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bug fixes

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stevekeyharvey
2026-04-27 17:57:58 +00:00
parent a94c0a55be
commit 484fe4ba0b
18 changed files with 775 additions and 188 deletions
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13
_On_Ice/algo_config_backup.json Normal file
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@@ -0,0 +1,13 @@
{
"Config_Updated_Timestamp": 1777098091913,
"Allow_Ordering_Aster": false,
"Allow_Ordering_Extend": false,
"Loop_Sleep_Sec": 5.00,
"Max_Target_Notional": 0.00,
"Min_Time_To_Funding_Minutes": 10,
"Price_Worsener_Aster": 0.0,
"Price_Worsener_Extend": 0.0,
"Target_Open_Cash_Position": 10,
"Print_Summary_Each_Loop" : true,
"Flip_Side_For_Testing": false
}

194
algo.ipynb
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@@ -2,7 +2,7 @@
"cells": [ "cells": [
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 7, "execution_count": 76,
"id": "d1eed397", "id": "d1eed397",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
@@ -18,7 +18,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 8, "execution_count": 77,
"id": "c6151613", "id": "c6151613",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
@@ -28,7 +28,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 31, "execution_count": null,
"id": "d83c61e5", "id": "d83c61e5",
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
@@ -38,87 +38,50 @@
"1" "1"
] ]
}, },
"execution_count": 31, "execution_count": 131,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
], ],
"source": [ "source": [
"config_update = {\n", "config_update = {\n",
" 'Min_Time_To_Funding_Minutes': 60,\n", " 'Min_Time_To_Funding_Minutes': 7,\n",
" 'Print_Summary_Each_Loop': True,\n", " # 'Allow_Ordering_Aster': True,\n",
" 'Allow_Ordering_Aster': True,\n", " # 'Allow_Ordering_Extend': True,\n",
" 'Allow_Ordering_Extend': True,\n", " 'Loop_Sleep_Sec': 0.00,\n",
" 'Loop_Sleep_Sec': 0.0,\n", "# 'Flip_Side_For_Testing': False,\n",
" 'Flip_Side_For_Testing': False,\n", "# 'Price_Worsener_Extend': 0.0,\n",
" 'Price_Worsener_Extend': 0.0,\n", " 'Log_Summary_Each_Loop': False,\n",
" 'Print_Summary_Each_Loop': False,\n",
"}\n", "}\n",
"VAL_KEY.publish('fr_orchestrator_input', json.dumps(config_update))" "VAL_KEY.publish('fr_orchestrator_input', json.dumps(config_update))"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 93,
"id": "d2fdd7d2",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 11,
"id": "45fae761", "id": "45fae761",
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"data": { "data": {
"text/plain": [ "text/plain": [
"Algo_Config(Config_Updated_Timestamp=1777151524162, Allow_Ordering_Aster=True, Allow_Ordering_Extend=True, Loop_Sleep_Sec=1, Max_Target_Notional=0.0, Min_Time_To_Funding_Minutes=60, Price_Worsener_Aster=0.0, Price_Worsener_Extend=0.0, Target_Open_Cash_Position=10)" "5.0"
] ]
}, },
"execution_count": 11, "execution_count": 93,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
], ],
"source": [ "source": [
"json.loads(VAL_KEY.get('fr_orchestrator_output'), object_hook=lambda d: structs.Algo_Config(**d))" "json.loads(VAL_KEY.get('fr_orchestrator_output'), object_hook=lambda d: structs.Algo_Config(**d)).Loop_Sleep_Sec"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'Config_Updated_Timestamp': 1777098091913,\n",
" 'Allow_Ordering_Aster': False,\n",
" 'Allow_Ordering_Extend': False,\n",
" 'Loop_Sleep_Sec': 1,\n",
" 'Max_Target_Notional': 0.0,\n",
" 'Min_Time_To_Funding_Minutes': 60,\n",
" 'Price_Worsener_Aster': 0.0,\n",
" 'Price_Worsener_Extend': 0.0,\n",
" 'Target_Open_Cash_Position': 10,\n",
" 'Print_Summary_Each_Loop': False,\n",
" 'Flip_Side_For_Testing': False}"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"asdict(ALGO_CONFIG)"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": null,
"id": "d2e26271", "id": "98c500cc",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [] "source": []
@@ -126,9 +89,130 @@
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": null,
"id": "f2cf3325",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 31,
"id": "a0df43de", "id": "a0df43de",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [
"pos = json.loads(VAL_KEY.get('fr_aster_user_positions'))"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "ca526c8a",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[{'timestamp_arrival': 1777303258987,\n",
" 'timestamp_msg': 1777303258979,\n",
" 'timestamp_transaction': 1777303258950,\n",
" 'event_reason_type': 'ORDER',\n",
" 'symbol': 'ETHUSDT',\n",
" 'position_amount': 0.226,\n",
" 'entry_price': 2284.28,\n",
" 'accumulated_realized_pre_fees': 8.24392002,\n",
" 'unrealized_pnl': 0.0,\n",
" 'margin_type': 'cross',\n",
" 'isolated_wallet': 0.0,\n",
" 'position_side': 'BOTH'}]"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pos"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "f788b6df",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Timestamp('2026-04-27 15:20:58.987000')"
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import pandas as pd\n",
"pd.to_datetime(1777303258987, unit='ms')"
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "855f980b",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Timestamp('2026-04-27 15:20:58.979000')"
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import pandas as pd\n",
"pd.to_datetime(1777303258979, unit='ms')"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Timestamp('2026-04-27 15:20:58.950000')"
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import pandas as pd\n",
"pd.to_datetime(1777303258950, unit='ms')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [] "source": []
}, },
{ {
@@ -155,7 +239,7 @@
"name": "python", "name": "python",
"nbconvert_exporter": "python", "nbconvert_exporter": "python",
"pygments_lexer": "ipython3", "pygments_lexer": "ipython3",
"version": "3.13.12" "version": "3.13.13"
} }
}, },
"nbformat": 4, "nbformat": 4,

2
algo/Dockerfile
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@@ -15,5 +15,5 @@ RUN pip install --no-cache-dir -r requirements.txt
COPY . . COPY . .
# Finally, run gunicorn. # Finally, run gunicorn.
CMD [ "python", "-u" ,"main.py"] CMD [ "python", "main.py"]
# CMD [ "gunicorn", "--workers=5", "--threads=1", "-b 0.0.0.0:8000", "app:server"] # CMD [ "gunicorn", "--workers=5", "--threads=1", "-b 0.0.0.0:8000", "app:server"]

11
algo_config.json
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@@ -1,13 +1,14 @@
{ {
"Config_Updated_Timestamp": 1777098091913, "Config_Updated_Timestamp": 1777312620005,
"Allow_Ordering_Aster": true, "Allow_Ordering_Aster": true,
"Allow_Ordering_Extend": true, "Allow_Ordering_Extend": true,
"Loop_Sleep_Sec": 0.00, "Loop_Sleep_Sec": 0.0,
"Max_Target_Notional": 0.00, "Max_Target_Notional": 0.0,
"Min_Time_To_Funding_Minutes": 10, "Min_Time_To_Funding_Minutes": 7,
"Price_Worsener_Aster": 0.0, "Price_Worsener_Aster": 0.0,
"Price_Worsener_Extend": 0.0, "Price_Worsener_Extend": 0.0,
"Target_Open_Cash_Position": 10, "Target_Open_Cash_Position": 10,
"Print_Summary_Each_Loop" : false, "Log_Summary_Each_Loop": false,
"Print_Summary_Each_Loop": false,
"Flip_Side_For_Testing": false "Flip_Side_For_Testing": false
} }

13
algo_orchestrator.py
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@@ -42,14 +42,19 @@ async def orchestrator() -> None:
timestamp = round(datetime.now().timestamp()*1000) timestamp = round(datetime.now().timestamp()*1000)
data = json.loads(message['data']) data = json.loads(message['data'])
# channel = message['channel'] # channel = message['channel']
with open('/algo_local_drive/algo_config.json', 'r', encoding='utf-8') as f:
# ALGO_CONFIG = json.load(f, object_hook=lambda d: Algo_Config(**d))
ALGO_CONFIG = json.load(f)
ALGO_CONFIG['Config_Updated_Timestamp'] = timestamp
for k, v in data.items(): for k, v in data.items():
if ALGO_CONFIG.get(k, None) is not None: if ALGO_CONFIG.get(k, None) is not None:
ALGO_CONFIG[k] = v ALGO_CONFIG[k] = v
ALGO_CONFIG['Config_Updated_Timestamp'] = timestamp
VAL_KEY.set(VK_OUT, json.dumps(ALGO_CONFIG)) VAL_KEY.set(VK_OUT, json.dumps(ALGO_CONFIG))
with open('algo_config.json', 'w', encoding='utf-8') as f: with open('/algo_local_drive/algo_config.json', 'w', encoding='utf-8') as f:
# print('SAVING FILE')
json.dump(ALGO_CONFIG, f, indent=4) json.dump(ALGO_CONFIG, f, indent=4)
print(f"Algo Config Updated @ {timestamp}; {data}") print(f"Algo Config Updated @ {timestamp}; {data}")
@@ -70,7 +75,7 @@ async def main() -> None:
VAL_KEY = valkey.Valkey(host='localhost', port=6379, db=0, decode_responses=True) VAL_KEY = valkey.Valkey(host='localhost', port=6379, db=0, decode_responses=True)
# engine = create_async_engine('mysql+asyncmy://root:pwd@localhost/fund_rate') # engine = create_async_engine('mysql+asyncmy://root:pwd@localhost/fund_rate')
with open('algo_config.json', 'r', encoding='utf-8') as f: with open('/algo_local_drive/algo_config.json', 'r', encoding='utf-8') as f:
# ALGO_CONFIG = json.load(f, object_hook=lambda d: Algo_Config(**d)) # ALGO_CONFIG = json.load(f, object_hook=lambda d: Algo_Config(**d))
ALGO_CONFIG = json.load(f) ALGO_CONFIG = json.load(f)
ALGO_CONFIG['Config_Updated_Timestamp'] = round(datetime.now().timestamp()*1000) ALGO_CONFIG['Config_Updated_Timestamp'] = round(datetime.now().timestamp()*1000)

2
algo_orchestrator/Dockerfile
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@@ -15,5 +15,5 @@ RUN pip install --no-cache-dir -r requirements.txt
COPY . . COPY . .
# Finally, run gunicorn. # Finally, run gunicorn.
CMD [ "python", "-u" ,"algo_orchestrator.py"] CMD [ "python", "algo_orchestrator.py"]
# CMD [ "gunicorn", "--workers=5", "--threads=1", "-b 0.0.0.0:8000", "app:server"] # CMD [ "gunicorn", "--workers=5", "--threads=1", "-b 0.0.0.0:8000", "app:server"]

15
docker-compose-algo.yml Normal file
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@@ -0,0 +1,15 @@
# tail -f Fund_Rate_Algo.log
# docker compose -f docker-compose-algo.yml up --build
services:
algo:
container_name: algo
restart: "no"
build:
context: ./
dockerfile: ./algo/Dockerfile
volumes:
- /home/ubuntu/data:/home/ubuntu/data:rw # Read-write access to data
- /home/ubuntu/logs:/home/ubuntu/logs:rw # Read-write access to data
- ./:/algo_local_drive:rw # Read-write access to data
network_mode: "host"

48
docker-compose.yml
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@@ -1,23 +1,24 @@
# tail -f Fund_Rate_Algo.log Fund_Rate_Aster_User.log Fund_Rate_Aster.log Fund_Rate_Extended_FR.log Fund_Rate_Extended_OB.log Fund_Rate_Extended_User.log # tail -f Fund_Rate_Algo.log Fund_Rate_Aster_User.log Fund_Rate_Aster.log Fund_Rate_Extended_FR.log Fund_Rate_Extended_OB.log Fund_Rate_Extended_Trades.log Fund_Rate_Extended_User.log
services: services:
algo: # algo:
container_name: algo # container_name: algo
restart: "no" # restart: "no"
build: # build:
context: ./ # context: ./
dockerfile: ./algo/Dockerfile # dockerfile: ./algo/Dockerfile
depends_on: # depends_on:
- algo_orchestrator # - algo_orchestrator
- ws_aster # - ws_aster
- ws_aster_user # - ws_aster_user
- ws_extended_fund_rate # - ws_extended_fund_rate
- ws_extended_orderbook # - ws_extended_orderbook
- ws_extended_user # - ws_extended_trades
volumes: # - ws_extended_user
- /home/ubuntu/data:/home/ubuntu/data:rw # Read-write access to data # volumes:
- /home/ubuntu/logs:/home/ubuntu/logs:rw # Read-write access to data # - /home/ubuntu/data:/home/ubuntu/data:rw # Read-write access to data
network_mode: "host" # - /home/ubuntu/logs:/home/ubuntu/logs:rw # Read-write access to data
# network_mode: "host"
algo_orchestrator: algo_orchestrator:
container_name: algo_orchestrator container_name: algo_orchestrator
restart: "unless-stopped" restart: "unless-stopped"
@@ -27,6 +28,7 @@ services:
volumes: volumes:
- /home/ubuntu/data:/home/ubuntu/data:rw # Read-write access to data - /home/ubuntu/data:/home/ubuntu/data:rw # Read-write access to data
- /home/ubuntu/logs:/home/ubuntu/logs:rw # Read-write access to data - /home/ubuntu/logs:/home/ubuntu/logs:rw # Read-write access to data
- ./:/algo_local_drive:rw # Read-write access to data
network_mode: "host" network_mode: "host"
ws_aster: ws_aster:
container_name: ws_aster container_name: ws_aster
@@ -68,6 +70,16 @@ services:
- /home/ubuntu/data:/home/ubuntu/data:rw # Read-write access to dataw - /home/ubuntu/data:/home/ubuntu/data:rw # Read-write access to dataw
- /home/ubuntu/logs:/home/ubuntu/logs:rw # Read-write access to data - /home/ubuntu/logs:/home/ubuntu/logs:rw # Read-write access to data
network_mode: "host" network_mode: "host"
ws_extended_trades:
container_name: ws_extended_trades
restart: "unless-stopped"
build:
context: ./
dockerfile: ./ws_extended_trades/Dockerfile
volumes:
- /home/ubuntu/data:/home/ubuntu/data:rw # Read-write access to dataw
- /home/ubuntu/logs:/home/ubuntu/logs:rw # Read-write access to data
network_mode: "host"
ws_extended_user: ws_extended_user:
container_name: ws_extended_user container_name: ws_extended_user
restart: "unless-stopped" restart: "unless-stopped"

0
engine_health.py Normal file
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76
main.py
View File

@@ -38,6 +38,7 @@ LOG_FILEPATH: str = os.getenv("LOGS_PATH") + '/Fund_Rate_Algo.log'
### Algo Config ### ### Algo Config ###
ALGO_CONFIG: structs.Algo_Config = None ALGO_CONFIG: structs.Algo_Config = None
MIN_TIME_TO_FUNDING: int
### CONSTANTS ### ### CONSTANTS ###
ASTER = structs.Perpetual_Exchange( ASTER = structs.Perpetual_Exchange(
@@ -64,6 +65,12 @@ EXTEND_AVAIL_COLLATERAL = 0
ASTER_NOTIONAL_POSITION = 0 ASTER_NOTIONAL_POSITION = 0
EXTEND_NOTIONAL_POSITION = 0 EXTEND_NOTIONAL_POSITION = 0
ASTER_NOTIONAL_OBJ: dict | None = None
EXTEND_NOTIONAL_OBJ: dict | None = None
ASTER_UNREALIZED_PNL = 0
EXTEND_UNREALIZED_PNL = 0
ASTER_OPEN_ORDERS = [] ASTER_OPEN_ORDERS = []
EXTEND_OPEN_ORDERS = [] EXTEND_OPEN_ORDERS = []
@@ -111,9 +118,13 @@ async def get_aster_collateral():
ASTER_AVAIL_COLLATERAL = float([d for d in r if d.get('asset')==ASTER.rh_asset][0].get('availableBalance')) ASTER_AVAIL_COLLATERAL = float([d for d in r if d.get('asset')==ASTER.rh_asset][0].get('availableBalance'))
async def get_aster_notional_position(resp: dict | None = None): async def get_aster_notional_position(resp: dict | None = None):
global ASTER_NOTIONAL_OBJ
global ASTER_NOTIONAL_POSITION global ASTER_NOTIONAL_POSITION
global ASTER_UNREALIZED_PNL
global ASTER_MULT global ASTER_MULT
previous_notional_obj = ASTER_NOTIONAL_OBJ
if not resp: if not resp:
fut_acct_positionRisk = { fut_acct_positionRisk = {
"url": "/fapi/v3/positionRisk", "url": "/fapi/v3/positionRisk",
@@ -123,29 +134,38 @@ async def get_aster_notional_position(resp: dict | None = None):
} }
} }
resp = await aster_auth.post_authenticated_url(fut_acct_positionRisk) resp = await aster_auth.post_authenticated_url(fut_acct_positionRisk)
d = [x for x in resp if x.get('symbol', None) == ASTER.symbol][0]
d['timestamp_arrival'] = round(datetime.now().timestamp()*1000)
else:
d = [x for x in resp if x.get('symbol', None) == ASTER.symbol][0]
if previous_notional_obj is not None:
if previous_notional_obj['timestamp_arrival'] > d['timestamp_arrival']:
# logging.info(f'ASTER NOTIONAL: prev timestamp ({pd.to_datetime(previous_notional_obj['timestamp_arrival'], unit='ms')}) > new timestamp ({pd.to_datetime(d['timestamp_arrival'], unit='ms')}); skipping')
return
d = [x for x in resp if x.get('symbol', None) == ASTER.symbol][0] ASTER_NOTIONAL_OBJ = d
if len(d) < 1: if len(d) < 1:
logging.info(f'BAD NOTIONAL - ASTER CHANGE: Empty d: {d}; resp: {resp}') logging.info(f'BAD NOTIONAL - ASTER CHANGE: Empty d: {d}; resp: {resp}')
await kill_algo() await kill_algo()
aster_unrealized_pnl = float(d['unrealized_pnl']) if d.get('unrealized_pnl') is not None else float(d['unRealizedProfit']) ASTER_UNREALIZED_PNL = float(d['unrealized_pnl']) if d.get('unrealized_pnl') is not None else float(d['unRealizedProfit'])
if d.get('notional') is not None: if d.get('notional') is not None:
notional = float(d['notional']) ASTER_NOTIONAL_POSITION = float(d['notional']) - ASTER_UNREALIZED_PNL
else: else:
notional = float(d['position_amount'])*float(d['entry_price']) ASTER_NOTIONAL_POSITION = float(d['position_amount'])*float(d['entry_price'])
previous_notional_position = ASTER_NOTIONAL_POSITION previous_notional_position = ASTER_NOTIONAL_POSITION
ASTER_NOTIONAL_POSITION = notional - aster_unrealized_pnl # if not resp: # this can never evaluate
if not resp: # ASTER_MULT = float(d['leverage'])
ASTER_MULT = float(d['leverage']) # if abs(ASTER_NOTIONAL_POSITION) > ALGO_CONFIG.Max_Target_Notional*1.01:
if abs(ASTER_NOTIONAL_POSITION) > ALGO_CONFIG.Max_Target_Notional*1.01: if abs(ASTER_NOTIONAL_POSITION) > ALGO_CONFIG.Max_Target_Notional*2.01:
logging.info(f'BAD NOTIONAL - ASTER CHANGE: {ASTER_NOTIONAL_POSITION}; UR PNL: {aster_unrealized_pnl}; MULT: {ASTER_MULT}; d: {d}; resp: {resp}') logging.info(f'BAD NOTIONAL - ASTER CHANGE: {previous_notional_position} -> {ASTER_NOTIONAL_POSITION}; UR PNL: {ASTER_UNREALIZED_PNL}; MULT: {ASTER_MULT}; d: {d}; resp: {resp}')
await kill_algo() await kill_algo()
if ASTER_NOTIONAL_POSITION != previous_notional_position: # if ASTER_NOTIONAL_POSITION != previous_notional_position:
logging.info(f'ASTER NOTIONAL CHANGE: {previous_notional_position} -> {ASTER_NOTIONAL_POSITION:.2f}; UR PNL: {aster_unrealized_pnl:.2f}; MULT: {ASTER_MULT:.0f}; resp: {bool(resp)}') logging.info(f'ASTER NOTIONAL CHANGE: {previous_notional_position} -> {ASTER_NOTIONAL_POSITION:.2f}; UR PNL: {ASTER_UNREALIZED_PNL:.2f}; MULT: {ASTER_MULT:.0f}; resp: {bool(resp)}')
async def get_extend_collateral(): async def get_extend_collateral():
global EXTEND_AVAIL_COLLATERAL global EXTEND_AVAIL_COLLATERAL
@@ -155,6 +175,7 @@ async def get_extend_collateral():
async def get_extend_notional(resp: dict | None = None): async def get_extend_notional(resp: dict | None = None):
global EXTEND_NOTIONAL_POSITION global EXTEND_NOTIONAL_POSITION
global EXTEND_UNREALIZED_PNL
global EXTEND_MULT global EXTEND_MULT
if not resp: if not resp:
@@ -166,7 +187,7 @@ async def get_extend_notional(resp: dict | None = None):
logging.info('get_extend_notional - No Positions') logging.info('get_extend_notional - No Positions')
else: else:
pos_dict = pos_dict[0] pos_dict = pos_dict[0]
unrealized_pnl = pos_dict.get('unrealised_pnl', 0) EXTEND_UNREALIZED_PNL = pos_dict.get('unrealised_pnl', 0)
previous_notional_position = EXTEND_NOTIONAL_POSITION previous_notional_position = EXTEND_NOTIONAL_POSITION
position_side = pos_dict['side'] # LONG or SHORT position_side = pos_dict['side'] # LONG or SHORT
notional_pos_abs = abs(float(pos_dict['value'])) notional_pos_abs = abs(float(pos_dict['value']))
@@ -177,10 +198,13 @@ async def get_extend_notional(resp: dict | None = None):
else: else:
logging.info(f'EXTEND BAD SIDE ON POSITION UPDATE: {pos_dict}') logging.info(f'EXTEND BAD SIDE ON POSITION UPDATE: {pos_dict}')
EXTEND_NOTIONAL_POSITION = notional_pos_sided - float(unrealized_pnl) EXTEND_NOTIONAL_POSITION = notional_pos_sided - float(EXTEND_UNREALIZED_PNL)
EXTEND_MULT = pos_dict.get('leverage', EXTEND_MULT) EXTEND_MULT = pos_dict.get('leverage', EXTEND_MULT)
if abs(EXTEND_NOTIONAL_POSITION) > ALGO_CONFIG.Max_Target_Notional*2.01:
logging.info(f'BAD NOTIONAL - EXTEND CHANGE: {previous_notional_position} -> {EXTEND_NOTIONAL_POSITION}; UR PNL: {EXTEND_UNREALIZED_PNL}; MULT: {EXTEND_MULT}; d: {pos_dict}; resp: {resp}')
await kill_algo()
if EXTEND_NOTIONAL_POSITION != previous_notional_position: if EXTEND_NOTIONAL_POSITION != previous_notional_position:
logging.info(f'EXTEND NOTIONAL CHANGE: {previous_notional_position} -> {EXTEND_NOTIONAL_POSITION:.2f}; UR PNL: {unrealized_pnl:.2f}; MULT: {EXTEND_MULT:.0f}; resp: {bool(resp)}') logging.info(f'EXTEND NOTIONAL CHANGE: {previous_notional_position} -> {EXTEND_NOTIONAL_POSITION:.2f}; UR PNL: {EXTEND_UNREALIZED_PNL:.2f}; MULT: {EXTEND_MULT:.0f}; resp: {bool(resp)}')
### EXCHANGE INFO ### ### EXCHANGE INFO ###
async def get_aster_exch_info(): async def get_aster_exch_info():
@@ -226,9 +250,11 @@ async def kill_algo():
logging.info('ALGO KILL FLAG ACTIVATED; CANCELLING OPEN ORDERS AND SHUTTING DOWN') logging.info('ALGO KILL FLAG ACTIVATED; CANCELLING OPEN ORDERS AND SHUTTING DOWN')
raise ValueError('KILL FLAG ACTIVATED') raise ValueError('KILL FLAG ACTIVATED')
### ALGO LOOP ### ### ALGO LOOP ###
async def run_algo(): async def run_algo():
global ALGO_CONFIG global ALGO_CONFIG
global MIN_TIME_TO_FUNDING
global ASTER_OPEN_ORDERS global ASTER_OPEN_ORDERS
global EXTEND_OPEN_ORDERS global EXTEND_OPEN_ORDERS
@@ -288,13 +314,15 @@ async def run_algo():
now_ms = round(datetime.now().timestamp()*1000) now_ms = round(datetime.now().timestamp()*1000)
time_to_funding_ms = min([ASTER_FUND_RATE_TIME, EXTEND_FUND_RATE_TIME]) - now_ms time_to_funding_ms = min([ASTER_FUND_RATE_TIME, EXTEND_FUND_RATE_TIME]) - now_ms
if ( time_to_funding_ms > MIN_TIME_TO_FUNDING ) and (not ASTER_OPEN_ORDERS) and (not EXTEND_OPEN_ORDERS): if ( time_to_funding_ms > MIN_TIME_TO_FUNDING ) and (not ASTER_OPEN_ORDERS) and (not EXTEND_OPEN_ORDERS):
print(f'Outside action window (minutes) and no active order (sleeping for 5 sec): {pd.to_datetime(time_to_funding_ms, unit='ms').minute} > {pd.to_datetime(MIN_TIME_TO_FUNDING, unit='ms').minute}') logging.info(f'Outside action window (minutes) and no active order (sleeping for 5 sec): {pd.to_datetime(time_to_funding_ms, unit='ms').minute} > {pd.to_datetime(MIN_TIME_TO_FUNDING, unit='ms').minute}')
time.sleep(5) time.sleep(5)
continue continue
if len(ASTER_WS_POS_UPDATES) > 0: if len(ASTER_WS_POS_UPDATES) > 0:
# await get_aster_notional_position()
await get_aster_notional_position(resp=ASTER_WS_POS_UPDATES) await get_aster_notional_position(resp=ASTER_WS_POS_UPDATES)
###### *** returned 0 notional even though had a position, need to handle and safety check to not order above max notional. ###### *** returned 0 notional even though had a position, need to handle and safety check to not order above max notional.
##### NEED TO UPDATE SO IT TAKES THE LATEST MSG, ie drop the WS msg if its older than the exisiting one from the API.
if len(EXTEND_WS_POS_UPDATES) > 0: if len(EXTEND_WS_POS_UPDATES) > 0:
await get_extend_notional(resp=EXTEND_WS_POS_UPDATES) await get_extend_notional(resp=EXTEND_WS_POS_UPDATES)
@@ -304,7 +332,7 @@ async def run_algo():
if ASTER_WS_ORDER_UPDATES is not None: if ASTER_WS_ORDER_UPDATES is not None:
for idx, o in enumerate(ASTER_OPEN_ORDERS): for idx, o in enumerate(ASTER_OPEN_ORDERS):
order_id = o.get('order_id') if o.get('order_id') is not None else o['orderId'] order_id = o.get('order_id') if o.get('order_id') is not None else o['orderId']
order_orig_status = o['status'] ### Got a keyerror on this order_orig_status = o.get('status') if o.get('status') is not None else o['order_status']
order_update = [ou for ou in ASTER_WS_ORDER_UPDATES if ou.get('order_id', None) == order_id] order_update = [ou for ou in ASTER_WS_ORDER_UPDATES if ou.get('order_id', None) == order_id]
if len(order_update) > 0: if len(order_update) > 0:
@@ -411,8 +439,8 @@ async def run_algo():
EXTEND_TOB_PX = float(EXTENDED_TICKER_DICT['best_bid_px']) EXTEND_TOB_PX = float(EXTENDED_TICKER_DICT['best_bid_px'])
ASTER_TGT_TAIL = ASTER_TGT_NOTIONAL - ASTER_NOTIONAL_POSITION ASTER_TGT_TAIL = ASTER_TGT_NOTIONAL - ( float(ASTER_NOTIONAL_POSITION) + float(ASTER_UNREALIZED_PNL) )
EXTEND_TGT_TAIL = EXTEND_TGT_NOTIONAL - EXTEND_NOTIONAL_POSITION EXTEND_TGT_TAIL = EXTEND_TGT_NOTIONAL - ( float(EXTEND_NOTIONAL_POSITION) + float(EXTEND_UNREALIZED_PNL) )
ASTER_TGT_TAIL_BASE_QTY = Decimal(str(float(ASTER_TGT_TAIL) / float(ASTER_TOB_PX))).quantize(Decimal(str(0.001)), rounding=ROUND_DOWN) ASTER_TGT_TAIL_BASE_QTY = Decimal(str(float(ASTER_TGT_TAIL) / float(ASTER_TOB_PX))).quantize(Decimal(str(0.001)), rounding=ROUND_DOWN)
EXTEND_TGT_TAIL_BASE_QTY = Decimal(str(float(EXTEND_TGT_TAIL) / float(EXTEND_TOB_PX))).quantize(Decimal(str(0.001)), rounding=ROUND_DOWN) EXTEND_TGT_TAIL_BASE_QTY = Decimal(str(float(EXTEND_TGT_TAIL) / float(EXTEND_TOB_PX))).quantize(Decimal(str(0.001)), rounding=ROUND_DOWN)
@@ -426,9 +454,10 @@ async def run_algo():
OUT: print | logging.info = logging.info if use_logging else print OUT: print | logging.info = logging.info if use_logging else print
OUT(f''' OUT(f'''
LOOP SLEEP (SEC): {ALGO_CONFIG.Loop_Sleep_Sec}
FLIP SIDES FOR TESTING?: {ALGO_CONFIG.Flip_Side_For_Testing} FLIP SIDES FOR TESTING?: {ALGO_CONFIG.Flip_Side_For_Testing}
{pd.to_datetime(ASTER_FUND_RATE_TIME, unit='ms')} ({(pd.to_datetime(ASTER_FUND_RATE_TIME, unit='ms')-datetime.now()):}) | {pd.to_datetime(EXTEND_FUND_RATE_TIME, unit='ms')} ({(pd.to_datetime(EXTEND_FUND_RATE_TIME, unit='ms')-datetime.now()):}) {pd.to_datetime(ASTER_FUND_RATE_TIME, unit='ms')} ({(pd.to_datetime(ASTER_FUND_RATE_TIME, unit='ms')-datetime.now()):}) | {pd.to_datetime(EXTEND_FUND_RATE_TIME, unit='ms')} ({(pd.to_datetime(EXTEND_FUND_RATE_TIME, unit='ms')-datetime.now()):})
ASTER: {ASTER_FUND_RATE:.6%} [{ASTER_FUND_RATE*10_000:.2f}bps] [{ASTER_FUND_RATE*1_000_000:.0f}pips] | EXTEND: {EXTEND_FUND_RATE:.6%} [{EXTEND_FUND_RATE*10_000:.2f}bps] [{EXTEND_FUND_RATE*1_000_000:.0f}pips] ASTER: {ASTER_FUND_RATE:.6%} [{ASTER_FUND_RATE*10_000:.2f}bps] [{ASTER_FUND_RATE*1_000_000:.0f}pips] | EXTEND: {EXTEND_FUND_RATE:.6%} [{EXTEND_FUND_RATE*10_000:.2f}bps] [{EXTEND_FUND_RATE*1_000_000:.0f}pips]
ASTER: {'LONG PAYS SHORT' if ASTER_FUND_RATE > 0 else 'SHORT PAYS LONG'} | EXTEND: {'LONG PAYS SHORT' if EXTEND_FUND_RATE > 0 else 'SHORT PAYS LONG'} ASTER: {'LONG PAYS SHORT' if ASTER_FUND_RATE > 0 else 'SHORT PAYS LONG'} | EXTEND: {'LONG PAYS SHORT' if EXTEND_FUND_RATE > 0 else 'SHORT PAYS LONG'}
ASTER: [ Available Collateral: {ASTER_AVAIL_COLLATERAL:.4f} ] | EXTEND: [ Available Collateral: {EXTEND_AVAIL_COLLATERAL:.4f} ] ASTER: [ Available Collateral: {ASTER_AVAIL_COLLATERAL:.4f} ] | EXTEND: [ Available Collateral: {EXTEND_AVAIL_COLLATERAL:.4f} ]
ASTER: [ Notional Position $ : {ASTER_NOTIONAL_POSITION:.4f} ] | EXTEND: [ Notional Position $ : {EXTEND_NOTIONAL_POSITION:.4f} ] ASTER: [ Notional Position $ : {ASTER_NOTIONAL_POSITION:.4f} ] | EXTEND: [ Notional Position $ : {EXTEND_NOTIONAL_POSITION:.4f} ]
@@ -440,7 +469,7 @@ async def run_algo():
TGT NOTIONAL: $ {ALGO_CONFIG.Max_Target_Notional if not Flags.NET_FUNDING_IS_ZERO else 0.00} TGT NOTIONAL: $ {ALGO_CONFIG.Max_Target_Notional if not Flags.NET_FUNDING_IS_ZERO else 0.00}
ASTER: {ASTER_NOTIONAL_POSITION:.4f} -> {ASTER_TGT_NOTIONAL:.2f} [ Remain: {ASTER_TGT_TAIL:.4f} ] | EXTEND: {EXTEND_NOTIONAL_POSITION:.4f} -> {EXTEND_TGT_NOTIONAL:.2f} [ Remain: {EXTEND_TGT_TAIL:.4f} ] ASTER: {ASTER_NOTIONAL_POSITION:.4f} -> {ASTER_TGT_NOTIONAL:.2f} [ Remain: {ASTER_TGT_TAIL:.4f} ] | EXTEND: {EXTEND_NOTIONAL_POSITION:.4f} -> {EXTEND_TGT_NOTIONAL:.2f} [ Remain: {EXTEND_TGT_TAIL:.4f} ]
ASTER: {ASTER_TGT_NOTIONAL:.4f} - {ASTER_NOTIONAL_POSITION:.4f} = Tail: {ASTER_TGT_TAIL:4f} | EXTEND: {EXTEND_TGT_NOTIONAL:.4f} - {EXTEND_NOTIONAL_POSITION:.4f} = Tail: {EXTEND_TGT_TAIL:4f} ASTER: {ASTER_TGT_NOTIONAL:.2f} - {ASTER_NOTIONAL_POSITION:.2f} + {ASTER_UNREALIZED_PNL:.2f} = {ASTER_TGT_TAIL:2f} | EXTEND: {EXTEND_TGT_NOTIONAL:.2f} - {EXTEND_NOTIONAL_POSITION:.2f} + {EXTEND_UNREALIZED_PNL:.2f} = {EXTEND_TGT_TAIL:2f}
ASTER: {ASTER_TGT_TAIL_BASE_QTY:.4f} > {MAX_MIN_ORDER_QTY:.4f} min [ Order: {ASTER_TGT_TAIL_ORDERABLE} ] | EXTEND: {EXTEND_TGT_TAIL_BASE_QTY:.4f} > {MAX_MIN_ORDER_QTY:.4f} min [ Order: {EXTEND_TGT_TAIL_ORDERABLE} ] ASTER: {ASTER_TGT_TAIL_BASE_QTY:.4f} > {MAX_MIN_ORDER_QTY:.4f} min [ Order: {ASTER_TGT_TAIL_ORDERABLE} ] | EXTEND: {EXTEND_TGT_TAIL_BASE_QTY:.4f} > {MAX_MIN_ORDER_QTY:.4f} min [ Order: {EXTEND_TGT_TAIL_ORDERABLE} ]
--- ASTER OPEN ORDERS --- --- ASTER OPEN ORDERS ---
@@ -449,8 +478,10 @@ async def run_algo():
--- EXTEND OPEN ORDERS --- --- EXTEND OPEN ORDERS ---
{EXTEND_OPEN_ORDERS} {EXTEND_OPEN_ORDERS}
''') ''')
if ALGO_CONFIG.Log_Summary_Each_Loop:
print_summary(use_logging=True)
if ALGO_CONFIG.Print_Summary_Each_Loop: if ALGO_CONFIG.Print_Summary_Each_Loop:
print_summary() print_summary(use_logging=False)
# print_summary() # print_summary()
### ROUTES ### ### ROUTES ###
@@ -510,6 +541,7 @@ async def run_algo():
order_resp = await aster_auth.post_authenticated_url(post_order) order_resp = await aster_auth.post_authenticated_url(post_order)
if order_resp.get('orderId', None) is not None: if order_resp.get('orderId', None) is not None:
order_resp['original_price'] = price order_resp['original_price'] = price
order_resp['order_status'] = order_resp['status']
ASTER_OPEN_ORDERS.append(order_resp) ASTER_OPEN_ORDERS.append(order_resp)
utils.send_tg_alert(f'FR_ALGO - ASTER Order. Start_$: {ASTER_NOTIONAL_POSITION:.2f}; Value: {float(ASTER_TGT_TAIL_BASE_QTY)*float(price):.2f}; Price: {float(price):.2f}') utils.send_tg_alert(f'FR_ALGO - ASTER Order. Start_$: {ASTER_NOTIONAL_POSITION:.2f}; Value: {float(ASTER_TGT_TAIL_BASE_QTY)*float(price):.2f}; Price: {float(price):.2f}')
logging.info(f'ASTER ORDER PLACED SUCCESS: {order_resp}') logging.info(f'ASTER ORDER PLACED SUCCESS: {order_resp}')
@@ -594,7 +626,7 @@ async def run_algo():
logging.info('EXTEND HAS NO TAIL BUT OPEN ORDERS - CANCELLING OPEN ORDERS') logging.info('EXTEND HAS NO TAIL BUT OPEN ORDERS - CANCELLING OPEN ORDERS')
await extend_cancel_all_orders() await extend_cancel_all_orders()
print(f'__________ End ___________ (Algo Engine ms: {(time.time() - loop_start)*1000})') # print(f'__________ End ___________ (Algo Engine ms: {(time.time() - loop_start)*1000}); Sleeping for sec: {ALGO_CONFIG.Loop_Sleep_Sec}')
time.sleep(ALGO_CONFIG.Loop_Sleep_Sec) time.sleep(ALGO_CONFIG.Loop_Sleep_Sec)

33
modules/aster_db.py
View File

@@ -139,9 +139,30 @@ async def create_fr_aster_user_account_pos(
else: else:
raise ValueError('Only MySQL engine is implemented') raise ValueError('Only MySQL engine is implemented')
### Mkt Trades Table ####
async def create_fr_aster_mkt_trades(
CON: AsyncContextManager,
engine: str = 'mysql', # mysql | duckdb
) -> None:
if CON is None:
logging.info("NO DB CONNECTION, SKIPPING Create Statements")
else:
if engine == 'mysql':
logging.info('Creating Table if Does Not Exist: fr_aster_mkt_trades')
await CON.execute(text("""
CREATE TABLE IF NOT EXISTS fr_aster_mkt_trades (
timestamp_arrival BIGINT,
timestamp_msg BIGINT,
timestamp_trade BIGINT,
symbol VARCHAR(20),
aggregate_trade_id VARCHAR(100),
price DOUBLE,
qty DOUBLE,
first_trade_id VARCHAR(100),
last_trade_id VARCHAR(100),
is_buyer_mkt_maker BOOL
);
"""))
await CON.commit()
else:
raise ValueError('Only MySQL engine is implemented')

29
modules/extended_db.py
View File

@@ -150,3 +150,32 @@ async def create_fr_extended_user_position(
else: else:
raise ValueError('Only MySQL engine is implemented') raise ValueError('Only MySQL engine is implemented')
### Market Trades Table ####
async def create_fr_extended_mkt_trades(
CON: AsyncContextManager,
engine: str = 'mysql', # mysql | duckdb
) -> None:
if CON is None:
logging.info("NO DB CONNECTION, SKIPPING Create Statements")
else:
if engine == 'mysql':
logging.info('Creating Table if Does Not Exist: fr_extended_mkt_trades')
await CON.execute(text("""
CREATE TABLE IF NOT EXISTS fr_extended_mkt_trades (
sequence_id INT,
timestamp_arrival BIGINT,
timestamp_msg BIGINT,
timestamp_trade BIGINT,
symbol VARCHAR(20),
side_taker VARCHAR(20),
trade_type VARCHAR(20),
price DOUBLE,
qty DOUBLE,
trade_id VARCHAR(100),
is_buyer_mkt_maker BOOL
);
"""))
await CON.commit()
else:
raise ValueError('Only MySQL engine is implemented')

1
modules/structs.py
View File

@@ -17,6 +17,7 @@ class Algo_Config:
Price_Worsener_Extend: float Price_Worsener_Extend: float
Target_Open_Cash_Position: int Target_Open_Cash_Position: int
Log_Summary_Each_Loop: bool = False
Print_Summary_Each_Loop: bool = False Print_Summary_Each_Loop: bool = False
Flip_Side_For_Testing: bool = False Flip_Side_For_Testing: bool = False

272
order_engine.ipynb Normal file
View File

@@ -0,0 +1,272 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": 32,
"id": "68966247",
"metadata": {},
"outputs": [],
"source": [
"import requests\n",
"import pandas as pd\n",
"import numpy as np\n",
"import json\n",
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "02cd5305",
"metadata": {},
"outputs": [],
"source": [
"### Extended Trades History ###\n",
"candleType = 'trades'\n",
"market = 'ETH-USD'\n",
"params = {\n",
" 'interval': \"1m\",\n",
" 'limit': 100,\n",
"}\n",
"r = requests.get(f'https://api.starknet.extended.exchange/api/v1/info/candles/{market}/{candleType}', params=params)"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "5603b04d",
"metadata": {},
"outputs": [],
"source": [
"### Aster Trades History ###\n",
"params = {\n",
" 'symbol': \"ETHUSDT\",\n",
" 'limit': 1000,\n",
"}\n",
"r = requests.get('https://fapi.asterdex.com/fapi/v3/trades', params=params)"
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "a3ad1819",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>id</th>\n",
" <th>price</th>\n",
" <th>qty</th>\n",
" <th>quoteQty</th>\n",
" <th>time</th>\n",
" <th>isBuyerMaker</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>74506547</td>\n",
" <td>2311.02</td>\n",
" <td>0.044</td>\n",
" <td>101.68</td>\n",
" <td>2026-04-27 14:22:45.650</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>74506548</td>\n",
" <td>2311.00</td>\n",
" <td>0.004</td>\n",
" <td>9.24</td>\n",
" <td>2026-04-27 14:22:45.650</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>74506549</td>\n",
" <td>2310.91</td>\n",
" <td>0.003</td>\n",
" <td>6.93</td>\n",
" <td>2026-04-27 14:22:45.650</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>74506550</td>\n",
" <td>2310.90</td>\n",
" <td>0.004</td>\n",
" <td>9.24</td>\n",
" <td>2026-04-27 14:22:45.650</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>74506551</td>\n",
" <td>2310.80</td>\n",
" <td>0.004</td>\n",
" <td>9.24</td>\n",
" <td>2026-04-27 14:22:45.700</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>995</th>\n",
" <td>74507542</td>\n",
" <td>2312.10</td>\n",
" <td>0.004</td>\n",
" <td>9.24</td>\n",
" <td>2026-04-27 14:34:12.500</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>996</th>\n",
" <td>74507543</td>\n",
" <td>2312.18</td>\n",
" <td>2.442</td>\n",
" <td>5646.34</td>\n",
" <td>2026-04-27 14:34:13.443</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>997</th>\n",
" <td>74507544</td>\n",
" <td>2312.24</td>\n",
" <td>10.099</td>\n",
" <td>23351.31</td>\n",
" <td>2026-04-27 14:34:13.600</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>998</th>\n",
" <td>74507545</td>\n",
" <td>2312.13</td>\n",
" <td>3.120</td>\n",
" <td>7213.84</td>\n",
" <td>2026-04-27 14:34:14.568</td>\n",
" <td>True</td>\n",
" </tr>\n",
" <tr>\n",
" <th>999</th>\n",
" <td>74507546</td>\n",
" <td>2312.19</td>\n",
" <td>6.228</td>\n",
" <td>14400.31</td>\n",
" <td>2026-04-27 14:34:15.988</td>\n",
" <td>True</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>1000 rows × 6 columns</p>\n",
"</div>"
],
"text/plain": [
" id price qty quoteQty time isBuyerMaker\n",
"0 74506547 2311.02 0.044 101.68 2026-04-27 14:22:45.650 True\n",
"1 74506548 2311.00 0.004 9.24 2026-04-27 14:22:45.650 True\n",
"2 74506549 2310.91 0.003 6.93 2026-04-27 14:22:45.650 True\n",
"3 74506550 2310.90 0.004 9.24 2026-04-27 14:22:45.650 True\n",
"4 74506551 2310.80 0.004 9.24 2026-04-27 14:22:45.700 True\n",
".. ... ... ... ... ... ...\n",
"995 74507542 2312.10 0.004 9.24 2026-04-27 14:34:12.500 True\n",
"996 74507543 2312.18 2.442 5646.34 2026-04-27 14:34:13.443 True\n",
"997 74507544 2312.24 10.099 23351.31 2026-04-27 14:34:13.600 True\n",
"998 74507545 2312.13 3.120 7213.84 2026-04-27 14:34:14.568 True\n",
"999 74507546 2312.19 6.228 14400.31 2026-04-27 14:34:15.988 True\n",
"\n",
"[1000 rows x 6 columns]"
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"l = json.loads(r.text)\n",
"df = pd.DataFrame(l)\n",
"df['time'] = pd.to_datetime(df['time'], unit='ms')\n",
"df"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "3c908942",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "60f4608a",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "76624896",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "5ade3c15",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "py_313",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.13.13"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

100
ws_aster.py
View File

@@ -15,7 +15,8 @@ from sqlalchemy.ext.asyncio import create_async_engine
import valkey import valkey
import os import os
from dotenv import load_dotenv from dotenv import load_dotenv
import modules.db as db
import modules.aster_db as aster_db
### Allow only ipv4 ### ### Allow only ipv4 ###
def allowed_gai_family(): def allowed_gai_family():
@@ -23,10 +24,11 @@ def allowed_gai_family():
urllib3_cn.allowed_gai_family = allowed_gai_family urllib3_cn.allowed_gai_family = allowed_gai_family
### Database ### ### Database ###
USE_DB: bool = False USE_DB: bool = True
USE_VK: bool = True USE_VK: bool = True
VK_FUND_RATE = 'fund_rate_aster' VK_FUND_RATE = 'fund_rate_aster'
VK_TICKER = 'fut_ticker_aster' VK_TICKER = 'fut_ticker_aster'
VK_LAST_TRADE = 'fut_last_trade_aster'
CON: AsyncContextManager | None = None CON: AsyncContextManager | None = None
VAL_KEY = None VAL_KEY = None
@@ -38,80 +40,10 @@ LOG_FILEPATH: str = os.getenv("LOGS_PATH") + '/Fund_Rate_Aster.log'
SYMBOL: str = 'ETHUSDT' SYMBOL: str = 'ETHUSDT'
STREAM_MARKPRICE: str = f'{SYMBOL.lower()}@markPrice@1s' STREAM_MARKPRICE: str = f'{SYMBOL.lower()}@markPrice@1s'
STREAM_BOOKTICKER: str = f'{SYMBOL.lower()}@bookTicker' STREAM_BOOKTICKER: str = f'{SYMBOL.lower()}@bookTicker'
STREAM_TRADES: str = f'{SYMBOL.lower()}@aggTrade'
### Globals ### ### Globals ###
WSS_URL = f"wss://fstream.asterdex.com/stream?streams={STREAM_MARKPRICE}/{STREAM_BOOKTICKER}" WSS_URL = f"wss://fstream.asterdex.com/stream?streams={STREAM_MARKPRICE}/{STREAM_BOOKTICKER}/{STREAM_TRADES}"
# WSS_URL = f"wss://fstream.asterdex.com/stream?streams={STREAM_MARKPRICE}"
# HIST_TRADES = np.empty((0, 3))
# HIST_TRADES_LOOKBACK_SEC = 6
# ### Database Funcs ###
# async def create_rtds_btcusd_table(
# CON: AsyncContextManager,
# engine: str = 'mysql', # mysql | duckdb
# ) -> None:
# if CON is None:
# logging.info("NO DB CONNECTION, SKIPPING Create Statements")
# else:
# if engine == 'mysql':
# logging.info('Creating Table if Does Not Exist: binance_btcusd_trades')
# await CON.execute(text("""
# CREATE TABLE IF NOT EXISTS binance_btcusd_trades (
# timestamp_arrival BIGINT,
# timestamp_msg BIGINT,
# timestamp_value BIGINT,
# value DOUBLE,
# qty DOUBLE
# );
# """))
# await CON.commit()
# else:
# raise ValueError('Only MySQL engine is implemented')
# async def insert_rtds_btcusd_table(
# timestamp_arrival: int,
# timestamp_msg: int,
# timestamp_value: int,
# value: float,
# qty: float,
# CON: AsyncContextManager,
# engine: str = 'mysql', # mysql | duckdb
# ) -> None:
# params={
# 'timestamp_arrival': timestamp_arrival,
# 'timestamp_msg': timestamp_msg,
# 'timestamp_value': timestamp_value,
# 'value': value,
# 'qty': qty,
# }
# if CON is None:
# logging.info("NO DB CONNECTION, SKIPPING Insert Statements")
# else:
# if engine == 'mysql':
# await CON.execute(text("""
# INSERT INTO binance_btcusd_trades
# (
# timestamp_arrival,
# timestamp_msg,
# timestamp_value,
# value,
# qty
# )
# VALUES
# (
# :timestamp_arrival,
# :timestamp_msg,
# :timestamp_value,
# :value,
# :qty
# )
# """),
# parameters=params
# )
# await CON.commit()
# else:
# raise ValueError('Only MySQL engine is implemented')
### Websocket ### ### Websocket ###
async def ws_stream(): async def ws_stream():
@@ -156,6 +88,24 @@ async def ws_stream():
}) })
VAL_KEY.set(VK_TICKER, VAL_KEY_OBJ) VAL_KEY.set(VK_TICKER, VAL_KEY_OBJ)
continue continue
case c if c == STREAM_TRADES:
# print(f'MKT_TRADE: {data}')
trade_obj = {
'timestamp_arrival': ts_arrival,
'timestamp_msg': data['data']['E'],
'timestamp_trade': data['data']['T'],
'symbol': data['data']['s'],
'aggregate_trade_id': data['data']['a'],
'price': float(data['data']['p']),
'qty': float(data['data']['q']),
'first_trade_id': data['data']['f'],
'last_trade_id': data['data']['l'],
'is_buyer_mkt_maker': bool(data['data']['m']),
}
# VAL_KEY.set(VK_LAST_TRADE, json.dumps(trade_obj))
if USE_DB:
await db.insert_df_to_mysql(table_name='fr_aster_mkt_trades', params=trade_obj, CON=CON)
continue
case _: case _:
logging.warning(f'UNMATCHED OTHER MSG: {data}') logging.warning(f'UNMATCHED OTHER MSG: {data}')
else: else:
@@ -188,7 +138,7 @@ async def main():
if USE_DB: if USE_DB:
engine = create_async_engine('mysql+asyncmy://root:pwd@localhost/fund_rate') engine = create_async_engine('mysql+asyncmy://root:pwd@localhost/fund_rate')
async with engine.connect() as CON: async with engine.connect() as CON:
# await create_rtds_btcusd_table(CON=CON) await aster_db.create_fr_aster_mkt_trades(CON=CON)
await ws_stream() await ws_stream()
else: else:
CON = None CON = None

134
ws_extended_trades.py Normal file
View File

@@ -0,0 +1,134 @@
import asyncio
import json
import logging
import os
import socket
import traceback
from datetime import datetime
from typing import AsyncContextManager
import numpy as np
import pandas as pd
import requests.packages.urllib3.util.connection as urllib3_cn # type: ignore
import valkey
import websockets
from dotenv import load_dotenv
from sqlalchemy.ext.asyncio import create_async_engine
import modules.db as db
import modules.extended_db as extended_db
### Allow only ipv4 ###
def allowed_gai_family():
return socket.AF_INET
urllib3_cn.allowed_gai_family = allowed_gai_family
### Database ###
USE_DB: bool = True
USE_VK: bool = True
VK_LAST_TRADE = 'fut_last_trade_extended'
CON: AsyncContextManager | None = None
VAL_KEY = None
### Logging ###
load_dotenv()
LOG_FILEPATH: str = os.getenv("LOGS_PATH") + '/Fund_Rate_Extended_Trades.log'
### CONSTANTS ###
WS_SYMBOL: str = 'ETH-USD'
### Globals ###
WSS_URL = f"wss://api.starknet.extended.exchange/stream.extended.exchange/v1/publicTrades/{WS_SYMBOL}"
### Websocket ###
async def ws_stream():
async for websocket in websockets.connect(WSS_URL):
logging.info(f"Connected to {WSS_URL}")
try:
async for message in websocket:
ts_arrival = round(datetime.now().timestamp()*1000)
if isinstance(message, str):
try:
data = json.loads(message)
if data.get('data', None) is not None:
if data['seq'] == 1: # Skip first msg that has historical trades
continue
list_for_df = []
for t in data['data']:
trade_obj = {
'sequence_id': data['seq'],
'timestamp_arrival': ts_arrival,
'timestamp_msg': data['ts'],
'timestamp_trade': t['T'],
'symbol': t['m'],
'side_taker': t['S'],
'trade_type': t['tT'],
'price': float(t['p']),
'qty': float(t['q']),
'trade_id': t['i'],
'is_buyer_mkt_maker': True if t['S']=='SELL' else False,
}
list_for_df.append(trade_obj)
# VAL_KEY.set(VK_LAST_TRADE, json.dumps(trade_obj))
if USE_DB:
await db.insert_df_to_mysql(table_name='fr_extended_mkt_trades', params=list_for_df, CON=CON)
pass
continue
else:
logging.info(f'Initial or unexpected data struct, skipping: {data}')
continue
except (json.JSONDecodeError, ValueError):
logging.warning(f'Message not in JSON format, skipping: {message}')
continue
else:
raise ValueError(f'Type: {type(data)} not expected: {message}')
except websockets.ConnectionClosed as e:
logging.error(f'Connection closed: {e}')
logging.error(traceback.format_exc())
continue
except Exception as e:
logging.error(f'Connection closed: {e}')
logging.error(traceback.format_exc())
async def main():
global VAL_KEY
global CON
if USE_VK:
VAL_KEY = valkey.Valkey(host='localhost', port=6379, db=0)
else:
VAL_KEY = None
logging.warning("VALKEY NOT BEING USED, NO DATA WILL BE PUBLISHED")
if USE_DB:
engine = create_async_engine('mysql+asyncmy://root:pwd@localhost/fund_rate')
async with engine.connect() as CON:
await extended_db.create_fr_extended_mkt_trades(CON=CON)
await ws_stream()
else:
CON = None
logging.warning("DATABASE NOT BEING USED, NO DATA WILL BE RECORDED")
await ws_stream()
if __name__ == '__main__':
START_TIME = round(datetime.now().timestamp()*1000)
logging.info(f'Log FilePath: {LOG_FILEPATH}')
logging.basicConfig(
force=True,
filename=LOG_FILEPATH,
level=logging.INFO,
format='%(asctime)s - %(levelname)s - %(message)s',
filemode='w'
)
logging.info(f"STARTED: {START_TIME}")
try:
asyncio.run(main())
except KeyboardInterrupt:
logging.info("Stream stopped")

19
ws_extended_trades/Dockerfile Normal file
View File

@@ -0,0 +1,19 @@
FROM python:3.13-slim
RUN apt-get update && \
apt-get install -y build-essential
RUN gcc --version
RUN rm -rf /var/lib/apt/lists/*
WORKDIR /app
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
COPY . .
# Finally, run gunicorn.
CMD [ "python", "ws_extended_trades.py"]
# CMD [ "gunicorn", "--workers=5", "--threads=1", "-b 0.0.0.0:8000", "app:server"]

1
ws_extended_user.py
View File

@@ -198,7 +198,6 @@ async def ws_stream():
VAL_KEY_OBJ = json.dumps(LOCAL_RECENT_POSITIONS) VAL_KEY_OBJ = json.dumps(LOCAL_RECENT_POSITIONS)
VAL_KEY.set(VK_POSITIONS, VAL_KEY_OBJ) VAL_KEY.set(VK_POSITIONS, VAL_KEY_OBJ)
await db.insert_df_to_mysql(table_name='fr_extended_user_position', params=list_for_df, CON=CON) await db.insert_df_to_mysql(table_name='fr_extended_user_position', params=list_for_df, CON=CON)
continue continue
case _: case _: