+edit

.bumpversion.toml

@@ -1,5 +1,5 @@
 [tool.bumpversion]
-current_version = "0.1.0"
+current_version = "0.1.5"
 parse = "(?P<major>\\d+)\\.(?P<minor>\\d+)\\.(?P<patch>\\d+)"
 serialize = ["{major}.{minor}.{patch}"]
 search = "{current_version}"

.github/workflows/unittest.yml

@@ -5,9 +5,9 @@ name: unittest
 
 on:
   push:
-    branches: [ "master" ]
+    branches: [ "main" ]
   pull_request:
-    branches: [ "master" ]
+    branches: [ "main" ]
 
 jobs:
   build:

.gitignore

@@ -5,3 +5,4 @@
 **__pycache__
 /.python-version
 /.coverage
+/src/binary_classification_ratios.egg-info/

README.md

@@ -1,6 +1,6 @@
 # Binary classification ratios
 
-<img src="assets/logo-binary-classification-ratios.svg" alt="logo-binary-classification-ratios" width="96">
+<img src="https://raw.githubusercontent.com/kovalp/binary_classification_ratios/main/assets/logo-binary-classification-ratios.svg" alt="logo-binary-classification-ratios" width="96">
 
 The package helps computing the quality metrics (ratios) arising in the binary classification.
 The binary classification is given by the confusion matrix. The confusion matrix is given
@@ -25,15 +25,24 @@ $$
 ## Usage
 
 There is a command-line utility `binary-classification-ratios`. The utility takes the 
-optional arguments `-tp`, `-tn`, `-fp`, and `-fn`, computes the popular binary-classification
-ratios such as $\mathrm{Accuracy}$, $\mathrm{Recall}$, $\mathrm{Precision}$ and 
-$\mathrm{F1-score}$ and prints them to terminal.
+optional arguments &nbsp;-tp, &nbsp;-tn, &nbsp;-fp, and &nbsp;-fn,
+computes the popular binary-classification ratios such as Accuracy, Recall, Precision and 
+F1-score and prints them to terminal.
 
-The package is designed to be useful in other projects where the elements of the confusion matrix
-are known.
+```shell
 
-```python
+binary-classification-ratios -tp 10 -tn 20 -fp 30 -fn 40
+Confusion matrix: TP 10 TN 20 FP 30 FN 40
+     accuracy 0.300
+    precision 0.250
+       recall 0.200
+     f1-score 0.222
+```
 
+The package is designed to be useful in other Python projects where the elements of the confusion matrix
+are known
+
+```python
 from binary_classification_ratios import BinaryClassificationRatios
 
 ratios = BinaryClassificationRatios(tp=10, tn=20, fp=30, fn=40)
@@ -42,20 +51,9 @@ print(ratios.get_summary())
 ratios.assert_min(0.9, 0.8, 0.7)
 ```
 
-## Development install
-
-Please, consult the maintainers README.
-
 ## Install
 
 ```shell
-uv sync --no-dev
-```
-or 
 
-```shell 
 pip install binary-classification-ratios
 ```
-
-
-

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "binary-classification-ratios"
-version = "0.1.0"
+version = "0.1.5"
 description = "Binary classification ratios gathered in one package."
 readme = "README.md"
 requires-python = ">=3.8,<4.0"
@@ -26,11 +26,11 @@ dev = [
     "pytest>=8.4.1;          python_version>='3.9'",
     "pytest-cov>=6.2.1;      python_version>='3.9'",
     "bump-my-version>=1.2.1; python_version>='3.9'",
-    "ruff>=0.12.9",
+    "ruff>=0.12.11",
 ]
 
 [project.scripts]
-binary-classificaion-ratios = "binary_classification_ratios.cli.run_bcr:main"
+binary-classification-ratios = "binary_classification_ratios.cli.main:main"
 
 [tool.uv]
 package = true

src/binary_classification_ratios/__init__.py

@@ -1,6 +1,6 @@
 """."""
 
-__version__ = '0.1.0'
+__version__ = '0.1.5'
 
 from .ratios import BinaryClassificationRatios
 

src/binary_classification_ratios/cli/cmd_line.py

@@ -1,7 +1,7 @@
 """."""
 
 from argparse import ArgumentParser
-from typing import Sequence
+from typing import Sequence, Union
 
 
 PROG = 'binary-classification-ratios'
@@ -17,7 +17,7 @@ def __init__(self) -> None:
         self.fn: int = 0
 
 
-def get_cmd_line(args: Sequence[str] | None = None) -> CmdLine:
+def get_cmd_line(args: Union[Sequence[str], None] = None) -> CmdLine:
     """."""
     parser = ArgumentParser(PROG, f'{PROG} [OPTIONS]')
     parser.add_argument('-tp', type=int, default=0, help='Number of true positives.')

src/binary_classification_ratios/cli/main.py

@@ -1,13 +1,13 @@
 """."""
 
-from typing import Sequence
+from typing import Sequence, Union
 
 from binary_classification_ratios import BinaryClassificationRatios
 
 from .cmd_line import get_cmd_line
 
 
-def run(args: Sequence[str] | None = None) -> float:
+def run(args: Union[Sequence[str], None] = None) -> float:
     """."""
     cli = get_cmd_line(args)
     bcr = BinaryClassificationRatios(tp=cli.tp, tn=cli.tn, fp=cli.fp, fn=cli.fn)