
"location_longitude",
float,
is_attribute_required=True,
attribute_description="Longitude of transport.")
def __init__(self):
super().__init__("transport_datamodel", [
self.PRICE_PER_KM, self.STATE, self.DRIVER_ID, self.PASSENGERS,
self.LOCATION_LATITUDE, self.LOCATION_LONGITUDE
], "Transport create fully.")
# -*- coding: utf-8 -*-
# ------------------------------------------------------------------------------
#
# Copyright 2018 Fetch.AI Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# ------------------------------------------------------------------------------
from oef.schema import DataModel, AttributeSchema
PRICE_PER_KM = AttributeSchema(
"price_per_km",
bool,
is_attribute_required=True,
attribute_description="Provides the price per kilometer.")
JOURNEY_MODEL = DataModel("journey", [PRICE_PER_KM],
"All possible scooter data.")
# -*- coding: utf-8 -*-
# ------------------------------------------------------------------------------
#
# Copyright 2018 Fetch.AI Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# ------------------------------------------------------------------------------
from oef.schema import DataModel, AttributeSchema
PARKING_PRICE_PER_1HOUR = AttributeSchema(
"price_per_1hour",
bool,
is_attribute_required=True,
attribute_description="Provides the price per 1 hour of parking.")
PARKING_JOURNEY_MODEL = DataModel("journey", [PARKING_PRICE_PER_1HOUR],
"All possible parking data.")
# -*- coding: utf-8 -*-
# ------------------------------------------------------------------------------
#
# Copyright 2018 Fetch.AI Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# ------------------------------------------------------------------------------
from oef.schema import DataModel, AttributeSchema
CHARGE_PRICE_PER_20MIN = AttributeSchema(
"price_per_20m",
bool,
is_attribute_required=True,
attribute_description="Provides the price per 20 minutes of charging.")
CHARGE_JOURNEY_MODEL = DataModel("journey", [CHARGE_PRICE_PER_20MIN],
"All possible charge data.")
class ControllerAgent(OEFAgent):
"""Class for a controller agent."""
CONTROLLER_DATAMODEL = DataModel("tac", [
AttributeSchema("version", int, True,
"Version number of the TAC Controller Agent."),
])
def __init__(self,
name: str = "controller",
oef_addr: str = "127.0.0.1",
oef_port: int = 10000,
version: int = 1,
monitor: Optional[Monitor] = None,
**kwargs):
"""
Initialize a Controller Agent for TAC.
:param name: The name of the OEF Agent.
:param oef_addr: the OEF address.
:param oef_port: the OEF listening port.
:param version: the version of the TAC controller.
:param monitor: the dashboard monitor. If None, defaults to a null (dummy) monitor.
"""
self.name = name
self.crypto = Crypto()
super().__init__(self.crypto.public_key,
oef_addr,
oef_port,
loop=asyncio.new_event_loop())
logger.debug(
"[{}]: Initialized myself as Controller Agent :\n{}".format(
self.name, pprint.pformat(vars())))
self.dispatcher = ControllerDispatcher(self)
self.monitor = NullMonitor(
) if monitor is None else monitor # type: Monitor
self.version = version
self.game_handler = None # type: Optional[GameHandler]
self.last_activity = datetime.datetime.now()
self._message_processing_task = None
self._timeout_checker_task = None
self._is_running = False
self._terminated = False
def on_message(self, msg_id: int, dialogue_id: int, origin: str,
content: bytes) -> None:
"""
Handle a simple message.
The TAC Controller expects that 'content' is a Protobuf serialization of a tac.messages.Request object.
The request is dispatched to the right request handler (using the ControllerDispatcher).
The handler returns an optional response, that is sent back to the sender.
Notice: the message sent back has the same message id, such that the client knows to which request the response is associated to.
:param msg_id: the message id
:param dialogue_id: the dialogue id
:param origin: the public key of the sender.
:param content: the content of the message.
:return: None
"""
logger.debug(
"[{}] on_message: msg_id={}, dialogue_id={}, origin={}".format(
self.name, msg_id, dialogue_id, origin))
self.update_last_activity()
response = self.dispatcher.process_request(
content, origin) # type: Optional[Response]
if response is not None:
self.send_message(msg_id, dialogue_id, origin,
response.serialize())
def on_oef_error(self, answer_id: int,
operation: OEFErrorOperation) -> None:
"""
Handle an oef error.
:param answer_id: the answer id
:param operation: the oef operation
:return: None
"""
logger.error(
"[{}]: Received OEF error: answer_id={}, operation={}".format(
self.name, answer_id, operation))
def on_dialogue_error(self, answer_id: int, dialogue_id: int,
origin: str) -> None:
"""
Handle a dialogue error.
:param answer_id: the answer id
:param dialogue_id: the dialogue id
:param origin: the public key of the sending agent
:return: None
"""
logger.error(
"[{}]: Received Dialogue error: answer_id={}, dialogue_id={}, origin={}"
.format(self.name, answer_id, dialogue_id, origin))
def register(self):
"""
Register on the OEF as a TAC controller agent.
:return: None.
"""
desc = Description({"version": 1},
data_model=self.CONTROLLER_DATAMODEL)
logger.debug("[{}]: Registering with {} data model".format(
self.name, desc.data_model.name))
self.register_service(0, desc)
def dump(self, directory: str, experiment_name: str) -> None:
"""
Dump the details of the simulation.
:param directory: the directory where experiments details are listed.
:param experiment_name: the name of the folder where the data about experiment will be saved.
:return: None.
"""
experiment_dir = directory + "/" + experiment_name
if self.game_handler is None or not self.game_handler.is_game_running(
):
logger.warning(
"[{}]: Game not present. Using empty dictionary.".format(
self.name))
game_dict = {} # type: Dict[str, Any]
else:
game_dict = self.game_handler.current_game.to_dict()
os.makedirs(experiment_dir, exist_ok=True)
with open(os.path.join(experiment_dir, "game.json"), "w") as f:
json.dump(game_dict, f)
def terminate(self) -> None:
"""
Terminate the controller agent.
:return: None
"""
if self._is_running:
logger.debug("[{}]: Terminating the controller...".format(
self.name))
self._is_running = False
self.game_handler.notify_tac_cancelled()
self._loop.call_soon_threadsafe(self.stop)
self._message_processing_task.join()
self._message_processing_task = None
if self.monitor.is_running:
self.monitor.stop()
def check_inactivity_timeout(self, rate: Optional[float] = 2.0) -> None:
"""
Check periodically if the timeout for inactivity or competition expired.
:param: rate: at which rate (in seconds) the frequency of the check.
:return: None
"""
logger.debug(
"[{}]: Started job to check for inactivity of {} seconds. Checking rate: {}"
.format(
self.name,
self.game_handler.tac_parameters.inactivity_timedelta.
total_seconds(), rate))
while True:
if self._is_running is False:
return
time.sleep(rate)
current_time = datetime.datetime.now()
inactivity_duration = current_time - self.last_activity
if inactivity_duration > self.game_handler.tac_parameters.inactivity_timedelta:
logger.debug(
"[{}]: Inactivity timeout expired. Terminating...".format(
self.name))
self.terminate()
return
elif current_time > self.game_handler.tac_parameters.end_time:
logger.debug(
"[{}]: Competition timeout expired. Terminating...".format(
self.name))
self.terminate()
return
def update_last_activity(self):
"""Update the last activity tracker."""
self.last_activity = datetime.datetime.now()
def handle_competition(self, tac_parameters: TACParameters):
"""
Start a Trading Agent Competition.
:param tac_parameters: the parameter of the competition.
:return:
"""
logger.debug("[{}]: Starting competition with parameters: {}".format(
self.name, pprint.pformat(tac_parameters.__dict__)))
self._is_running = True
self._message_processing_task = Thread(target=self.run)
self.monitor.start(None)
self.monitor.update()
self.game_handler = GameHandler(self, tac_parameters)
self._message_processing_task.start()
if self.game_handler.handle_registration_phase():
# start the inactivity timeout.
self._timeout_checker_task = Thread(
target=self.check_inactivity_timeout)
self._timeout_checker_task.run()
else:
self.terminate()
def wait_and_handle_competition(self,
tac_parameters: TACParameters) -> None:
"""
Wait until the current time is greater than the start time, then, start the TAC.
:param tac_parameters: the parameters for TAC.
:return: None
"""
now = datetime.datetime.now()
logger.debug(
"[{}]: waiting for starting the competition: start_time={}, current_time={}, timedelta ={}s"
.format(self.name, str(tac_parameters.start_time), str(now),
(tac_parameters.start_time - now).total_seconds()))
seconds_to_wait = (tac_parameters.start_time - now).total_seconds()
time.sleep(0.5 if seconds_to_wait < 0 else seconds_to_wait)
self.handle_competition(tac_parameters)
def test_raise_when_have_incorrect_types(self):
"""
Test that if an attribute value has a value inconsistent with its schema, we moan.
"""
check_inconsistency_checker([AttributeSchema("foo", float, True)],
{"foo": "bar"}, "incorrect type")
def test_raise_when_have_unallowed_types(self):
"""
Test that if an attribute value has a value inconsistent with its schema, we moan.
"""
check_inconsistency_checker([AttributeSchema("foo", tuple, True)],
{"foo": tuple()}, "unallowed type")
def test_raise_when_not_required_attribute_is_omitted(self):
"""
Test that if we miss out a required attribute, we moan about it
"""
check_inconsistency_checker([AttributeSchema("foo", str, True)], {},
"Missing required attribute.")
# -*- coding: utf-8 -*-
# ------------------------------------------------------------------------------
#
# Copyright 2018 Fetch.AI Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# ------------------------------------------------------------------------------
from oef.schema import DataModel, AttributeSchema
PRICE_PER_ENERGY_PERCENT = AttributeSchema(
"price_per_energy_percent",
bool,
is_attribute_required=True,
attribute_description="Provides the price per one energy percent")
JOURNEY_MODEL = DataModel("journey", [PRICE_PER_ENERGY_PERCENT],
"All possible scooter data.")
# Instead of having an OEF Node running somewhere, we can use a in-process instance of an OEF Node.
# It will run and process messages concurrently with the other agents.
local_node = OEFLocalProxy.LocalNode()
client_proxy = OEFLocalProxy("greetings_client", local_node)
server_proxy = OEFLocalProxy("greetings_server", local_node)
# create agents
client_agent = GreetingsAgent(client_proxy)
server_agent = GreetingsAgent(server_proxy)
# connect the agents to the OEF
client_agent.connect()
server_agent.connect()
# register the greetings service agent on the OEF
say_hello = AttributeSchema("say_hello", bool, True,
"The agent answers to 'hello' messages.")
greetings_model = DataModel("greetings", [say_hello], "Greetings service.")
greetings_description = Description({"say_hello": True}, greetings_model)
server_agent.register_service(0, greetings_description)
# the client executes the search for greetings services
# we are looking for services that answers to "hello" messages
query = Query([Constraint("say_hello", Eq(True))], greetings_model)
print("[{}]: Search for 'greetings' services. search_id={}".format(
client_agent.public_key, 0))
client_agent.search_services(0, query)
# run the agents
try:
loop = asyncio.get_event_loop()
def test_not_equal_when_compared_with_different_type(self):
a_query = Query([Constraint("foo", Eq(0))],
DataModel("bar", [AttributeSchema("foo", int, True)]))
not_a_query = tuple()
assert a_query != not_a_query
import json
import unittest
import sys
import csv
import os
from oef.schema import Description
from utils.src.python.protostuff import dictToProto, protoToDict
from protocol.src.proto import agent_pb2
from oef.schema import DataModel, AttributeSchema
from oef.agents import OefMessageHandler
WIND_SPEED_ATTR = AttributeSchema(
"wind_speed",
bool,
is_attribute_required=True,
attribute_description="Provides wind speed measurements.")
TEMPERATURE_ATTR = AttributeSchema(
"temperature",
bool,
is_attribute_required=True,
attribute_description="Provides temperature measurements.")
AIR_PRESSURE_ATTR = AttributeSchema(
"air_pressure",
bool,
is_attribute_required=True,
attribute_description="Provides air pressure measurements.")
origin))
self.send_message(1, dialogue_id, origin, content)
if __name__ == '__main__':
# create agent and connect it to OEF
server_agent = EchoServiceAgent("echo_server",
oef_addr="oef-node",
oef_port=10000,
loop=asyncio.get_event_loop())
server_agent.connect()
# register a service on the OEF
echo_feature = AttributeSchema(
"does_echo", bool, True,
"Whether the service agent can do echo or not.")
echo_model = DataModel("echo", [echo_feature], "echo service.")
echo_description = Description({"does_echo": True}, echo_model)
msg_id = 22
server_agent.register_service(msg_id, echo_description)
# run the agent
print("[{}]: Waiting for messages...".format(server_agent.public_key))
try:
server_agent.run()
finally:
print("[{}]: Disconnecting...".format(server_agent.public_key))
server_agent.stop()
server_agent.disconnect()
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
# ------------------------------------------------------------------------------
from oef.schema import DataModel, AttributeSchema, Location
PRICE_PER_KM = AttributeSchema("price_per_km", int, True,
"Provides the price per kilometer.")
PRICE_KWH = AttributeSchema("price_kilowatt_hour", int, True,
"Provides the price kilowatt hour.")
CHARGER_BONUS = AttributeSchema("charger_bonus", int, False,
"Provides bonus cash back for charging here.")
CHARGER_LOCATION = AttributeSchema("charger_location", Location, True,
"The location of the charger ")
CHARGER_AVAILABLE = AttributeSchema(
"charger_available", bool, True,
"Provides the availability of the charger ")
CHARGER_OWNER = AttributeSchema(
"charger_owner", str, False, "Provides charger's owner, "
"it could be person id or name name")
