refactor(layout): rename multi_swarm → multi_swarm_core con doppia nidificazione uv workspace

- mv src/multi_swarm → src/multi_swarm_core/multi_swarm_core (member layout)
- sed-replace globale degli import: from/import multi_swarm.* → multi_swarm_core.*
- 115 occorrenze aggiornate in src/ scripts/ tests/
- multi_swarm_coevolutive (nome repo) preservato dal word boundary

Pre-condizione per il setup uv workspace della Fase 3.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

tests/integration/test_e2e_minimal_run.py

@@ -5,10 +5,10 @@ import numpy as np
 import pandas as pd
 import pytest
 
-from multi_swarm.genome.hypothesis import ModelTier
-from multi_swarm.llm.client import CompletionResult
-from multi_swarm.orchestrator.run import RunConfig, run_phase1
-from multi_swarm.persistence.repository import Repository
+from multi_swarm_core.genome.hypothesis import ModelTier
+from multi_swarm_core.llm.client import CompletionResult
+from multi_swarm_core.orchestrator.run import RunConfig, run_phase1
+from multi_swarm_core.persistence.repository import Repository
 
 
 @pytest.fixture

tests/integration/test_ga_loop_with_prompt_mutator.py

@@ -9,8 +9,8 @@ from __future__ import annotations
 import random
 from dataclasses import dataclass
 
-from multi_swarm.ga.loop import GAConfig, next_generation
-from multi_swarm.genome.hypothesis import HypothesisAgentGenome, ModelTier
+from multi_swarm_core.ga.loop import GAConfig, next_generation
+from multi_swarm_core.genome.hypothesis import HypothesisAgentGenome, ModelTier
 
 _PROMPT_TEMPLATES = (
     "Strategia mean-reversion 1h. Entry long RSI(14) < 30 e close > SMA(50). Stop 2%.",

tests/unit/test_adversarial.py

@@ -4,14 +4,14 @@ import numpy as np
 import pandas as pd
 import pytest
 
-from multi_swarm.agents.adversarial import (
+from multi_swarm_core.agents.adversarial import (
     AdversarialAgent,
     AdversarialReport,
     Severity,
 )
-from multi_swarm.backtest.engine import BacktestResult
-from multi_swarm.backtest.orders import Side, Trade
-from multi_swarm.protocol.parser import parse_strategy
+from multi_swarm_core.backtest.engine import BacktestResult
+from multi_swarm_core.backtest.orders import Side, Trade
+from multi_swarm_core.protocol.parser import parse_strategy
 
 
 @pytest.fixture
@@ -178,10 +178,10 @@ def test_undertrading_under_10_is_high(monkeypatch: pytest.MonkeyPatch,
         return lambda df: fake_signals
 
     monkeypatch.setattr(
-        "multi_swarm.agents.adversarial.BacktestEngine.run", fake_run
+        "multi_swarm_core.agents.adversarial.BacktestEngine.run", fake_run
     )
     monkeypatch.setattr(
-        "multi_swarm.agents.adversarial.compile_strategy", fake_compile
+        "multi_swarm_core.agents.adversarial.compile_strategy", fake_compile
     )
 
     src = _MINIMAL_STRATEGY_SRC
@@ -220,8 +220,8 @@ def test_undertrading_threshold_parametric(monkeypatch: pytest.MonkeyPatch,
     def fake_compile(strategy):  # type: ignore[no-untyped-def]
         return lambda df: fake_signals
 
-    monkeypatch.setattr("multi_swarm.agents.adversarial.BacktestEngine.run", fake_run)
-    monkeypatch.setattr("multi_swarm.agents.adversarial.compile_strategy", fake_compile)
+    monkeypatch.setattr("multi_swarm_core.agents.adversarial.BacktestEngine.run", fake_run)
+    monkeypatch.setattr("multi_swarm_core.agents.adversarial.compile_strategy", fake_compile)
 
     ast = parse_strategy(_MINIMAL_STRATEGY_SRC)
     # Default threshold 10: 15 trade NON killato
@@ -269,10 +269,10 @@ def test_overtrading_with_tighter_threshold(monkeypatch: pytest.MonkeyPatch,
         return lambda df: fake_signals
 
     monkeypatch.setattr(
-        "multi_swarm.agents.adversarial.BacktestEngine.run", fake_run
+        "multi_swarm_core.agents.adversarial.BacktestEngine.run", fake_run
     )
     monkeypatch.setattr(
-        "multi_swarm.agents.adversarial.compile_strategy", fake_compile
+        "multi_swarm_core.agents.adversarial.compile_strategy", fake_compile
     )
 
     src = _MINIMAL_STRATEGY_SRC
@@ -315,10 +315,10 @@ def test_flat_too_long_flagged(monkeypatch: pytest.MonkeyPatch,
         return lambda df: fake_signals
 
     monkeypatch.setattr(
-        "multi_swarm.agents.adversarial.BacktestEngine.run", fake_run
+        "multi_swarm_core.agents.adversarial.BacktestEngine.run", fake_run
     )
     monkeypatch.setattr(
-        "multi_swarm.agents.adversarial.compile_strategy", fake_compile
+        "multi_swarm_core.agents.adversarial.compile_strategy", fake_compile
     )
 
     src = _MINIMAL_STRATEGY_SRC
@@ -367,10 +367,10 @@ def test_fees_eat_alpha_flagged(monkeypatch: pytest.MonkeyPatch,
         return lambda df: fake_signals
 
     monkeypatch.setattr(
-        "multi_swarm.agents.adversarial.BacktestEngine.run", fake_run
+        "multi_swarm_core.agents.adversarial.BacktestEngine.run", fake_run
     )
     monkeypatch.setattr(
-        "multi_swarm.agents.adversarial.compile_strategy", fake_compile
+        "multi_swarm_core.agents.adversarial.compile_strategy", fake_compile
     )
 
     src = _MINIMAL_STRATEGY_SRC
@@ -413,10 +413,10 @@ def test_time_in_market_too_high_flagged(monkeypatch: pytest.MonkeyPatch,
         return lambda df: fake_signals
 
     monkeypatch.setattr(
-        "multi_swarm.agents.adversarial.BacktestEngine.run", fake_run
+        "multi_swarm_core.agents.adversarial.BacktestEngine.run", fake_run
     )
     monkeypatch.setattr(
-        "multi_swarm.agents.adversarial.compile_strategy", fake_compile
+        "multi_swarm_core.agents.adversarial.compile_strategy", fake_compile
     )
 
     src = _MINIMAL_STRATEGY_SRC
@@ -461,10 +461,10 @@ def test_reasonable_balanced_strategy_not_flagged(monkeypatch: pytest.MonkeyPatc
         return lambda df: fake_signals
 
     monkeypatch.setattr(
-        "multi_swarm.agents.adversarial.BacktestEngine.run", fake_run
+        "multi_swarm_core.agents.adversarial.BacktestEngine.run", fake_run
     )
     monkeypatch.setattr(
-        "multi_swarm.agents.adversarial.compile_strategy", fake_compile
+        "multi_swarm_core.agents.adversarial.compile_strategy", fake_compile
     )
 
     src = _MINIMAL_STRATEGY_SRC

tests/unit/test_backtest_engine.py

@@ -2,8 +2,8 @@ import numpy as np
 import pandas as pd
 import pytest
 
-from multi_swarm.backtest.engine import BacktestEngine
-from multi_swarm.backtest.orders import Side
+from multi_swarm_core.backtest.engine import BacktestEngine
+from multi_swarm_core.backtest.orders import Side
 
 
 @pytest.fixture

tests/unit/test_backtest_orders.py

@@ -2,7 +2,7 @@ from datetime import UTC, datetime
 
 import pytest
 
-from multi_swarm.backtest.orders import Order, Position, Side, Trade
+from multi_swarm_core.backtest.orders import Order, Position, Side, Trade
 
 
 def test_order_validates_side() -> None:

tests/unit/test_cerbero_client.py

@@ -1,7 +1,7 @@
 import pytest
 import responses
 
-from multi_swarm.cerbero.client import CerberoClient
+from multi_swarm_core.cerbero.client import CerberoClient
 
 
 @responses.activate

tests/unit/test_cerbero_ohlcv.py

@@ -6,7 +6,7 @@ from pathlib import Path
 import pandas as pd
 import pytest
 
-from multi_swarm.data.cerbero_ohlcv import CerberoOHLCVLoader, OHLCVRequest
+from multi_swarm_core.data.cerbero_ohlcv import CerberoOHLCVLoader, OHLCVRequest
 
 
 @pytest.fixture

tests/unit/test_cerbero_tools.py

@@ -1,6 +1,6 @@
 import pytest
 
-from multi_swarm.cerbero.tools import CerberoTools
+from multi_swarm_core.cerbero.tools import CerberoTools
 
 
 def test_tools_dispatch_sma(mocker):

tests/unit/test_config.py

@@ -1,4 +1,4 @@
-"""Tests for multi_swarm.config.Settings.
+"""Tests for multi_swarm_core.config.Settings.
 
 Note on .env isolation:
 The happy-path test relies on monkeypatch.setenv to provide values.
@@ -10,7 +10,7 @@ absence of required env vars. This keeps the test deterministic both in CI
 
 import pytest
 
-from multi_swarm.config import Settings
+from multi_swarm_core.config import Settings
 
 
 def test_settings_loads_from_env(monkeypatch: pytest.MonkeyPatch) -> None:

tests/unit/test_cost_tracker.py

@@ -1,5 +1,5 @@
-from multi_swarm.genome.hypothesis import ModelTier
-from multi_swarm.llm.cost_tracker import CostTracker, estimate_cost
+from multi_swarm_core.genome.hypothesis import ModelTier
+from multi_swarm_core.llm.cost_tracker import CostTracker, estimate_cost
 
 
 def test_estimate_cost_tier_c():

tests/unit/test_diversity.py

@@ -1,6 +1,6 @@
 from __future__ import annotations
 
-from multi_swarm.metrics.diversity import population_prompt_diversity
+from multi_swarm_core.metrics.diversity import population_prompt_diversity
 
 
 def test_empty_or_single_prompt_zero_diversity() -> None:

tests/unit/test_falsification.py

@@ -4,8 +4,8 @@ import numpy as np
 import pandas as pd
 import pytest
 
-from multi_swarm.agents.falsification import FalsificationAgent, FalsificationReport
-from multi_swarm.protocol.parser import parse_strategy
+from multi_swarm_core.agents.falsification import FalsificationAgent, FalsificationReport
+from multi_swarm_core.protocol.parser import parse_strategy
 
 
 @pytest.fixture

tests/unit/test_fitness.py

@@ -1,8 +1,8 @@
 from itertools import pairwise
 
-from multi_swarm.agents.adversarial import AdversarialReport, Finding, Severity
-from multi_swarm.agents.falsification import FalsificationReport
-from multi_swarm.ga.fitness import compute_fitness
+from multi_swarm_core.agents.adversarial import AdversarialReport, Finding, Severity
+from multi_swarm_core.agents.falsification import FalsificationReport
+from multi_swarm_core.ga.fitness import compute_fitness
 
 
 def make_falsification(

tests/unit/test_ga_initial.py

@@ -1,7 +1,7 @@
 import random
 
-from multi_swarm.ga.initial import build_initial_population
-from multi_swarm.genome.hypothesis import ModelTier
+from multi_swarm_core.ga.initial import build_initial_population
+from multi_swarm_core.genome.hypothesis import ModelTier
 
 
 def test_initial_population_size():

tests/unit/test_ga_loop.py

@@ -1,7 +1,7 @@
 import random
 
-from multi_swarm.ga.loop import GAConfig, next_generation
-from multi_swarm.genome.hypothesis import HypothesisAgentGenome, ModelTier
+from multi_swarm_core.ga.loop import GAConfig, next_generation
+from multi_swarm_core.genome.hypothesis import HypothesisAgentGenome, ModelTier
 
 
 def make(idx: int) -> HypothesisAgentGenome:

tests/unit/test_ga_summary.py

@@ -2,7 +2,7 @@ import math
 
 import pytest
 
-from multi_swarm.ga.summary import generation_summary
+from multi_swarm_core.ga.summary import generation_summary
 
 
 def test_summary_basic_stats():

tests/unit/test_genome_crossover.py

@@ -1,7 +1,7 @@
 import random
 
-from multi_swarm.genome.crossover import uniform_crossover
-from multi_swarm.genome.hypothesis import HypothesisAgentGenome, ModelTier
+from multi_swarm_core.genome.crossover import uniform_crossover
+from multi_swarm_core.genome.hypothesis import HypothesisAgentGenome, ModelTier
 
 
 def make(name: str) -> HypothesisAgentGenome:

tests/unit/test_genome_hypothesis.py

@@ -1,4 +1,4 @@
-from multi_swarm.genome.hypothesis import HypothesisAgentGenome, ModelTier
+from multi_swarm_core.genome.hypothesis import HypothesisAgentGenome, ModelTier
 
 
 def test_genome_creation_defaults():

tests/unit/test_genome_mutation.py

@@ -2,8 +2,8 @@ import random
 
 import pytest
 
-from multi_swarm.genome.hypothesis import HypothesisAgentGenome, ModelTier
-from multi_swarm.genome.mutation import (
+from multi_swarm_core.genome.hypothesis import HypothesisAgentGenome, ModelTier
+from multi_swarm_core.genome.mutation import (
     COGNITIVE_STYLES,
     FEATURE_POOL,
     mutate_cognitive_style,

tests/unit/test_hypothesis_agent.py

@@ -1,8 +1,8 @@
 import json
 
-from multi_swarm.agents.hypothesis import HypothesisAgent, MarketSummary
-from multi_swarm.genome.hypothesis import HypothesisAgentGenome, ModelTier
-from multi_swarm.llm.client import CompletionResult, EmptyCompletionError
+from multi_swarm_core.agents.hypothesis import HypothesisAgent, MarketSummary
+from multi_swarm_core.genome.hypothesis import HypothesisAgentGenome, ModelTier
+from multi_swarm_core.llm.client import CompletionResult, EmptyCompletionError
 
 
 def make_summary() -> MarketSummary:

tests/unit/test_llm_client.py

@@ -1,7 +1,7 @@
 import pytest
 
-from multi_swarm.genome.hypothesis import HypothesisAgentGenome, ModelTier
-from multi_swarm.llm.client import CompletionResult, LLMClient
+from multi_swarm_core.genome.hypothesis import HypothesisAgentGenome, ModelTier
+from multi_swarm_core.llm.client import CompletionResult, LLMClient
 
 
 def make_genome(tier: ModelTier) -> HypothesisAgentGenome:
@@ -23,7 +23,7 @@ def test_completion_tier_c_uses_openrouter(mocker):
     fake_response.usage = mocker.MagicMock(prompt_tokens=100, completion_tokens=200)
     fake_openai.chat.completions.create.return_value = fake_response
 
-    mocker.patch("multi_swarm.llm.client.OpenAI", return_value=fake_openai)
+    mocker.patch("multi_swarm_core.llm.client.OpenAI", return_value=fake_openai)
 
     client = LLMClient(openrouter_api_key="or-x")
     g = make_genome(ModelTier.C)
@@ -43,7 +43,7 @@ def test_completion_tier_b_uses_openrouter_with_anthropic_model(mocker):
     fake_response.choices = [mocker.MagicMock(message=mocker.MagicMock(content="(strategy ...)"))]
     fake_response.usage = mocker.MagicMock(prompt_tokens=80, completion_tokens=150)
     fake_openai.chat.completions.create.return_value = fake_response
-    mocker.patch("multi_swarm.llm.client.OpenAI", return_value=fake_openai)
+    mocker.patch("multi_swarm_core.llm.client.OpenAI", return_value=fake_openai)
 
     client = LLMClient(openrouter_api_key="or-x")
     g = make_genome(ModelTier.B)
@@ -67,7 +67,7 @@ def test_completion_retries_on_connection_error(mocker):
     fake_openai.chat.completions.create.side_effect = openai.APIConnectionError(
         request=mocker.MagicMock()
     )
-    mocker.patch("multi_swarm.llm.client.OpenAI", return_value=fake_openai)
+    mocker.patch("multi_swarm_core.llm.client.OpenAI", return_value=fake_openai)
 
     client = LLMClient(openrouter_api_key="or-x")
     g = make_genome(ModelTier.C)
@@ -86,7 +86,7 @@ def test_completion_uses_custom_model_tier_c(mocker):
     ]
     fake_response.usage = mocker.MagicMock(prompt_tokens=10, completion_tokens=20)
     fake_openai.chat.completions.create.return_value = fake_response
-    mocker.patch("multi_swarm.llm.client.OpenAI", return_value=fake_openai)
+    mocker.patch("multi_swarm_core.llm.client.OpenAI", return_value=fake_openai)
 
     client = LLMClient(
         openrouter_api_key="or-x",
@@ -109,7 +109,7 @@ def test_completion_uses_custom_model_tier_b(mocker):
     ]
     fake_response.usage = mocker.MagicMock(prompt_tokens=10, completion_tokens=20)
     fake_openai.chat.completions.create.return_value = fake_response
-    mocker.patch("multi_swarm.llm.client.OpenAI", return_value=fake_openai)
+    mocker.patch("multi_swarm_core.llm.client.OpenAI", return_value=fake_openai)
 
     client = LLMClient(
         openrouter_api_key="or-x",
@@ -130,7 +130,7 @@ def test_completion_tier_s_uses_openrouter_with_anthropic_model(mocker):
     fake_response.choices = [mocker.MagicMock(message=mocker.MagicMock(content="(strategy s)"))]
     fake_response.usage = mocker.MagicMock(prompt_tokens=50, completion_tokens=100)
     fake_openai.chat.completions.create.return_value = fake_response
-    mocker.patch("multi_swarm.llm.client.OpenAI", return_value=fake_openai)
+    mocker.patch("multi_swarm_core.llm.client.OpenAI", return_value=fake_openai)
 
     client = LLMClient(openrouter_api_key="or-x")
     g = make_genome(ModelTier.S)
@@ -149,7 +149,7 @@ def test_completion_tier_a_uses_openrouter_with_anthropic_model(mocker):
     fake_response.choices = [mocker.MagicMock(message=mocker.MagicMock(content="(strategy a)"))]
     fake_response.usage = mocker.MagicMock(prompt_tokens=40, completion_tokens=80)
     fake_openai.chat.completions.create.return_value = fake_response
-    mocker.patch("multi_swarm.llm.client.OpenAI", return_value=fake_openai)
+    mocker.patch("multi_swarm_core.llm.client.OpenAI", return_value=fake_openai)
 
     client = LLMClient(openrouter_api_key="or-x")
     g = make_genome(ModelTier.A)
@@ -170,7 +170,7 @@ def test_completion_tier_d_uses_openrouter_with_llama(mocker):
     ]
     fake_response.usage = mocker.MagicMock(prompt_tokens=30, completion_tokens=70)
     fake_openai.chat.completions.create.return_value = fake_response
-    mocker.patch("multi_swarm.llm.client.OpenAI", return_value=fake_openai)
+    mocker.patch("multi_swarm_core.llm.client.OpenAI", return_value=fake_openai)
 
     client = LLMClient(openrouter_api_key="or-x")
     g = make_genome(ModelTier.D)
@@ -191,7 +191,7 @@ def test_completion_uses_custom_model_tier_s(mocker):
     ]
     fake_response.usage = mocker.MagicMock(prompt_tokens=10, completion_tokens=20)
     fake_openai.chat.completions.create.return_value = fake_response
-    mocker.patch("multi_swarm.llm.client.OpenAI", return_value=fake_openai)
+    mocker.patch("multi_swarm_core.llm.client.OpenAI", return_value=fake_openai)
 
     client = LLMClient(
         openrouter_api_key="or-x",
@@ -221,7 +221,7 @@ def test_completion_succeeds_after_one_retry(mocker):
         openai.APITimeoutError(request=mocker.MagicMock()),
         fake_response,
     ]
-    mocker.patch("multi_swarm.llm.client.OpenAI", return_value=fake_openai)
+    mocker.patch("multi_swarm_core.llm.client.OpenAI", return_value=fake_openai)
 
     client = LLMClient(openrouter_api_key="or-x")
     g = make_genome(ModelTier.C)

tests/unit/test_market_summary.py

@@ -1,7 +1,7 @@
 import numpy as np
 import pandas as pd
 
-from multi_swarm.agents.market_summary import build_market_summary
+from multi_swarm_core.agents.market_summary import build_market_summary
 
 
 def test_build_summary_basic() -> None:

tests/unit/test_metrics_basic.py

@@ -2,7 +2,7 @@ import numpy as np
 import pandas as pd
 import pytest
 
-from multi_swarm.metrics.basic import max_drawdown, sharpe_ratio, total_return
+from multi_swarm_core.metrics.basic import max_drawdown, sharpe_ratio, total_return
 
 
 def test_sharpe_zero_returns():

tests/unit/test_metrics_dsr.py

@@ -1,7 +1,7 @@
 import numpy as np
 import pandas as pd
 
-from multi_swarm.metrics.dsr import deflated_sharpe_ratio, expected_max_sharpe
+from multi_swarm_core.metrics.dsr import deflated_sharpe_ratio, expected_max_sharpe
 
 
 def test_expected_max_sharpe_grows_with_n_trials():

tests/unit/test_mutation_dispatcher.py

@@ -4,8 +4,8 @@ import random
 from collections import Counter
 from dataclasses import dataclass
 
-from multi_swarm.genome.hypothesis import HypothesisAgentGenome, ModelTier
-from multi_swarm.genome.mutation import weighted_random_mutate
+from multi_swarm_core.genome.hypothesis import HypothesisAgentGenome, ModelTier
+from multi_swarm_core.genome.mutation import weighted_random_mutate
 
 _PROMPT = (
     "Strategia mean-reversion 1h BTC. Entry long quando RSI(14) < 30 e "

tests/unit/test_mutation_prompt_llm.py

@@ -3,8 +3,8 @@ from __future__ import annotations
 import random
 from dataclasses import dataclass
 
-from multi_swarm.genome.hypothesis import HypothesisAgentGenome, ModelTier
-from multi_swarm.genome.mutation_prompt_llm import (
+from multi_swarm_core.genome.hypothesis import HypothesisAgentGenome, ModelTier
+from multi_swarm_core.genome.mutation_prompt_llm import (
     MUTATION_INSTRUCTIONS,
     _extract_prompt,
     is_valid_prompt,

tests/unit/test_protocol_compiler.py

@@ -6,9 +6,9 @@ import numpy as np
 import pandas as pd
 import pytest
 
-from multi_swarm.backtest.orders import Side
-from multi_swarm.protocol.compiler import compile_strategy
-from multi_swarm.protocol.parser import parse_strategy
+from multi_swarm_core.backtest.orders import Side
+from multi_swarm_core.protocol.compiler import compile_strategy
+from multi_swarm_core.protocol.parser import parse_strategy
 
 
 @pytest.fixture

tests/unit/test_protocol_parser.py

@@ -2,7 +2,7 @@ import json
 
 import pytest
 
-from multi_swarm.protocol.grammar import (
+from multi_swarm_core.protocol.grammar import (
     ACTION_VALUES,
     ALL_OPS,
     COMPARATOR_OPS,
@@ -10,7 +10,7 @@ from multi_swarm.protocol.grammar import (
     KIND_VALUES,
     LOGICAL_OPS,
 )
-from multi_swarm.protocol.parser import (
+from multi_swarm_core.protocol.parser import (
     FeatureNode,
     IndicatorNode,
     LiteralNode,

tests/unit/test_protocol_validator.py

@@ -2,8 +2,8 @@ import json
 
 import pytest
 
-from multi_swarm.protocol.parser import parse_strategy
-from multi_swarm.protocol.validator import ValidationError, validate_strategy
+from multi_swarm_core.protocol.parser import parse_strategy
+from multi_swarm_core.protocol.validator import ValidationError, validate_strategy
 
 
 def _wrap(condition: dict, action: str = "entry-long") -> str:

tests/unit/test_repository.py

@@ -1,8 +1,8 @@
 import json
 from pathlib import Path
 
-from multi_swarm.genome.hypothesis import HypothesisAgentGenome, ModelTier
-from multi_swarm.persistence.repository import Repository
+from multi_swarm_core.genome.hypothesis import HypothesisAgentGenome, ModelTier
+from multi_swarm_core.persistence.repository import Repository
 
 
 def make_genome(idx: int) -> HypothesisAgentGenome:

tests/unit/test_selection.py

@@ -1,7 +1,7 @@
 import random
 
-from multi_swarm.ga.selection import elite_select, tournament_select
-from multi_swarm.genome.hypothesis import HypothesisAgentGenome, ModelTier
+from multi_swarm_core.ga.selection import elite_select, tournament_select
+from multi_swarm_core.genome.hypothesis import HypothesisAgentGenome, ModelTier
 
 
 def make(idx: int) -> HypothesisAgentGenome:

tests/unit/test_splits.py

@@ -1,7 +1,7 @@
 import pandas as pd
 import pytest
 
-from multi_swarm.data.splits import expanding_walk_forward
+from multi_swarm_core.data.splits import expanding_walk_forward
 
 
 @pytest.fixture