add unit tests

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