Add opportunity dataset collection
This commit is contained in:
Carlos Ouyang
@@ -5,7 +5,12 @@ from __future__ import annotations
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import unittest
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from unittest.mock import patch
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from coinhunter.services import opportunity_service, portfolio_service, signal_service
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from coinhunter.services import (
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opportunity_service,
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portfolio_service,
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research_service,
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signal_service,
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)
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class FakeSpotClient:
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@@ -253,6 +258,37 @@ class OpportunityServiceTestCase(unittest.TestCase):
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"entry_threshold": 1.5,
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"watch_threshold": 0.6,
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"overlap_penalty": 0.6,
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"auto_research": False,
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"research_provider": "coingecko",
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"research_timeout_seconds": 4.0,
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"risk_limits": {
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"min_liquidity": 0.0,
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"max_overextension": 0.08,
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"max_downside_risk": 0.3,
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"max_unlock_risk": 0.75,
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"max_regulatory_risk": 0.75,
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"min_quality_for_add": 0.0,
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},
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"weights": {
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"trend": 1.0,
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"momentum": 1.0,
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"breakout": 0.8,
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"pullback": 0.4,
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"volume": 0.7,
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"liquidity": 0.3,
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"trend_alignment": 0.8,
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"fundamental": 0.8,
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"tokenomics": 0.7,
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"catalyst": 0.5,
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"adoption": 0.4,
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"smart_money": 0.3,
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"volatility_penalty": 0.5,
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"overextension_penalty": 0.7,
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"downside_penalty": 0.5,
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"unlock_penalty": 0.8,
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"regulatory_penalty": 0.4,
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"position_concentration_penalty": 0.6,
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},
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},
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"portfolio": {
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"add_threshold": 1.5,
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@@ -314,3 +350,133 @@ class OpportunityServiceTestCase(unittest.TestCase):
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score, metrics = signal_service.score_market_signal([], [], {"price_change_pct": 1.0}, {})
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self.assertEqual(score, 0.0)
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self.assertEqual(metrics["trend"], 0.0)
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def test_overextended_candidate_is_not_an_add(self):
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closes = [100, 110, 121, 133, 146, 160, 176]
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volumes = [100, 120, 130, 150, 170, 190, 230]
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ticker = {
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"price_change_pct": 35.0,
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"quote_volume": 20_000_000.0,
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"high_price": 180.0,
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"low_price": 95.0,
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}
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score, metrics = opportunity_service._score_candidate(
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closes, volumes, ticker, self.config["opportunity"]["weights"], 0.0, {"1h": closes, "4h": closes}
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)
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action, reasons = opportunity_service._action_for(score, 0.0, metrics)
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self.assertGreater(score, 1.0)
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self.assertGreater(metrics["overextension"], 0.08)
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self.assertEqual(action, "observe")
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self.assertIn("move looks extended; wait for a cleaner entry", reasons)
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def test_external_research_signals_improve_candidate_quality(self):
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closes = [100, 101, 102, 103, 104, 105, 106]
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volumes = [100, 105, 110, 115, 120, 125, 130]
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ticker = {
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"price_change_pct": 4.0,
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"quote_volume": 50_000_000.0,
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"high_price": 110.0,
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"low_price": 95.0,
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}
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base_score, base_metrics = opportunity_service._score_candidate(
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closes, volumes, ticker, self.config["opportunity"]["weights"], 0.0, {"1h": closes}
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)
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researched_score, researched_metrics = opportunity_service._score_candidate(
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closes,
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volumes,
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ticker,
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self.config["opportunity"]["weights"],
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0.0,
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{"1h": closes},
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{
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"fundamental": 85,
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"tokenomics": 80,
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"catalyst": 70,
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"adoption": 90,
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"smart_money": 60,
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},
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)
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self.assertGreater(researched_score, base_score)
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self.assertEqual(base_metrics["quality"], 0.0)
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self.assertGreater(researched_metrics["quality"], 0.7)
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def test_scan_uses_automatic_external_research(self):
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config = self.config | {
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"opportunity": self.config["opportunity"]
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| {
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"auto_research": True,
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"top_n": 2,
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}
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}
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with (
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patch.object(opportunity_service, "audit_event", return_value=None),
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patch.object(
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opportunity_service,
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"get_external_research",
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return_value={
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"SOLUSDT": {
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"fundamental": 0.9,
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"tokenomics": 0.8,
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"catalyst": 0.9,
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"adoption": 0.8,
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"smart_money": 0.7,
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"unlock_risk": 0.1,
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"regulatory_risk": 0.1,
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"research_confidence": 0.9,
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}
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},
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) as research_mock,
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):
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payload = opportunity_service.scan_opportunities(config, spot_client=FakeSpotClient())
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research_mock.assert_called_once()
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sol = next(item for item in payload["recommendations"] if item["symbol"] == "SOLUSDT")
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self.assertEqual(sol["metrics"]["fundamental"], 0.9)
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self.assertEqual(sol["metrics"]["research_confidence"], 0.9)
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def test_unlock_risk_blocks_add_recommendation(self):
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metrics = {
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"liquidity": 0.8,
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"overextension": 0.0,
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"downside_risk": 0.0,
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"unlock_risk": 0.9,
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"regulatory_risk": 0.0,
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"quality": 0.8,
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}
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action, reasons = opportunity_service._action_for(
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3.0,
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0.0,
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metrics,
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self.config["opportunity"]["risk_limits"],
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)
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self.assertEqual(action, "observe")
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self.assertIn("token unlock or dilution risk is too high", reasons)
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class ResearchServiceTestCase(unittest.TestCase):
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def test_coingecko_market_data_becomes_research_signals(self):
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signals = research_service._coingecko_market_to_signals(
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{
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"id": "solana",
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"symbol": "sol",
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"market_cap": 80_000_000_000,
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"fully_diluted_valuation": 95_000_000_000,
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"total_volume": 5_000_000_000,
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"market_cap_rank": 6,
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"circulating_supply": 550_000_000,
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"total_supply": 600_000_000,
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"max_supply": None,
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"price_change_percentage_7d_in_currency": 12.0,
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"price_change_percentage_30d_in_currency": 35.0,
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"price_change_percentage_200d_in_currency": 80.0,
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},
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is_trending=True,
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)
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self.assertGreater(signals["fundamental"], 0.6)
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self.assertGreater(signals["tokenomics"], 0.8)
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self.assertGreater(signals["catalyst"], 0.6)
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self.assertLess(signals["unlock_risk"], 0.2)
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