FluentRandomPicker 3.5.1

Fluent Random Picker

Fluent Random Picker is a user-friendly, but also performant .NET library that simplifies random value selection / picking. It allows you to specify probabilities and weights for each value, making it easy to handle complex randomization tasks.

• Fluent Random Picker
  • Compatibility
  • Getting started
  • Examples
    • The easiest example
    • Specifying percentages
    • Specifying weights
    • Picking multiple values
    • Picking distinct values
    • Using external types with weight/percentage information
    • Omitting percentages or weights
    • Specifying the returned type explicitly
  • Advanced
  • Migration to version 3

Compatibility

Fluent Random Picker targets .Net Standard 2.0 and is therefore compatible with the following target frameworks:

• ✔️ .Net 5, 6, 7, 8
• ✔️ .Net Core 2.X, 3.X
• ✔️ .Net Standard 2.0, 2.1
• ✔️ .Net Framework 4.7.2, 4.8

Getting started

Install the nuget package (https://www.nuget.org/packages/FluentRandomPicker/)

Add the using directive:

using FluentRandomPicker;

To get started, use the Out.Of() syntax as shown in the examples below:

Examples

The easiest example

var randomNumber = Out.Of().Value(5).AndValue(6).PickOne();
// randomNumber is 5 or 6 with equal probability.

Specifying percentages

var randomChar = Out.Of()
                  .Value('a').WithPercentage(70)
                  .AndValue('b').WithPercentage(30)
                  .PickOne();
// randomChar is 'a' with a probability of 70 % and 'b' with a probability of 30 %.

Specifying weights

var randomString = Out.Of()
                  .Value("hello").WithWeight(2)
                  .AndValue("world").WithWeight(3)
                  .PickOne();
// randomString is "hello" or "world", but the probability for "world" is 1.5 times as high.

Specifying multiple values

var randomChar = Out.Of().Values(new List<char> { 'a', 'b' })
                  .WithPercentages(new List<int> { 70, 30 })
                  .PickOne();
// randomChar is 'a' with a probability of 70 % and 'b' with a probability of 30 %.

var randomChar = Out.Of().Values(new HashSet<string> { "hello", "world" })
                  .WithWeights(new List<int> { 2, 3 })
                  .PickOne();
// randomString is "hello" or "world", but the probability for "world" is 1.5 times as high.

Picking multiple values

var randomInts = Out.Of()
                  .Value(1).WithPercentage(70)
                  .AndValue(10).WithPercentage(15)
                  .AndValue(100).WithPercentage(10)
                  .AndValue(1000).WithPercentage(5)
                  .Pick(5);
// randomInts can be [1, 1, 1, 1, 1] with a higher probability or [1, 1, 100, 10, 1]
// or even [1000, 1000, 1000, 1000, 1000] with a very small probability.

Picking distinct values

var randomInts = Out.Of()
                  .Values(new List<int> { 1, 10, 100, 1000 })
                  .WithPercentages(70, 15, 10, 5)
                  .PickDistinct(2);
// randomInts can be [1, 10], [1, 100], ..., [1000, 100], but not [1, 1], [10, 10], ...

Using external types with weight/percentage information

class Item {
    public int Rarity { get; set; }
    public string Name { get; set; }
}

var items = new Item[]
{
    new Item { Name = "Stone", Rarity = 5 }, // common
    new Item { Name = "Silver helmet", Rarity = 2 }, // uncommon
    new Item { Name = "Gold sword", Rarity = 1 }, // rare
};

var itemName = Out.Of()
                  .PrioritizedElements(items)
                  .WithValueSelector(x => x.Name)
                  .AndWeightSelector(x => x.Rarity)
                  .PickOne();

// itemName is "Stone" in 5/8 of the cases, "Silver helmet" in 2/8 of the cases and "Gold sword" in 1/8 of the cases.
// If no value selector is specified, the whole item object will be returned instead of only its name.

Omitting percentages or weights

var randomChar = Out.Of()
                  .Value('a').WithPercentage(80)
                  .AndValue('b') // no percentage
                  .AndValue('c') // no percentage
                  .PickOne();
// The missing percentages to reach 100% are equally distributed on the values without specified percentages.
// Attention! The missing percentages to reach 100% must be divisible without remainder through the number of values without percentages.
// randomChar is 'a' with a probability of 80% or 'b' or 'c' with a probability of each 10%.

var randomString = Out.Of()
                  .Value("hello").WithWeight(4)
                  .AndValue("world") // no weight
                  .PickOne();
// The default weight is 1.
// randomString is "hello" with a probability of 80% (4 of 5) and "world" with a probability of 20% (1 of 5).

Specifying the returned type explicitly

var operation = Out.Of<Func<long, long>>()
                .Value(i => i + 2)
                .AndValue(i => i * 2)
                .AndValue(i => (long)Math.Pow(i, 2))
                .AndValue(i => (long)Math.Pow(i, i))
                .PickOne();

var result = operation(10);
// result equals 10 + 2 or 10 * 2 or 10^2 or 10^10. 

Advanced

Please see README-Advanced.md for more advanced topics like:

• specifying a seed
• using a secure RNG
• using a custom RNG

Migration to version 3

The namespace was changed to match coding conventions. Please replace:

using Fluent_Random_Picker;

with

using FluentRandomPicker;

Some method parameter identifiers do also have changed to match the coding conventions of Microsoft.