code stringlengths 17 6.64M |
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@dataclass
class CancelOrderMsg(OrderMsg):
order: LimitOrder
tag: str
metadata: dict
|
@dataclass
class PartialCancelOrderMsg(OrderMsg):
order: LimitOrder
quantity: int
tag: str
metadata: dict
|
@dataclass
class ModifyOrderMsg(OrderMsg):
old_order: LimitOrder
new_order: LimitOrder
|
@dataclass
class ReplaceOrderMsg(OrderMsg):
agent_id: int
old_order: LimitOrder
new_order: LimitOrder
|
@dataclass
class OrderBookMsg(Message, ABC):
pass
|
@dataclass
class OrderAcceptedMsg(OrderBookMsg):
order: LimitOrder
|
@dataclass
class OrderExecutedMsg(OrderBookMsg):
order: Order
|
@dataclass
class OrderCancelledMsg(OrderBookMsg):
order: LimitOrder
|
@dataclass
class OrderPartialCancelledMsg(OrderBookMsg):
new_order: LimitOrder
|
@dataclass
class OrderModifiedMsg(OrderBookMsg):
new_order: LimitOrder
|
@dataclass
class OrderReplacedMsg(OrderBookMsg):
old_order: LimitOrder
new_order: LimitOrder
|
@dataclass
class QueryMsg(Message, ABC):
symbol: str
|
@dataclass
class QueryResponseMsg(Message, ABC):
symbol: str
mkt_closed: bool
|
@dataclass
class QueryLastTradeMsg(QueryMsg):
pass
|
@dataclass
class QueryLastTradeResponseMsg(QueryResponseMsg):
last_trade: Optional[int]
|
@dataclass
class QuerySpreadMsg(QueryMsg):
depth: int
|
@dataclass
class QuerySpreadResponseMsg(QueryResponseMsg):
depth: int
bids: List[Tuple[(int, int)]]
asks: List[Tuple[(int, int)]]
last_trade: Optional[int]
|
@dataclass
class QueryOrderStreamMsg(QueryMsg):
length: int
|
@dataclass
class QueryOrderStreamResponseMsg(QueryResponseMsg):
length: int
orders: List[Dict[(str, Any)]]
|
@dataclass
class QueryTransactedVolMsg(QueryMsg):
lookback_period: str
|
@dataclass
class QueryTransactedVolResponseMsg(QueryResponseMsg):
bid_volume: int
ask_volume: int
|
class OrderSizeModel():
def __init__(self) -> None:
self.model = GeneralMixtureModel.from_json(json.dumps(order_size))
def sample(self, random_state: np.random.RandomState) -> float:
return round(self.model.sample(random_state=random_state))
|
class MeanRevertingOracle(Oracle):
'The MeanRevertingOracle requires three parameters: a mean fundamental value,\n a mean reversion coefficient, and a shock variance. It constructs and retains\n a fundamental value time series for each requested symbol, and provides noisy\n observations of those values ... |
class Oracle():
def get_daily_open_price(self, symbol: str, mkt_open: NanosecondTime, cents: bool=True) -> int:
raise NotImplementedError
|
class SparseMeanRevertingOracle(MeanRevertingOracle):
'The SparseMeanRevertingOracle produces a fundamental value time series for\n each requested symbol, and provides noisy observations of the fundamental\n value upon agent request. This "sparse discrete" fundamental uses a\n combination of two process... |
class Side(Enum):
BID = 'BID'
ASK = 'ASK'
def is_bid(self) -> bool:
return (self == Side.BID)
def is_ask(self) -> bool:
return (self == Side.ASK)
|
class Order(ABC):
'A basic Order type used by an Exchange to conduct trades or maintain an order book.\n\n This should not be confused with order Messages agents send to request an Order.\n Specific order types will inherit from this (like LimitOrder).\n '
_order_id_counter: int = 0
@abstractmet... |
class LimitOrder(Order):
"\n LimitOrder class that inherits from Order class and adds a limit price and a\n hidden order flag.\n\n These are the Orders that typically go in an Exchange's OrderBook.\n "
def __init__(self, agent_id: int, time_placed: NanosecondTime, symbol: str, quantity: int, side... |
class MarketOrder(Order):
'MarketOrder class, inherits from Order class.'
def __init__(self, agent_id: int, time_placed: NanosecondTime, symbol: str, quantity: int, side: Side, order_id: Optional[int]=None, tag: Optional[Any]=None) -> None:
super().__init__(agent_id, time_placed, symbol, quantity, si... |
class PriceLevel():
'\n A class that represents a single price level containing multiple orders for one\n side of an order book. The option to have hidden orders is supported. This class\n abstracts the complextity of handling both visible and hidden orders away from\n the parent order book.\n\n Vi... |
def delist(list_of_lists):
return [x for b in list_of_lists for x in b]
|
def numeric(s):
'Returns numeric type from string, stripping commas from the right.\n\n Adapted from https://stackoverflow.com/a/379966.\n '
s = s.rstrip(',')
try:
return int(s)
except ValueError:
try:
return float(s)
except ValueError:
return s
|
def get_value_from_timestamp(s: pd.Series, ts: datetime.datetime):
'Get the value of s corresponding to closest datetime to ts.\n\n Arguments:\n s: Pandas Series with pd.DatetimeIndex.\n ts: Timestamp at which to retrieve data.\n '
ts_str = ts.strftime('%Y-%m-%d %H:%M:%S')
s = s.loc[(~... |
@contextmanager
def ignored(warning_str, *exceptions):
'Context manager that wraps the code block in a try except statement, catching\n specified exceptions and printing warning supplied by user.\n\n Arguments:\n warning_str: Warning statement printed when exception encountered.\n exceptions: ... |
def generate_uniform_random_pairwise_dist_on_line(left: float, right: float, num_points: int, random_state: np.random.RandomState) -> np.ndarray:
'Uniformly generate points on an interval, and return numpy array of pairwise\n distances between points.\n\n Arguments:\n left: Left endpoint of interval.... |
def meters_to_light_ns(x):
'Converts x in units of meters to light nanoseconds.'
x_lns = (x / 0.299792458)
x_lns = x_lns.astype(int)
return x_lns
|
def validate_window_size(s):
"Check if s is integer or string 'adaptive'."
try:
return int(s)
except ValueError:
if (s.lower() == 'adaptive'):
return s.lower()
else:
raise ValueError(f'String {s} must be integer or string "adaptive".')
|
def sigmoid(x, beta):
'Numerically stable sigmoid function.\n\n Adapted from https://timvieira.github.io/blog/post/2014/02/11/exp-normalize-trick/"\n '
if (x >= 0):
z = np.exp(((- beta) * x))
return (1 / (1 + z))
else:
z = np.exp((beta * x))
return (z / (1 + z))
|
def subdict(d, keys):
return dict(((k, v) for (k, v) in d.items() if (k in keys)))
|
def restrictdict(d, keys):
inter = [k for k in d.keys() if (k in keys)]
return subdict(d, inter)
|
def dollarize(cents: Union[(List[int], int)]) -> Union[(List[str], str)]:
'Dollarizes int-cents prices for printing.\n\n Defined outside the class for utility access by non-agent classes.\n\n Arguments:\n cents:\n '
if isinstance(cents, list):
return [dollarize(x) for x in cents]
eli... |
def generate_latency_model(agent_count, latency_type='deterministic'):
assert (latency_type in ['deterministic', 'no_latency']), 'Please select a correct latency_type'
latency_rstate = np.random.RandomState(seed=np.random.randint(low=0, high=(2 ** 32)))
pairwise = (agent_count, agent_count)
if (latenc... |
def config_add_agents(orig_config_state, agents):
agent_count = len(orig_config_state['agents'])
orig_config_state['agents'] = (orig_config_state['agents'] + agents)
lat_mod = generate_latency_model((agent_count + len(agents)))
orig_config_state['agent_latency_model'] = lat_mod
return orig_config_... |
def reset_env():
Order._order_id_counter = 0
|
def test_poisson_time_generator():
gen = PoissonTimeGenerator(lambda_time=2, random_generator=np.random.RandomState(seed=1))
for _ in range(10):
print(gen.next())
|
class FakeExchangeAgent():
def __init__(self):
self.messages = []
self.current_time = TIME
self.mkt_open = TIME
self.book_logging = None
self.stream_history = 10
def reset(self):
self.messages = []
def send_message(self, recipient_id: int, message: Messag... |
def setup_book_with_orders(bids: List[Tuple[(int, List[int])]]=[], asks: List[Tuple[(int, List[int])]]=[]) -> Tuple[(OrderBook, FakeExchangeAgent, List[LimitOrder])]:
agent = FakeExchangeAgent()
book = OrderBook(agent, SYMBOL)
orders = []
for (price, quantities) in bids:
for quantity in quanti... |
def test_cancel_order():
(book, agent, orders) = setup_book_with_orders(bids=[(100, [40, 10]), (200, [10, 30, 20, 10])], asks=[(300, [10, 50, 20]), (400, [40, 10]), (500, [20])])
book.cancel_order(orders[1])
assert (book.get_l3_bid_data() == [(200, [10, 30, 20, 10]), (100, [40])])
assert (len(agent.me... |
def test_get_l1_bid_ask_data():
(book, _, _) = setup_book_with_orders(bids=[], asks=[])
assert (book.get_l1_bid_data() == None)
assert (book.get_l1_ask_data() == None)
(book, _, _) = setup_book_with_orders(bids=[(100, [40, 10]), (200, [10, 30, 20, 10])], asks=[(300, [10, 50, 20]), (400, [40, 10]), (50... |
def test_get_l2_bid_ask_data():
(book, _, _) = setup_book_with_orders(bids=[], asks=[])
assert (book.get_l2_bid_data() == [])
assert (book.get_l2_ask_data() == [])
(book, _, _) = setup_book_with_orders(bids=[(100, [40, 10]), (200, [10, 30, 20, 10])], asks=[(300, [10, 50, 20]), (400, [40, 10]), (500, [... |
def test_get_l3_bid_ask_data():
(book, _, _) = setup_book_with_orders(bids=[], asks=[])
assert (book.get_l3_bid_data() == [])
assert (book.get_l3_ask_data() == [])
(book, _, _) = setup_book_with_orders(bids=[(100, [40, 10]), (200, [10, 30, 20, 10])], asks=[(300, [10, 50, 20]), (400, [40, 10]), (500, [... |
def test_get_transacted_volume():
(book, _, _) = setup_book_with_orders(bids=[(100, [40, 10]), (200, [10, 30, 20, 10])], asks=[(300, [10, 50, 20]), (400, [40, 10]), (500, [20])])
for q in [10, 30, 20, 10]:
order = MarketOrder(agent_id=1, time_placed=TIME, symbol=SYMBOL, quantity=q, side=Side.BID)
... |
def test_get_imbalance():
(book, _, _) = setup_book_with_orders(bids=[(100, [10])], asks=[(200, [10])])
assert (book.get_imbalance() == (0, None))
(book, _, _) = setup_book_with_orders(bids=[(100, [20])], asks=[(200, [10])])
assert (book.get_imbalance() == (0.5, Side.BID))
(book, _, _) = setup_boo... |
def test_handle_limit_orders():
bid_order = LimitOrder(agent_id=1, time_placed=TIME, symbol=SYMBOL, quantity=10, side=Side.BID, limit_price=100)
agent = FakeExchangeAgent()
book = OrderBook(agent, SYMBOL)
book.handle_limit_order(bid_order)
assert (book.bids == [PriceLevel([(bid_order, {})])])
... |
def test_handle_hidden_limit_orders():
bid_order = LimitOrder(agent_id=1, time_placed=TIME, symbol=SYMBOL, quantity=10, side=Side.BID, is_hidden=True, limit_price=100)
agent = FakeExchangeAgent()
book = OrderBook(agent, SYMBOL)
book.handle_limit_order(bid_order)
assert (book.bids == [PriceLevel([(... |
def test_handle_matching_limit_orders():
(book, agent, _) = setup_book_with_orders(asks=[(100, [30])])
bid_order = LimitOrder(agent_id=1, time_placed=TIME, symbol=SYMBOL, quantity=30, side=Side.BID, is_hidden=False, limit_price=110)
book.handle_limit_order(bid_order)
assert (book.bids == [])
asser... |
def test_handle_bad_limit_orders():
agent = FakeExchangeAgent()
book = OrderBook(agent, SYMBOL)
order = LimitOrder(agent_id=1, time_placed=TIME, symbol='BAD', quantity=10, side=Side.BID, is_hidden=True, limit_price=100)
with pytest.warns(UserWarning):
book.handle_limit_order(order)
order =... |
def test_handle_insert_by_id_limit_order():
agent = FakeExchangeAgent()
book = OrderBook(agent, SYMBOL)
order1 = LimitOrder(order_id=1, agent_id=1, time_placed=TIME, symbol=SYMBOL, quantity=10, side=Side.BID, limit_price=100)
order2 = LimitOrder(order_id=2, agent_id=1, time_placed=TIME, symbol=SYMBOL,... |
def test_handle_market_order_bid_1():
'Test buy order that partially consumes one order'
(book, agent, limit_orders) = setup_book_with_orders(asks=[(100, [30])])
market_order = MarketOrder(agent_id=2, time_placed=TIME, symbol=SYMBOL, quantity=10, side=Side.BID)
book.handle_market_order(market_order)
... |
def test_handle_market_order_bid_2():
'Test buy order that fully consumes one order'
(book, agent, limit_orders) = setup_book_with_orders(asks=[(100, [30])])
market_order = MarketOrder(agent_id=2, time_placed=TIME, symbol=SYMBOL, quantity=30, side=Side.BID)
book.handle_market_order(market_order)
a... |
def test_handle_market_order_bid_3():
'Test buy order that consumes multiple orders'
(book, agent, limit_orders) = setup_book_with_orders(asks=[(100, [30, 40])])
market_order = MarketOrder(agent_id=2, time_placed=TIME, symbol=SYMBOL, quantity=70, side=Side.BID)
book.handle_market_order(market_order)
... |
def test_handle_market_order_bid_4():
'Test buy order that consumes multiple orders at different prices'
(book, agent, limit_orders) = setup_book_with_orders(asks=[(100, [30]), (200, [40])])
market_order = MarketOrder(agent_id=2, time_placed=TIME, symbol=SYMBOL, quantity=70, side=Side.BID)
book.handle... |
def test_handle_market_order_ask_1():
'Test sell order that partially consumes one order'
(book, agent, limit_orders) = setup_book_with_orders(bids=[(100, [30])])
market_order = MarketOrder(agent_id=2, time_placed=TIME, symbol=SYMBOL, quantity=10, side=Side.ASK)
book.handle_market_order(market_order)
... |
def test_handle_market_order_ask_2():
'Test sell order that fully consumes one order'
(book, agent, limit_orders) = setup_book_with_orders(bids=[(100, [30])])
market_order = MarketOrder(agent_id=2, time_placed=TIME, symbol=SYMBOL, quantity=30, side=Side.ASK)
book.handle_market_order(market_order)
... |
def test_handle_market_order_ask_3():
'Test sell order that consumes multiple orders'
(book, agent, limit_orders) = setup_book_with_orders(bids=[(100, [30, 40])])
market_order = MarketOrder(agent_id=2, time_placed=TIME, symbol=SYMBOL, quantity=70, side=Side.ASK)
book.handle_market_order(market_order)
... |
def test_handle_market_order_ask_4():
'Test sell order that consumes multiple orders at different prices'
(book, agent, limit_orders) = setup_book_with_orders(bids=[(200, [40]), (100, [30])])
market_order = MarketOrder(agent_id=2, time_placed=TIME, symbol=SYMBOL, quantity=70, side=Side.ASK)
book.handl... |
def test_handle_bad_limit_orders():
(book, _, _) = setup_book_with_orders()
order = MarketOrder(agent_id=1, time_placed=TIME, symbol='BAD', quantity=70, side=Side.ASK)
with pytest.warns(UserWarning):
book.handle_market_order(order)
order = MarketOrder(agent_id=1, time_placed=TIME, symbol=SYMBO... |
def test_modify_order_quantity_down():
(book, agent, orders) = setup_book_with_orders(bids=[(100, [40, 10]), (200, [10, 30, 20, 10])], asks=[(300, [10, 50, 20]), (400, [40, 10]), (500, [20])])
modified_order = deepcopy(orders[0])
modified_order.quantity = 30
book.modify_order(orders[0], modified_order... |
def test_modify_order_quantity_up():
(book, agent, orders) = setup_book_with_orders(bids=[(100, [40, 10]), (200, [10, 30, 20, 10])], asks=[(300, [10, 50, 20]), (400, [40, 10]), (500, [20])])
modified_order = deepcopy(orders[0])
modified_order.quantity = 70
book.modify_order(orders[0], modified_order)
... |
def test_empty_book():
book = OrderBook(FakeExchangeAgent(), SYMBOL)
assert (book.get_l1_bid_data() == None)
assert (book.get_l1_ask_data() == None)
assert (book.get_l2_bid_data() == [])
assert (book.get_l2_ask_data() == [])
assert (book.get_l3_bid_data() == [])
assert (book.get_l3_ask_dat... |
@pytest.fixture
def price_level():
reset_env()
return PriceLevel([(LimitOrder(0, 0, '', 10, Side.BID, 100, is_hidden=False), {}), (LimitOrder(0, 0, '', 10, Side.BID, 100, is_hidden=True), {}), (LimitOrder(0, 0, '', 10, Side.BID, 100, is_hidden=False), {}), (LimitOrder(0, 0, '', 10, Side.BID, 100, is_hidden=Tr... |
def test_init(price_level):
assert (len(price_level.visible_orders) == 3)
assert (len(price_level.hidden_orders) == 2)
assert (price_level.price == 100)
assert (price_level.side == Side.BID)
|
def test_bad_init():
with pytest.raises(ValueError):
_ = PriceLevel([])
|
def test_add_order(price_level):
order = LimitOrder(0, 0, '', 10, Side.BID, 100, is_hidden=False)
price_level.add_order(order)
assert (price_level.visible_orders[(- 1)] == (order, {}))
order = LimitOrder(0, 0, '', 10, Side.BID, 100, is_hidden=True)
price_level.add_order(order)
assert (price_le... |
def test_update_order_quantity(price_level):
assert (price_level.update_order_quantity(0, 5) == True)
assert (price_level.visible_orders[0][0].order_id == 0)
assert (price_level.update_order_quantity(0, 15) == True)
assert (price_level.visible_orders[(- 1)][0].order_id == 0)
assert (price_level.up... |
def test_remove_order(price_level):
(order, _) = price_level.remove_order(0)
assert isinstance(order, LimitOrder)
assert (order.order_id == 0)
assert (len(price_level.visible_orders) == 2)
(order, _) = price_level.remove_order(1)
assert isinstance(order, LimitOrder)
assert (order.order_id ... |
def test_peek(price_level):
assert (price_level.peek() == price_level.visible_orders[0])
price_level.visible_orders = []
assert (price_level.peek() == price_level.hidden_orders[0])
price_level.hidden_orders = []
with pytest.raises(ValueError):
price_level.peek()
|
def test_pop(price_level):
order = price_level.visible_orders[0]
assert (price_level.pop() == order)
price_level.visible_orders = []
order = price_level.hidden_orders[0]
assert (price_level.pop() == order)
price_level.hidden_orders = []
with pytest.raises(ValueError):
price_level.p... |
def test_order_is_match(price_level):
order = LimitOrder(0, 0, '', 10, Side.ASK, 90, is_hidden=False)
assert (price_level.order_is_match(order) == True)
order = LimitOrder(0, 0, '', 10, Side.ASK, 100, is_hidden=False)
assert (price_level.order_is_match(order) == True)
order = LimitOrder(0, 0, '', ... |
def test_order_has_better_price(price_level):
order = LimitOrder(0, 0, '', 10, Side.BID, 90, is_hidden=False)
assert (price_level.order_has_better_price(order) == False)
order = LimitOrder(0, 0, '', 10, Side.BID, 100, is_hidden=False)
assert (price_level.order_has_better_price(order) == False)
ord... |
def test_order_has_worse_price(price_level):
order = LimitOrder(0, 0, '', 10, Side.BID, 90, is_hidden=False)
assert (price_level.order_has_worse_price(order) == True)
order = LimitOrder(0, 0, '', 10, Side.BID, 100, is_hidden=False)
assert (price_level.order_has_worse_price(order) == False)
order =... |
def test_order_has_equal_price(price_level):
order = LimitOrder(0, 0, '', 10, Side.BID, 90, is_hidden=False)
assert (price_level.order_has_equal_price(order) == False)
order = LimitOrder(0, 0, '', 10, Side.BID, 100, is_hidden=False)
assert (price_level.order_has_equal_price(order) == True)
order =... |
def test_total_quantity(price_level):
assert (price_level.total_quantity == 30)
price_level.visible_orders = []
price_level.hidden_orders = []
assert (price_level.total_quantity == 0)
|
def test_is_empty(price_level):
assert (price_level.is_empty == False)
price_level.visible_orders = []
assert (price_level.is_empty == False)
price_level.hidden_orders = []
assert (price_level.is_empty == True)
|
def test_eq(price_level):
assert (price_level == price_level)
lo = LimitOrder(0, 0, '', 10, Side.BID, 90, is_hidden=False)
assert (PriceLevel([(lo, {})]) != price_level)
|
def test_create_price_to_comply_order():
order = LimitOrder(agent_id=1, time_placed=TIME, symbol=SYMBOL, quantity=10, side=Side.BID, is_price_to_comply=True, limit_price=100)
agent = FakeExchangeAgent()
book = OrderBook(agent, SYMBOL)
book.handle_limit_order(deepcopy(order))
hidden_half = deepcopy... |
def test_fill_price_to_comply_order():
order = LimitOrder(agent_id=1, time_placed=TIME, symbol=SYMBOL, quantity=10, side=Side.BID, is_price_to_comply=True, limit_price=100)
agent = FakeExchangeAgent()
book = OrderBook(agent, SYMBOL)
book.handle_limit_order(order)
hidden_half = deepcopy(order)
... |
def test_cancel_price_to_comply_order():
order = LimitOrder(agent_id=1, time_placed=TIME, symbol=SYMBOL, quantity=10, side=Side.BID, is_price_to_comply=True, limit_price=100)
agent = FakeExchangeAgent()
book = OrderBook(agent, SYMBOL)
book.handle_limit_order(order)
assert (book.cancel_order(order)... |
def test_modify_price_to_comply_order():
pass
|
def test_replace_price_to_comply_order():
old_order = LimitOrder(agent_id=1, time_placed=TIME, symbol=SYMBOL, quantity=10, side=Side.BID, is_price_to_comply=True, limit_price=100)
agent = FakeExchangeAgent()
book = OrderBook(agent, SYMBOL)
book.handle_limit_order(old_order)
assert (len(book.asks) ... |
def test_replace_order():
(book, agent, orders) = setup_book_with_orders(bids=[(100, [40, 10]), (200, [10, 30, 20, 10])], asks=[(300, [10, 50, 20]), (400, [40, 10]), (500, [20])])
new_order = LimitOrder(agent_id=1, time_placed=TIME, symbol=SYMBOL, quantity=50, side=Side.BID, limit_price=100)
book.replace_... |
def test_constant_depth_generator():
g = ConstantDepthGenerator(10)
assert (g.next() == 10)
assert (g.mean() == 10)
|
def test_constant_order_size_generator():
g = ConstantOrderSizeGenerator(10)
assert (g.next() == 10)
assert (g.mean() == 10)
|
def test_uniform_depth_generator():
g = UniformDepthGenerator(0, 10, np.random.RandomState())
assert (g.mean() == 5)
|
def test_uniform_order_size_generator():
g = UniformOrderSizeGenerator(0, 10, np.random.RandomState())
assert (g.mean() == 5)
|
def test_gym_runner_markets_execution():
env = gym.make('markets-execution-v0', background_config='rmsc04')
env.seed(0)
state = env.reset()
for i in range(5):
(state, reward, done, info) = env.step(0)
env.step(1)
env.step(2)
env.seed()
env.reset()
env.close()
|
def test_gym_runner_markets_daily_investor():
env = gym.make('markets-daily_investor-v0', background_config='rmsc04')
env.seed(0)
state = env.reset()
for i in range(5):
(state, reward, done, info) = env.step(0)
env.step(1)
env.step(2)
env.seed()
env.reset()
env.close()
|
def test_order_id_generation():
Order._order_id_counter = 0
order1 = MarketOrder(1, TIME, 'X', 1, True)
order2 = MarketOrder(1, TIME, 'X', 1, True)
order3 = MarketOrder(1, TIME, 'X', 1, True)
assert (order1.order_id == 0)
assert (order2.order_id == 1)
assert (order3.order_id == 2)
Orde... |
def test_order_equality():
order1 = LimitOrder(1, TIME, 'X', 1, True, 1)
order2 = LimitOrder(1, TIME, 'X', 1, True, 1)
assert (order1 == order1)
assert (order1 == deepcopy(order1))
assert (order1 != order2)
|
def test_base_order_init():
with pytest.raises(TypeError):
Order(1, TIME, 'X', 1, True)
|
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