public void Register()
{
var anon = new AnonymousData();
anon.Register <IModel>(_ => new Model());
var result = (IModel)anon.Any(typeof(IModel));
Assert.NotNull(result);
}
public AnonymousDataContext(AnonymousData factory, Type resultType)
{
Argument.NotNull(factory, nameof(factory));
Argument.NotNull(resultType, nameof(resultType));
this.factory = factory;
ResultType = resultType;
current = this.factory.customizations.Count;
}
public void AnyString()
{
var anon = new AnonymousData();
var result = anon.AnyString();
Assert.NotNull(result);
Assert.True(result.All(c => char.IsLetter(c)));
}
public void RegisterDefault()
{
var anon = new AnonymousData();
// Registration happens in the class fixture AnonymousDataTestsFixture.
var result = anon.Any <GloballyRegisteredModel>();
Assert.Equal("xyzzy", result.Value);
}
public void FreezeValue()
{
var anon = new AnonymousData();
anon.Freeze(42);
var result = anon.Any <int>();
Assert.Equal(42, result);
}
public void Register_DerivedPropertyExpression()
{
var anon = new AnonymousData();
var value = anon.Any <string>();
anon.Register((DerivedModel m) => m.Unset, _ => value);
var result = anon.Any <DerivedModel>(PopulateOption.Deep);
Assert.Same(value, result.Unset);
}
public void TestAnyEnumerable_TypeMinMaxLength()
{
var anon = new AnonymousData();
var result = anon.AnyEnumerable(typeof(int), 4, 10);
var count = result.OfType <int>().Count();
Assert.NotNull(result);
Assert.True(count >= 4 && count <= 10);
}
public void Any_Predicate_ShouldEnsurePredicate()
{
var anon = new AnonymousData();
bool Predicate(int i) => (i % 2) == 0;
var result = anon.Any <int>(Predicate);
Assert.True(Predicate(result));
}
public void Register_PropertyExpression()
{
var anon = new AnonymousData();
var model = anon.Any <Model>();
anon.Register((DeepModel m) => m.Model, a => model);
var result = anon.Any <DeepModel>(PopulateOption.Deep);
Assert.Same(model, result.Model);
}
public void TestAnyEnumerableT_MinMaxLength()
{
var anon = new AnonymousData();
var result = anon.AnyEnumerable <int>(4, 10);
var count = result.Count();
Assert.NotNull(result);
Assert.True(count >= 4 && count <= 10);
}
public void RegisterDefault_PropertyExpression()
{
var anon = new AnonymousData();
var model = new AnonymousDataTestsFixture.GloballyRegisteredModel();
// Registration happens in the class fixture AnonymousDataTestsFixture.
anon.Populate(model);
Assert.Equal("xyzzy", model.Value);
}
public void Any_PopulateShallow_ShouldPopulateFirstLevel()
{
var anon = new AnonymousData();
var result = anon.Any <DeepModel>(PopulateOption.Shallow);
Assert.NotNull(result);
Assert.NotNull(result.Model);
Assert.Equal(result.Model.Value, nameof(Model));
}
public void Customize()
{
var anon = new AnonymousData();
anon.Customize(new Customization());
var result = (IModel)anon.Any(typeof(IModel));
Assert.NotNull(result);
}
public void AnyString_MinMaxLengthDistribution()
{
var anon = new AnonymousData();
var result = anon.AnyString(4, 10, Distribution.Uniform);
Assert.NotNull(result);
Assert.True(result.All(c => char.IsLetter(c)));
Assert.True(result.Length >= 4 && result.Length <= 10);
}
public void AnyAlphaChar()
{
var anon = new AnonymousData();
var classifier = new Classifier <char>();
classifier.AddClassification("Alpha", d => char.IsLetter(d));
classifier.Classify(() => anon.AnyAlphaChar());
Assert.True(classifier["Alpha"] == 1.0);
}
public void SetMinMaxItemsConstrainsSize()
{
var anon = new AnonymousData();
anon.SetMinimumItemCount(2);
anon.SetMaximumItemCount(2);
var result = anon.Any <List <int> >();
Assert.Equal(2, result.Count);
}
public void AnyLatinSupplementChar()
{
var anon = new AnonymousData();
var classifier = new Classifier <char>();
classifier.AddClassification("Alpha", d => d >= 0xa0 && d <= 0xff);
classifier.Classify(() => anon.AnyLatinSupplementChar());
Assert.True(classifier["Alpha"] == 1.0);
}
public void AnyPrintableChar()
{
var anon = new AnonymousData();
var classifier = new Classifier <char>();
classifier.AddClassification("Alpha", d => (d >= 0x20 && d <= 0x7f) || (d >= 0xa0 && d <= 0xff));
classifier.Classify(() => anon.AnyPrintableChar());
Assert.True(classifier["Alpha"] == 1.0);
}
public void AnyBasicLatinChar_Distribution()
{
var anon = new AnonymousData();
var classifier = new Classifier <char>();
classifier.AddClassification("Alpha", d => d >= 0x20 && d <= 0x7f);
classifier.Classify(() => anon.AnyBasicLatinChar(Distribution.Uniform));
Assert.True(classifier["Alpha"] == 1.0);
}
public void AnyAlphaNumericChar_Distribution()
{
var anon = new AnonymousData();
var classifier = new Classifier <char>();
classifier.AddClassification("Alpha", d => char.IsLetterOrDigit(d));
classifier.Classify(() => anon.AnyAlphaNumericChar(Distribution.Uniform));
Assert.True(classifier["Alpha"] == 1.0);
}
public void AnyFullName()
{
var anon = new AnonymousData();
// Do this a few times to cover all branches.
for (int i = 0; i < 50; ++i)
{
var name = anon.AnyFullName();
Assert.NotNull(name);
}
}
public void Any_PopulateDeepWithCollections_ShouldPopulateCollections()
{
var anon = new AnonymousData();
var result = anon.Any <DeepModelWithCollection>(PopulateOption.Deep);
Assert.NotNull(result);
Assert.NotEmpty(result.ReadOnlyNames);
Assert.NotEmpty(result.InitializedNames);
Assert.NotEmpty(result.UninitializedNames);
Assert.NotEmpty(result.Dictionary);
}
public void Any_Populate_ShouldPopulateFirstLevel()
{
var anon = new AnonymousData();
var result = anon.Any <DeepModel>();
anon.Populate(result);
Assert.NotNull(result);
Assert.NotNull(result.Model);
Assert.Equal(nameof(Model), result.Model.Value);
}
public void Any_Double()
{
var anon = new AnonymousData();
var classifier = new Classifier <double>();
classifier.AddClassification("GT", d => d > 0);
classifier.AddClassification("LT", d => d < 0);
classifier.Classify(() => (double)anon.Any(typeof(double)));
Assert.True(classifier["GT"] > 0.4);
Assert.True(classifier["LT"] > 0.4);
}
public void AnyChar()
{
var anon = new AnonymousData();
var classifier = new Classifier <char>();
classifier.AddClassification("GT", d => d > (char.MaxValue / 2));
classifier.AddClassification("LT", d => d < (char.MaxValue / 2));
classifier.Classify(() => anon.AnyChar());
Assert.True(classifier["GT"] > 0.4);
Assert.True(classifier["LT"] > 0.4);
}
public void AnyInt64()
{
var anon = new AnonymousData();
var classifier = new Classifier <long>();
classifier.AddClassification("GT", d => d > 0);
classifier.AddClassification("LT", d => d < 0);
classifier.Classify(() => anon.AnyInt64());
Assert.True(classifier["GT"] > 0.4);
Assert.True(classifier["LT"] > 0.4);
}
public void AnyDouble_MinMaxDistribution()
{
var anon = new AnonymousData();
var classifier = new Classifier <double>();
classifier.AddClassification("GT", d => d > 0);
classifier.AddClassification("LT", d => d < 0);
classifier.Classify(() => anon.AnyDouble(float.MinValue, float.MaxValue, Distribution.Uniform));
Assert.True(classifier["GT"] > 0.4);
Assert.True(classifier["LT"] > 0.4);
}
public void AnyDateTimeOffset()
{
var anon = new AnonymousData();
var classifier = new Classifier <DateTimeOffset>();
classifier.AddClassification("GT", d => d.Ticks > (DateTimeOffset.MaxValue.Ticks / 2));
classifier.AddClassification("LT", d => d.Ticks < (DateTimeOffset.MaxValue.Ticks / 2));
classifier.Classify(() => anon.AnyDateTimeOffset());
Assert.True(classifier["GT"] > 0.4);
Assert.True(classifier["LT"] > 0.4);
}
public void AnyInt16_MinMax()
{
var anon = new AnonymousData();
var classifier = new Classifier <short>();
classifier.AddClassification("GT", d => d > 0);
classifier.AddClassification("LT", d => d < 0);
classifier.Classify(() => anon.AnyInt16(short.MinValue, short.MaxValue));
Assert.True(classifier["GT"] > 0.4);
Assert.True(classifier["LT"] > 0.4);
}
public void AnyInt16_Distribution()
{
var anon = new AnonymousData();
var classifier = new Classifier <short>();
classifier.AddClassification("GT", d => d > 0);
classifier.AddClassification("LT", d => d < 0);
classifier.Classify(() => anon.AnyInt16(Distribution.Uniform));
Assert.True(classifier["GT"] > 0.4);
Assert.True(classifier["LT"] > 0.4);
}
