Always remove .mypy_cache; fix more mypy tests

Makefile

@@ -42,6 +42,7 @@ reformat:
 	$(PYTHON) -m black .
 
 test:
+	rm -rf .mypy_cache
 	$(MYPY) -p miplearn
 	$(MYPY) -p tests
 	$(MYPY) -p benchmark

benchmark/benchmark.py

@@ -24,7 +24,7 @@ import importlib
 import logging
 import os
 from pathlib import Path
-from typing import Dict
+from typing import Dict, List
 
 import matplotlib.pyplot as plt
 import pandas as pd
@@ -39,6 +39,7 @@ from miplearn import (
     setup_logger,
     PickleGzInstance,
     write_pickle_gz_multiple,
+    Instance,
 )
 
 setup_logger()
@@ -59,7 +60,7 @@ def train(args: Dict) -> None:
 
     done_filename = f"{basepath}/train/done"
     if not os.path.isfile(done_filename):
-        train_instances = [
+        train_instances: List[Instance] = [
             PickleGzInstance(f) for f in glob.glob(f"{basepath}/train/*.gz")
         ]
         solver = LearningSolver(
@@ -79,7 +80,9 @@ def train(args: Dict) -> None:
 
 def test_baseline(args: Dict) -> None:
     basepath = args["<challenge>"]
-    test_instances = [PickleGzInstance(f) for f in glob.glob(f"{basepath}/test/*.gz")]
+    test_instances: List[Instance] = [
+        PickleGzInstance(f) for f in glob.glob(f"{basepath}/test/*.gz")
+    ]
     csv_filename = f"{basepath}/benchmark_baseline.csv"
     if not os.path.isfile(csv_filename):
         solvers = {
@@ -102,8 +105,12 @@ def test_baseline(args: Dict) -> None:
 
 def test_ml(args: Dict) -> None:
     basepath = args["<challenge>"]
-    test_instances = [PickleGzInstance(f) for f in glob.glob(f"{basepath}/test/*.gz")]
-    train_instances = [PickleGzInstance(f) for f in glob.glob(f"{basepath}/train/*.gz")]
+    test_instances: List[Instance] = [
+        PickleGzInstance(f) for f in glob.glob(f"{basepath}/test/*.gz")
+    ]
+    train_instances: List[Instance] = [
+        PickleGzInstance(f) for f in glob.glob(f"{basepath}/train/*.gz")
+    ]
     csv_filename = f"{basepath}/benchmark_ml.csv"
     if not os.path.isfile(csv_filename):
         solvers = {

tests/test_benchmark.py

@@ -20,7 +20,7 @@ def test_benchmark() -> None:
 
         # Solve training instances
         training_solver = LearningSolver()
-        training_solver.parallel_solve(train_instances, n_jobs=n_jobs)
+        training_solver.parallel_solve(train_instances, n_jobs=n_jobs)  # type: ignore
 
         # Benchmark
         test_solvers = {
@@ -28,8 +28,12 @@ def test_benchmark() -> None:
             "Strategy B": LearningSolver(),
         }
         benchmark = BenchmarkRunner(test_solvers)
-        benchmark.fit(train_instances)
-        benchmark.parallel_solve(test_instances, n_jobs=n_jobs, n_trials=2)
+        benchmark.fit(train_instances)  # type: ignore
+        benchmark.parallel_solve(
+            test_instances,  # type: ignore
+            n_jobs=n_jobs,
+            n_trials=2,
+        )
         assert benchmark.results.values.shape == (12, 20)
 
         benchmark.write_csv("/tmp/benchmark.csv")