All examples below use the thread-safe, static Jds.TestingUtils.Randomization.Randomizer.Shared instance of IRandomizationSource, which generates random values using System.Random.Shared. This IRandomizationSource is advised for most tests.
If a specific set of random-seeming data is needed, consider creating a Jds.TestingUtils.Randomization.DeterministicRandomizationSource. It uses provided IEnumerable<> sources to supply values when requested.
Add Jds.TestingUtils.Randomization NuGet Package and Add using
Add Jds.TestingUtils.Randomization NuGet package to the test project.
Add the extensions to your test files with the following using statement:
using Jds.TestingUtils.Randomization;
All examples below assume the following additionalusing statements:
using System;
using System.Collections.Generic;
using System.Linq;
Generate Pseudo-random Numbers
IRandomizationSource.Boolean()
Gets a pseudo-random bool.
IRandomizationSource.Byte()
Gets a pseudo-random byte, greater than or equal to byte.MinValue, and less than byte.MaxValue.
Gets a pseudo-random byte, greater than or equal to minInclusive, and less than maxExclusive.
IRandomizationSource.Double()
Gets a pseudo-random double, using IRandomizationSource.NextDouble. The value should be greater than or equal to 0.0, and less than 1.0.
IRandomizationSource.Float()
Gets a pseudo-random float, using IRandomizationSource.NextFloat. The value should be greater than or equal to 0.0, and less than 1.0.
IRandomizationSource.Int()
Gets a pseudo-random int, using IRandomizationSource.NextIntInRange. The value should be greater than or equal to int.MinValue, and less than int.MaxValue.
IRandomizationSource.IntInRange(int minInclusive, int maxExclusive)
Gets a pseudo-random int, using IRandomizationSource.NextIntInRange. The value should be greater than or equal to minInclusive, and less than maxExclusive.
IRandomizationSource.IntNegative()
Gets a pseudo-random int, using IRandomizationSource.NextIntInRange. The value should be greater than or equal to int.MinValue, and less than 0.
IRandomizationSource.IntPositive()
Gets a pseudo-random int, using IRandomizationSource.NextIntInRange. The value should be greater than or equal to 0, and less than int.MaxValue.
IRandomizationSource.Long()
Gets a pseudo-random long, using IRandomizationSource.NextLongInRange. The value should be greater than or equal to long.MinValue, and less than long.MaxValue.
IRandomizationSource.LongInRange(long minInclusive, long maxExclusive)
Gets a pseudo-random long, using IRandomizationSource.NextLongInRange. The value should be greater than or equal to minInclusive, and less than maxExclusive.
IRandomizationSource.LongNegative()
Gets a pseudo-random long, using IRandomizationSource.NextLongInRange. The value should be greater than or equal to long.MinValue, and less than 0.
IRandomizationSource.LongPositive()
Gets a pseudo-random long, using IRandomizationSource.NextLongInRange. The value should be greater than or equal to 0, and less than long.MaxValue.
Generate a Random Number of Generated Items
IRandomizationSource.Enumerable<T>(Func<T> factory, int inclusiveMinCount, int exclusiveMaxCount)
IRandomizationSource.Enumerable<T>(Func<int, T> factory, int inclusiveMinCount, int exclusiveMaxCount)
Creates an IEnumerable<T> of a randomly-generated length using values provided by a factory method.
Example: Randomizer.Shared.Enumerable(Guid.NewGuid, 3, 7) - which would generate a sequence of 3 to 6Guid values.
Select a Random Item or Enumeration Value
IRandomizationSource.RandomEnumValue<TEnum>()
Selects a pseudo-random value from the enum of type specified (TEnum).
Generates a pseudo-random string of length characters, using provided chars. Random selections from chars are concatenated until reaching length characters.
Generates a pseudo-random string of length characters, using provided strings. Random selections from strings are concatenated until reaching length characters. The result is truncated to length characters.
Generates a pseudo-random string of length characters using ASCII Latin characters. Uses a - z by default. If uppercase, uses A - Z. If alphanumeric, also includes 0 - 9 with either casing.
Generate a Mail Address
IRandomizationSource.MailAddress()
IRandomizationSource.MailAddress(int length)
Generates a pseudo-random System.Net.Mail.MailAddress. The generated System.Net.Mail.MailAddress.User will be a dot-atom form of local-part (see RFC-2822 section 3.4.1). The generated System.Net.Mail.MailAddress.Host will be a domain (see RFC-1035 section 2.3.1).
IRandomizationSource.RandomUrl(int hostLength, int pathLength = 0, int queryLength = 0, int fragmentLength = 0, string scheme = "https", int? port = null)
Generates a pseudo-random string URL according to RFC-3986 URI syntax. The host segment is generated using IRandomizationSource.DomainName(int length).
Generate a Sequence of Items from a Markov Chain Model
IRandomizationSource.CreateMarkovGenerator(IReadOnlyCollection<IReadOnlyList<T>> sources, int chainLength = 1) where T : notnull, IEquatable<T>
Generates a Func<int, IReadOnlyList<T>> which accepts an int maxLength and uses a Markov Chain model, derived from sources, to generate sequences of T of up to length maxLength.
The chainLength determines how many T are grouped to determine Markov Chain probability.
IRandomizationSource.CreateMarkovGenerator(IEnumerable<string> sources, int chainLength = 1)
Generates a Func<int, string> which accepts an int maxLength and uses a Markov Chain model, derived from sources, to generate strings of up to length maxLength.
The chainLength determines how many characters in each input string are grouped to determine Markov Chain probability.
Example uses: create a random word or name generator using a list of example words or names.
IRandomizationSource.GenerateRandomMarkov<T>(IReadOnlyCollection<IReadOnlyList<T>> sources, int? maxLength = null, int chainLength = 1)
Generates a IReadOnlyList<T> based upon a Markov Chain model, derived from sources.
The chainLength determines how many items in each input IReadOnlyList<T> are grouped to determine Markov Chain probability.
Use IRandomizationSource.CreateMarkovGenerator() (above), instead of this function, unless only a single value is needed.
The resources needed to generate the Markov Chain model are non-trivial. This function creates a new model each time it is executed, consuming both computational and memory resources.
IRandomizationSource.GenerateRandomMarkov(IEnumerable<string> sources, int? maxLength = null, int chainLength = 1)
Generates a string based upon a Markov Chain model, derived from sources..
The chainLength determines how many characters in each input string are grouped to determine Markov Chain probability.
Use IRandomizationSource.CreateMarkovGenerator() (above), instead of this function, unless only a single value is needed.
The resources needed to generate the Markov Chain model are non-trivial. This function creates a new model each time it is executed, consuming both computational and memory resources.
Example uses: create a random word or name generator using a list of example words or names.
Generate a Word, Sentence, or Paragraph (Lorem Ipsum)
The Lorem Ipsum random generators create Latin-like words, sentences, and paragraphs. They use Markov Chain models trained on multiple Latin sources: the traditional Lorem Ipsum excerpts of Cicero's De Finibus Bonorum et Malorum, and excerpts of René Descartes's Meditationes de Prima Philosophia.
IRandomizationSource.LoremIpsumParagraph((int WordCount, int MaxWordLength) paragraphParameters)
Generates a paragraph string of paragraphParameters.WordCount words, broken into a random number of sentences. Each word in the paragraph is no more than paragraphParameters.MaxWordLength characters.
IRandomizationSource.LoremIpsumSentence((int WordCount, int MaxWordLength) sentenceParameters)
Generates a sentence string of sentenceParameters.WordCount words, each word no more than sentenceParameters.MaxWordLength characters. Sentences always begin with a capital letter and end with a period (.).
IRandomizationSource.DemographicsBirthDateTime((int MinAgeInYears, int MaxAgeInYearsExclusive) ageRange, DateTime? relativeTo = null)
Generates a date of birth DateTime within the ageRange specified, relative to relativeTo. If not provided, ageRange defaults to (MinAgeInYears: 18, MaxAgeInYearsExclusive: 96). If not provided, relativeTo defaults to DateTime.UtcNow.
Generates a forename string of no more than maxLength characters. Generated names have an initial capital letter and all subsequent characters are lowercase.
Generates a surname string of no more than maxLength characters. Generated names have an initial capital letter and all subsequent characters are lowercase.
Create a Custom Domain-Specific Language to Generate Complex or Custom Types
This library does not provide a domain-specific language. However, by creating your own static methods extending IStatefulRandomizationSource<TState> (where TState should be your generator options), you can easily construct a domain-specific language to generate complex or custom types.
creating a randomization state object (to provide configuration)
creating a domain value object (the thing we want to generate)
creating a domain-specific language (a static method extending IStatefulRandomizationSource<TState> which used the configuration and generated the value object)
creating unit tests which use the domain-specific language
This functionality was already possible by extending IRandomizationSource with methods accepting parameters. However, IStatefulRandomizationSource<TState> provides greater flexibility. By embedding state object types into your extension methods, you can simplify verbose generator method signatures.
The IStatefulRandomizationSource<TState> extends IRandomizationSource with a public TState State { get; } property.
Construction
Use Randomizer.WithState() static methods to create a new stateful randomizer based upon an initial state value.
Use the .WithState(TState initialState) extension method on IRandomizationSource to create a derived stateful randomizer using that randomization source instance.
Modifying State
In some scenarios, you may want to modify the existing randomization source state (e.g., when designing a "builder" interface). This is handled using some monadic methods.
It is intended that the state values used in a randomization source are immutable. When the state needs to change, the following monadic methods allow you to derive a new IStatefulRandomizationSource<TState> using the current state value.
Use Bind to replace the stateful randomization source with a new stateful randomization source derived from current state. This is an uncommon IStatefulRandomizationSource operation, normally only used when swapping the underlying IRandomizationSource.
Use Map to replace the state contained within the stateful randomization source with a new state (which may be of the same type or another). This is the most common state operation.
