feat: use OffTargetDetector and ExecutableRunner as ContextManagers (#64

)

Since `OffTargetDetector` and `ExecutableRunner` are context managers,
it makes sense to type them as such by having them inherit from the
abstract manager base class. This PR also fixes an issue where if tests
fail, IO resources are not cleaned up since context managers were not
being used.

prymer/offtarget/offtarget_detector.py

@@ -75,6 +75,7 @@
 """  # noqa: E501
 
 import itertools
+from contextlib import AbstractContextManager
 from dataclasses import dataclass
 from dataclasses import field
 from dataclasses import replace
@@ -124,7 +125,7 @@ class OffTargetResult:
     right_primer_spans: list[Span] = field(default_factory=list)
 
 
-class OffTargetDetector:
+class OffTargetDetector(AbstractContextManager):
     """
     Detect off-target mappings of primers and primer pairs.
 
@@ -442,4 +443,5 @@ def __exit__(
         traceback: Optional[TracebackType],
     ) -> None:
         """Gracefully terminates any running subprocesses."""
+        super().__exit__(exc_type, exc_value, traceback)
         self.close()

prymer/util/executable_runner.py

@@ -11,13 +11,14 @@
 import os
 import shutil
 import subprocess
+from contextlib import AbstractContextManager
 from pathlib import Path
 from types import TracebackType
 from typing import Optional
 from typing import Self
 
 
-class ExecutableRunner:
+class ExecutableRunner(AbstractContextManager):
     """
     Base class for interaction with subprocess for all command-line tools. The base class supports
     use of the context management protocol and performs basic validation of executable paths.
@@ -67,6 +68,7 @@ def __exit__(
         traceback: Optional[TracebackType],
     ) -> None:
         """Gracefully terminates any running subprocesses."""
+        super().__exit__(exc_type, exc_value, traceback)
         self.close()
 
     @classmethod

tests/api/test_picking.py

@@ -573,31 +573,29 @@ def _pick_top_primer_pairs(
     max_primer_pair_hits: int,
     min_difference: int = 1,
 ) -> list[PrimerPair]:
-    offtarget_detector = OffTargetDetector(
-        ref=picking_ref,
-        max_primer_hits=max_primer_hits,
-        max_primer_pair_hits=max_primer_pair_hits,
-        three_prime_region_length=5,
-        max_mismatches_in_three_prime_region=0,
-        max_mismatches=0,
-        max_amplicon_size=params.amplicon_sizes.max,
-    )
-    dimer_checker = NtThermoAlign()
-
-    picked = pick_top_primer_pairs(
-        primer_pairs=primer_pairs,
-        num_primers=len(primer_pairs),
-        min_difference=min_difference,
-        params=params,
-        offtarget_detector=offtarget_detector,
-        is_dimer_tm_ok=lambda s1, s2: (
-            dimer_checker.duplex_tm(s1=s1, s2=s2) <= params.max_dimer_tm
-        ),
-    )
-    offtarget_detector.close()
-    dimer_checker.close()
-
-    return picked
+    with (
+        NtThermoAlign() as dimer_checker,
+        OffTargetDetector(
+            ref=picking_ref,
+            max_primer_hits=max_primer_hits,
+            max_primer_pair_hits=max_primer_pair_hits,
+            three_prime_region_length=5,
+            max_mismatches_in_three_prime_region=0,
+            max_mismatches=0,
+            max_amplicon_size=params.amplicon_sizes.max,
+        ) as offtarget_detector,
+    ):
+        picked: list[PrimerPair] = pick_top_primer_pairs(
+            primer_pairs=primer_pairs,
+            num_primers=len(primer_pairs),
+            min_difference=min_difference,
+            params=params,
+            offtarget_detector=offtarget_detector,
+            is_dimer_tm_ok=lambda s1, s2: (
+                dimer_checker.duplex_tm(s1=s1, s2=s2) <= params.max_dimer_tm
+            ),
+        )
+        return picked
 
 
 _PARAMS: FilteringParams = _zero_score_filtering_params(_score_input())