Merge branch 'refactor' of ssh://giugl.io.gitea:10022/peperunas/gkaching into refactor

bfxbot/bfxbot.py

@@ -8,6 +8,14 @@ from bfxbot.models import SymbolStatus, Ticker, EventHandler, Strategy
 
 class BfxBot:
     def __init__(self, api_key: str, api_secret: str, tick_duration: int = 1):
+        if api_key is None:
+            print("API_KEY is not set!")
+            raise ValueError
+
+        if api_secret is None:
+            print("API_SECRET is not set!")
+            raise ValueError
+
         self.bfx: BfxWrapper = BfxWrapper(api_key, api_secret)
         self.status: Dict[Symbol, SymbolStatus] = {}
         self.ticker: Ticker = Ticker(tick_duration)

main.py

@@ -485,70 +485,34 @@
 # if __name__ == "__main__":
 #     asyncio.run(Screen.wrapper(main))
 import asyncio
-import shutil
+import os
-from typing import List
 
-from asciimatics.screen import Screen, ManagedScreen
+import dotenv
-from asciimatics.widgets import Frame, Layout, Text
-from bfxapi import Position
 
 from bfxbot import BfxBot
-import dotenv
-import os
-import bfxapi
-
 from bfxbot.currency import Symbol
-from bfxbot.models import Strategy, SymbolStatus, PositionState, Event, EventKind
+from bfxbot.models import PositionState
-from bfxbot.utils import TAKER_FEE, net_pl_percentage
 from strategy import TrailingStopStrategy
 
 dotenv.load_dotenv()
-
-async def main():
 API_KEY = os.getenv("API_KEY")
 API_SECRET = os.getenv("API_SECRET")
 
-    if API_KEY is None:
+bot = BfxBot(api_key=API_KEY, api_secret=API_SECRET)
-        print("API_KEY is not set! Set the var in the .env file.")
-        return
-
-    if API_SECRET is None:
-        print("API_SECRET is not set! Set the var in the .env file.")
-        return
-
-    bot = BfxBot(api_key=API_KEY, api_secret=API_SECRET, tick_duration=20)
 strategy = TrailingStopStrategy()
 bot.set_strategy(Symbol.BTC, strategy)
 eh = bot.event_handler(Symbol.BTC)
 
+
+@eh.on_state(PositionState.PROFIT)
+def on_min_profit(ss, pw):
+    print("Minimum profit!")
+
+async def main():
     await bot.start()
 
     while True:
-        await bot_loop(bot)
-
-
-@ManagedScreen
-async def bot_loop(bot: BfxBot, screen: Screen = None):
-    prepare_tui(screen)
-    screen.play()
-
         await bot.update()
 
-def prepare_tui(screen: Screen):
-    w, h = shutil.get_terminal_size()
-
-    frame = Frame(screen, w, h, has_border=False)
-
-    info_layout = Layout([1])
-    graph_layout = Layout([1])
-    footer_layout = Layout([1])
-
-    frame.add_layout(info_layout)
-    frame.add_layout(graph_layout)
-    frame.add_layout(footer_layout)
-
-    info_layout.add_widget(Text(label="Test"))
-
-
 if __name__ == '__main__':
     asyncio.run(main())

requirements.txt

@@ -1,5 +1,2 @@
-asciimatics==1.12.0
+python-dotenv~=0.15.0
-asyncio==3.4.3
+sympy~=1.7
-playsound==1.2.2
-termcolor==1.1.0
-termplotlib==0.3.2

strategy.py

@@ -1,22 +1,60 @@
 from typing import List
 
-from bfxapi import Position
+import sympy.abc
+from sympy import Point, solve
 
 from bfxbot.models import Strategy, PositionState, SymbolStatus, Event, EventKind
 from bfxbot.utils import TAKER_FEE, net_pl_percentage
 
 
+class Position(object):
+    def __init__(self):
+        self.id = None
+        self.profit_loss_percentage = None
+
+    pass
+
+class SquaredTrailingStop:
+    def __init__(self, p_min: Point, p_max: Point):
+        a = sympy.abc.a
+        b = sympy.abc.b
+        c = sympy.abc.c
+
+        self.p_min = p_min
+        self.p_max = p_max
+
+        e1 = 2 * a * (p_max.x + b)
+        e2 = a * (p_min.x + b)**2 + c - p_min.y
+        e3 = a * (p_max.x + b)**2 + c - p_max.y
+
+        s = solve([e1, e2, e3])[0]
+
+        self.a, self.b, self.c = s[a], s[b], s[c]
+
+    def y(self, x):
+        def inter_y(x):
+            return self.a * (x + self.b)**2 + self.c
+
+        if x < self.p_min.x:
+            return self.p_min.y
+        elif x > self.p_max.x:
+            return self.p_max.y
+        else:
+            return inter_y(x)
+
+    def profit(self, x):
+        if x < self.p_min.x:
+            return 0
+        return x - self.y(x)
+
 class TrailingStopStrategy(Strategy):
     BREAK_EVEN_PERC = TAKER_FEE
-    MIN_PROFIT_PERC = TAKER_FEE * 2.5
+    MIN_PROFIT_PERC = BREAK_EVEN_PERC + 0.3
-    GOOD_PROFIT_PERC = MIN_PROFIT_PERC * 1.5
+    GOOD_PROFIT_PERC = MIN_PROFIT_PERC * 2.5
     MAX_LOSS_PERC = -3.75
-    OFFER_PERC = 0.01
+    OFFER_PERC = 0.005
 
-    TRAIL_STOP_PERCENTAGES = {
+    TRAILING_STOP = SquaredTrailingStop(Point(MIN_PROFIT_PERC, MIN_PROFIT_PERC/3*2), Point(GOOD_PROFIT_PERC, 0.1))
-        PositionState.MINIMUM_PROFIT: 0.27,
-        PositionState.PROFIT: 0.14
-    }
 
     def position_on_tick(self, position: Position, ss: SymbolStatus) -> (PositionState, List[Event]):
         events = []
@@ -51,3 +89,5 @@ class TrailingStopStrategy(Strategy):
             events.append(Event(EventKind.CLOSE_POSITION, position.id, ss.current_tick))
 
         return state, events
+
+