def test_to_pandas(self):
# Fix the timestamp here so that we can test order age accurately
created = 1625835199511442
now_ts = created + 100 * 1e6
self.maxDiff = None
orders = [
LimitOrder("HBOT_1", "A-B", True, "A", "B", Decimal("1"), Decimal("1.5")),
LimitOrder(f"HBOT_{str(created)}", "C-D", True, "C", "D", Decimal("1"), Decimal("1")),
LimitOrder("HBOT_2", "A-B ", False, "A", "B", Decimal("2.5"), Decimal("1"), Decimal("0"), created, LimitOrderStatus.OPEN),
LimitOrder(f"HBOT_{str(created)}", "A-B ", False, "A", "B", Decimal("2"), Decimal("1"), Decimal(0), created, LimitOrderStatus.CANCELED),
]
df = LimitOrder.to_pandas(orders, 1.5, end_time_order_age=now_ts)
# Except df output is as below
# Order ID Type Price Spread Amount Age Hang
# HBOT_2 sell 2.5 66.67% 1.0 00:01:40 n/a
# ...1442 sell 2.0 33.33% 1.0 00:01:40 n/a
# HBOT_1 buy 1.0 33.33% 1.5 n/a n/a
# ...1442 buy 1.0 33.33% 1.0 00:01:40 n/a
# we can't compare the text output directly as for some weird reason the test file passes when run individually
# but will fail under coverage run -m nose test.hummingbot
# self.assertEqual(expect_txt, df.to_string(index=False, max_colwidth=50))
self.assertEqual("HBOT_2", df["Order ID"][0])
self.assertEqual("sell", df["Type"][0])
self.assertAlmostEqual(2.5, df["Price"][0])
self.assertEqual("66.67%", df["Spread"][0])
self.assertAlmostEqual(1., df["Amount"][0])
self.assertEqual("00:01:40", df["Age"][0])
self.assertEqual("n/a", df["Hang"][0])
# Test to see if hanging orders are displayed correctly
df = LimitOrder.to_pandas(orders, 1.5, ["HBOT_1", "HBOT_2"], end_time_order_age=now_ts)
# Except df output is as below
# Order ID Type Price Spread Amount Age Hang
# HBOT_2 sell 2.5 66.67% 1.0 00:01:40 yes
# ...1442 sell 2.0 33.33% 1.0 00:01:40 no
# HBOT_1 buy 1.0 33.33% 1.5 n/a yes
# ...1442 buy 1.0 33.33% 1.0 00:01:40 no
self.assertEqual("HBOT_2", df["Order ID"][0])
self.assertEqual("sell", df["Type"][0])
self.assertAlmostEqual(2.5, df["Price"][0])
self.assertEqual("66.67%", df["Spread"][0])
self.assertAlmostEqual(1., df["Amount"][0])
self.assertEqual("00:01:40", df["Age"][0])
self.assertEqual("yes", df["Hang"][0])
# Test to see if df is created and order age is calculated
df = LimitOrder.to_pandas(orders, 1.5, [])
self.assertAlmostEqual(2.5, df["Price"][0])
self.assertTrue(":" in df["Age"][0])
def format_status(self) -> str:
lines = []
warning_lines = []
for market_info in self._market_infos.values():
active_orders = self.market_info_to_active_orders.get(
market_info, [])
warning_lines.extend(self.network_warning([market_info]))
markets_df = self.market_status_data_frame([market_info])
lines.extend(
["", " Markets:"] +
[" " + line for line in str(markets_df).split("\n")])
assets_df = self.wallet_balance_data_frame([market_info])
lines.extend(
["", " Assets:"] +
[" " + line for line in str(assets_df).split("\n")])
# See if there're any open orders.
if active_orders:
df = LimitOrder.to_pandas(active_orders)
df_lines = str(df).split("\n")
lines.extend(["", " Active orders:"] +
[" " + line for line in df_lines])
else:
lines.extend(["", " No active maker orders."])
warning_lines.extend(self.balance_warning([market_info]))
if warning_lines:
lines.extend(["", "*** WARNINGS ***"] + warning_lines)
return "\n".join(lines)
def format_status(self) -> str:
lines: list = []
warning_lines: list = []
lines.extend(self.configuration_status_lines())
for market_info in self._market_infos.values():
active_orders = self.market_info_to_active_orders.get(
market_info, [])
warning_lines.extend(self.network_warning([market_info]))
markets_df = self.market_status_data_frame([market_info])
lines.extend(
["", " Markets:"] +
[" " + line for line in str(markets_df).split("\n")])
assets_df = self.wallet_balance_data_frame([market_info])
lines.extend(
["", " Assets:"] +
[" " + line for line in str(assets_df).split("\n")])
# See if there're any open orders.
if len(active_orders) > 0:
df = LimitOrder.to_pandas(active_orders)
df_lines = str(df).split("\n")
lines.extend(["", " Active orders:"] +
[" " + line for line in df_lines])
else:
lines.extend(["", " No active maker orders."])
filled_trades = self.filled_trades()
average_price = (statistics.mean(
[trade.price
for trade in filled_trades]) if filled_trades else Decimal(0))
lines.extend([
"", f" Average filled orders price: "
f"{PerformanceMetrics.smart_round(average_price)} "
f"{market_info.quote_asset}"
])
lines.extend([
f" Pending amount: {PerformanceMetrics.smart_round(self._quantity_remaining)} "
f"{market_info.base_asset}"
])
warning_lines.extend(self.balance_warning([market_info]))
if warning_lines:
lines.extend(["", "*** WARNINGS ***"] + warning_lines)
return "\n".join(lines)
def format_status(self) -> str:
lines: list = []
warning_lines: list = []
lines.extend(self.configuration_status_lines())
for market_info in self._market_infos.values():
active_orders = self.market_info_to_active_orders.get(
market_info, [])
warning_lines.extend(self.network_warning([market_info]))
markets_df = self.market_status_data_frame([market_info])
lines.extend(
["", " Markets:"] +
[" " + line for line in markets_df.to_string().split("\n")])
assets_df = self.wallet_balance_data_frame([market_info])
lines.extend(
["", " Assets:"] +
[" " + line for line in assets_df.to_string().split("\n")])
# See if there're any open orders.
if len(active_orders) > 0:
price_provider = None
for market_info in self._market_infos.values():
price_provider = market_info
if price_provider is not None:
df = LimitOrder.to_pandas(
active_orders,
mid_price=price_provider.get_mid_price())
if self._is_buy:
# Descend from the price closest to the mid price
df = df.sort_values(by=['Price'], ascending=False)
else:
# Ascend from the price closest to the mid price
df = df.sort_values(by=['Price'], ascending=True)
df = df.reset_index(drop=True)
df_lines = df.to_string().split("\n")
lines.extend(["", " Active orders:"] +
[" " + line for line in df_lines])
else:
lines.extend(["", " No active maker orders."])
filled_trades = self.filled_trades()
average_price = (statistics.mean(
[trade.price
for trade in filled_trades]) if filled_trades else Decimal(0))
lines.extend([
"", f" Average filled orders price: "
f"{PerformanceMetrics.smart_round(average_price)} "
f"{market_info.quote_asset}"
])
lines.extend([
f" Pending amount: {PerformanceMetrics.smart_round(self._quantity_remaining)} "
f"{market_info.base_asset}"
])
warning_lines.extend(self.balance_warning([market_info]))
if warning_lines:
lines.extend(["", "*** WARNINGS ***"] + warning_lines)
return "\n".join(lines)