Merge pull request #4 from kovalp/convert-to-builtin-int

Convert to builtin int

Author: kovalp

.bumpversion.toml

@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.2.1"
+current_version = "0.3.0"
 parse = "(?P<major>\\d+)\\.(?P<minor>\\d+)\\.(?P<patch>\\d+)"
 serialize = ["{major}.{minor}.{patch}"]
 search = "{current_version}"

CHANGELOG.md

@@ -1,8 +1,8 @@
-# 0.2.0
+# 0.3.0
 
   - Adjustable format for the accuracy and other metrics.
   - Using the hatchling build system to avoid complains about the `project.license` format.
-
+  - Enforce the initial attributes to builtin `ìnt`.  
 
 # 0.1.0
 

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "binary-classification-ratios"
-version = "0.2.1"
+version = "0.3.0"
 description = "Binary classification ratios gathered in one package."
 readme = "README.md"
 requires-python = ">=3.8,<4.0"

src/binary_classification_ratios/__init__.py

@@ -1,6 +1,6 @@
 """."""
 
-__version__ = '0.2.1'
+__version__ = '0.3.0'
 
 from .ratios import BinaryClassificationRatios
 

src/binary_classification_ratios/ratios.py

@@ -3,7 +3,7 @@
 and summarize classification metrics such as accuracy, precision, recall, and F1-score.
 """
 
-from typing import Dict, Union
+from typing import Any, Dict, Union
 
 from binary_classification_ratios.summary import BinaryClassificationSummary
 
@@ -19,12 +19,12 @@ class BinaryClassificationRatios(object):
         fn: Number of false negatives.
     """
 
-    def __init__(self, *, tp: int = 0, tn: int = 0, fp: int = 0, fn: int = 0) -> None:
+    def __init__(self, *, tp: Any = 0, tn: Any = 0, fp: Any = 0, fn: Any = 0) -> None:
         """Initializes a new instance with all zero values."""
-        self.tp = tp
-        self.tn = tn
-        self.fp = fp
-        self.fn = fn
+        self.tp = int(tp)
+        self.tn = int(tn)
+        self.fp = int(fp)
+        self.fn = int(fn)
         self.summary = BinaryClassificationSummary()
 
     def get_summary(self) -> str:

test/test_ratios.py

@@ -11,7 +11,7 @@ def bcr() -> BinaryClassificationRatios:
     return BinaryClassificationRatios(tp=10, tn=9, fp=8, fn=7)
 
 
-def test_classification_ratios_init() -> None:
+def test_no_args_init() -> None:
     """."""
     bcr = BinaryClassificationRatios()
     assert bcr.get_f1_score() == pytest.approx(0.0)
@@ -20,6 +20,15 @@ def test_classification_ratios_init() -> None:
     assert bcr.get_accuracy() == pytest.approx(0.0)
 
 
+def test_convert_to_int() -> None:
+    """."""
+    bcr = BinaryClassificationRatios(tp=10.0, tn=9.0, fp=8.0, fn=7.0)
+    assert isinstance(bcr.tp, int)
+    assert isinstance(bcr.tn, int)
+    assert isinstance(bcr.fp, int)
+    assert isinstance(bcr.fn, int)
+
+
 def test_classification_ratios_meaningful(bcr: BinaryClassificationRatios) -> None:
     """."""
     assert bcr.get_f1_score() == pytest.approx(0.5714285714285715)