📝 Add StrEnum example for python 3.11+

docs/tutorial/parameter-types/enum.md

@@ -1,8 +1,18 @@
 To define a *CLI parameter* that can take a value from a predefined set of values you can use a standard Python <a href="https://docs.python.org/3/library/enum.html" class="external-link" target="_blank">`enum.Enum`</a>:
 
-```Python hl_lines="1  6 7 8 9  12 13"
-{!../docs_src/parameter_types/enum/tutorial001.py!}
-```
+
+=== "Python 3.11+"
+
+    ```Python hl_lines="1  6 7 8 9  12 13"
+    {!> ../docs_src/parameter_types/enum/tutorial001_str_enum.py!}
+    ```
+
+=== "Python 3.7+"
+
+    ```Python hl_lines="1  6 7 8 9  12 13"
+    {!> ../docs_src/parameter_types/enum/tutorial001.py!}
+    ```
+
 
 !!! tip
     Notice that the function parameter `network` will be an `Enum`, not a `str`.
@@ -51,6 +61,12 @@ Error: Invalid value for '--network': invalid choice: CONV. (choose from simple,
 
 You can make an `Enum` (choice) *CLI parameter* be case-insensitive with the `case_sensitive` parameter:
 
+=== "Python 3.11+"
+
+    ```Python hl_lines="15"
+    {!> ../docs_src/parameter_types/enum/tutorial002_str_enum.py!}
+    ```
+
 === "Python 3.7+"
 
     ```Python hl_lines="15"

docs_src/parameter_types/enum/tutorial001_str_enum.py

@@ -0,0 +1,17 @@
+from enum import StrEnum
+
+import typer
+
+
+class NeuralNetwork(StrEnum):
+    simple = "simple"
+    conv = "conv"
+    lstm = "lstm"
+
+
+def main(network: NeuralNetwork = NeuralNetwork.simple):
+    print(f"Training neural network of type: {network.value}")
+
+
+if __name__ == "__main__":
+    typer.run(main)

docs_src/parameter_types/enum/tutorial002_str_enum.py

@@ -0,0 +1,22 @@
+from enum import StrEnum
+
+import typer
+from typing_extensions import Annotated
+
+
+class NeuralNetwork(StrEnum):
+    simple = "simple"
+    conv = "conv"
+    lstm = "lstm"
+
+
+def main(
+    network: Annotated[
+        NeuralNetwork, typer.Option(case_sensitive=False)
+    ] = NeuralNetwork.simple,
+):
+    print(f"Training neural network of type: {network.value}")
+
+
+if __name__ == "__main__":
+    typer.run(main)

tests/test_tutorial/test_parameter_types/test_enum/test_tutorial001_str_enum.py

@@ -0,0 +1,53 @@
+import subprocess
+import sys
+
+import typer
+from typer.testing import CliRunner
+
+from docs_src.parameter_types.enum import tutorial001_str_enum as mod
+
+runner = CliRunner()
+
+app = typer.Typer()
+app.command()(mod.main)
+
+
+def test_help():
+    result = runner.invoke(app, ["--help"])
+    assert result.exit_code == 0
+    assert "--network" in result.output
+    assert "[simple|conv|lstm]" in result.output
+    assert "default: simple" in result.output
+
+
+def test_main():
+    result = runner.invoke(app, ["--network", "conv"])
+    assert result.exit_code == 0
+    assert "Training neural network of type: conv" in result.output
+
+
+def test_invalid_case():
+    result = runner.invoke(app, ["--network", "CONV"])
+    assert result.exit_code != 0
+    assert "Invalid value for '--network': 'CONV' is not one of" in result.output
+    assert "simple" in result.output
+    assert "conv" in result.output
+    assert "lstm" in result.output
+
+
+def test_invalid_other():
+    result = runner.invoke(app, ["--network", "capsule"])
+    assert result.exit_code != 0
+    assert "Invalid value for '--network': 'capsule' is not one of" in result.output
+    assert "simple" in result.output
+    assert "conv" in result.output
+    assert "lstm" in result.output
+
+
+def test_script():
+    result = subprocess.run(
+        [sys.executable, "-m", "coverage", "run", mod.__file__, "--help"],
+        capture_output=True,
+        encoding="utf-8",
+    )
+    assert "Usage" in result.stdout

tests/test_tutorial/test_parameter_types/test_enum/test_tutorial002_str_enum.py

@@ -0,0 +1,33 @@
+import subprocess
+import sys
+
+import typer
+from typer.testing import CliRunner
+
+from docs_src.parameter_types.enum import tutorial002_str_enum as mod
+
+runner = CliRunner()
+
+app = typer.Typer()
+app.command()(mod.main)
+
+
+def test_upper():
+    result = runner.invoke(app, ["--network", "CONV"])
+    assert result.exit_code == 0
+    assert "Training neural network of type: conv" in result.output
+
+
+def test_mix():
+    result = runner.invoke(app, ["--network", "LsTm"])
+    assert result.exit_code == 0
+    assert "Training neural network of type: lstm" in result.output
+
+
+def test_script():
+    result = subprocess.run(
+        [sys.executable, "-m", "coverage", "run", mod.__file__, "--help"],
+        capture_output=True,
+        encoding="utf-8",
+    )
+    assert "Usage" in result.stdout