mirror of
https://github.com/Ichinga-Samuel/aiomql.git
synced 2026-08-02 06:47:45 +00:00
Ichinga Samuel
105 lines
3.4 KiB
Python
105 lines
3.4 KiB
Python
from datetime import datetime
|
|
|
|
import pytest
|
|
import pytz
|
|
import pandas as pd
|
|
from aiomql.lib.candle import Candle, Candles
|
|
from aiomql.core.meta_trader import MetaTrader
|
|
from aiomql.core.constants import TimeFrame
|
|
|
|
|
|
class TestCandle:
|
|
@classmethod
|
|
def setup_class(cls):
|
|
cls.bullish_candle = Candle(open=1.3421, high=1.3462, low=1.3405, close=1.3452, time=0, Index=0)
|
|
cls.bearish_candle = Candle(open=1.3452, high=1.3405, low=1.3462, close=1.3421, time=1, Index=1)
|
|
|
|
def test_repr(self):
|
|
repr_str = repr(self.bearish_candle)
|
|
assert repr_str.startswith("Candle(")
|
|
assert "open=" in repr_str
|
|
assert "high=" in repr_str
|
|
assert "low=" in repr_str
|
|
assert "close=" in repr_str
|
|
|
|
def test_set_attributes(self):
|
|
self.bearish_candle.set_attributes(ema=10)
|
|
assert self.bearish_candle.ema == 10
|
|
|
|
def test_compare(self):
|
|
assert self.bearish_candle > self.bullish_candle
|
|
assert self.bullish_candle != self.bearish_candle
|
|
assert self.bullish_candle < self.bearish_candle
|
|
|
|
def test_dict(self):
|
|
self.bearish_candle.set_attributes(ema=10)
|
|
result = self.bearish_candle.dict(exclude={"time"})
|
|
result2 = self.bearish_candle.dict(include={"close", "high"})
|
|
assert result["open"] == 1.3452
|
|
assert result["ema"] == 10
|
|
assert "time" not in result
|
|
assert set(result2.keys()) == {"close", "high"}
|
|
|
|
def test_dictionary_properties(self):
|
|
self.bearish_candle["ema"] = 4
|
|
assert self.bearish_candle["ema"] == 4
|
|
|
|
def test_candle_type(self):
|
|
assert self.bearish_candle.is_bearish()
|
|
assert self.bullish_candle.is_bullish()
|
|
|
|
|
|
class TestCandles:
|
|
@pytest.fixture(scope="class")
|
|
async def candles(self):
|
|
mt = MetaTrader()
|
|
start = datetime(day=5, month=10, year=2023)
|
|
rates = await mt.copy_rates_from("BTCUSD", mt.TIMEFRAME_H1, start, 200)
|
|
return Candles(data=rates)
|
|
|
|
def test_get_series(self, candles):
|
|
series = candles["open"]
|
|
assert isinstance(series, pd.Series)
|
|
assert len(series) == 200
|
|
|
|
def test_get_candle(self, candles):
|
|
candle = candles[10]
|
|
assert isinstance(candle, Candle)
|
|
assert candle in candles
|
|
|
|
def test_slice(self, candles):
|
|
sliced = candles[10:15]
|
|
assert len(sliced) == 5
|
|
assert isinstance(sliced, Candles)
|
|
|
|
def test_setitem(self, candles):
|
|
new_series = candles.open
|
|
new_series = new_series * 2
|
|
candles["double_open"] = new_series
|
|
assert "double_open" in candles.data.columns
|
|
|
|
def test_getattr(self, candles):
|
|
open_series = candles.open
|
|
assert isinstance(open_series, pd.Series)
|
|
assert open_series.equals(candles.data["open"])
|
|
|
|
def test_iter(self, candles):
|
|
l_5 = candles[-5:]
|
|
assert all(isinstance(candle, Candle) for candle in l_5)
|
|
|
|
def test_timeframe(self, candles):
|
|
tf = candles.timeframe
|
|
assert tf == TimeFrame.H1
|
|
|
|
def test_ta_and_rename(self, candles):
|
|
ema = candles.ta.ema(close="open", length=10, append=True)
|
|
assert "EMA_10" in candles.data.columns
|
|
candles.rename(inplace=True, EMA_10="ema")
|
|
assert "ema" in candles.data.columns
|
|
|
|
def test_ta_lib(self, candles):
|
|
fas = candles.ta_lib.above(candles.open, candles.close)
|
|
assert isinstance(fas, pd.Series)
|
|
candles["fas"] = fas
|
|
assert "fas" in candles.data.columns
|