d1af736bfc
- Added a new design document outlining the integration of BTC/ETH candle data as additional features in the XRP ML filter, enhancing prediction accuracy. - Introduced `MultiSymbolStream` for combined WebSocket data retrieval of XRP, BTC, and ETH. - Expanded feature set from 13 to 21 by including 8 new BTC/ETH-related features. - Updated various scripts and modules to support the new feature set and data handling. - Enhanced training and deployment scripts to accommodate the new dataset structure. This commit lays the groundwork for improved model performance by leveraging the correlation between BTC and ETH with XRP.
104 lines
2.9 KiB
Python
104 lines
2.9 KiB
Python
import pytest
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import asyncio
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from unittest.mock import AsyncMock, patch, MagicMock
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from src.data_stream import KlineStream
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from src.data_stream import MultiSymbolStream
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def test_multi_symbol_stream_has_three_buffers():
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stream = MultiSymbolStream(
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symbols=["XRPUSDT", "BTCUSDT", "ETHUSDT"],
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interval="1m",
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)
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assert "xrpusdt" in stream.buffers
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assert "btcusdt" in stream.buffers
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assert "ethusdt" in stream.buffers
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def test_multi_symbol_stream_get_dataframe_returns_none_when_empty():
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stream = MultiSymbolStream(
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symbols=["XRPUSDT", "BTCUSDT", "ETHUSDT"],
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interval="1m",
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)
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assert stream.get_dataframe("XRPUSDT") is None
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def test_multi_symbol_stream_get_dataframe_returns_df_when_full():
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import pandas as pd
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stream = MultiSymbolStream(
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symbols=["XRPUSDT", "BTCUSDT", "ETHUSDT"],
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interval="1m",
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buffer_size=200,
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)
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candle = {
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"timestamp": 1000, "open": 1.0, "high": 1.1,
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"low": 0.9, "close": 1.05, "volume": 100.0, "is_closed": True,
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}
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for i in range(50):
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c = candle.copy()
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c["timestamp"] = 1000 + i
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stream.buffers["xrpusdt"].append(c)
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df = stream.get_dataframe("XRPUSDT")
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assert df is not None
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assert len(df) == 50
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@pytest.mark.asyncio
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async def test_kline_stream_parses_message():
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stream = KlineStream(symbol="XRPUSDT", interval="1m")
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raw_msg = {
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"k": {
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"t": 1700000000000,
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"o": "0.5000",
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"h": "0.5100",
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"l": "0.4900",
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"c": "0.5050",
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"v": "100000",
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"x": True,
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}
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}
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candle = stream.parse_kline(raw_msg)
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assert candle["close"] == 0.5050
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assert candle["is_closed"] is True
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@pytest.mark.asyncio
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async def test_callback_called_on_closed_candle():
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received = []
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stream = KlineStream(
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symbol="XRPUSDT",
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interval="1m",
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on_candle=lambda c: received.append(c),
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)
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raw_msg = {
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"k": {
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"t": 1700000000000,
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"o": "0.5",
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"h": "0.51",
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"l": "0.49",
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"c": "0.505",
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"v": "100000",
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"x": True,
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}
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}
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stream.handle_message(raw_msg)
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assert len(received) == 1
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@pytest.mark.asyncio
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async def test_preload_history_fills_buffer():
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stream = KlineStream(symbol="XRPUSDT", interval="1m", buffer_size=200)
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# REST API 응답 형식: [open_time, open, high, low, close, volume, ...]
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fake_klines = [
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[1700000000000 + i * 60000, "0.5", "0.51", "0.49", "0.505", "100000",
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0, "0", "0", "0", "0", "0"]
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for i in range(201) # 201개 반환 → 마지막 1개 제외 → 200개 버퍼
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]
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mock_client = AsyncMock()
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mock_client.futures_klines.return_value = fake_klines
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await stream._preload_history(mock_client, limit=200)
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assert len(stream.buffer) == 200
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assert stream.get_dataframe() is not None
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