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A Golang library with a collection of diverse and high-performance algorithms for various problem-solving needs.

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# algo: A Collection of High-Performance Algorithms

[![Go Reference](https://pkg.go.dev/badge/github.com/Ja7ad/algo.svg)](https://pkg.go.dev/github.com/Ja7ad/algo)
[![codecov](https://codecov.io/gh/Ja7ad/algo/graph/badge.svg?token=9fLKrkUviU)](https://codecov.io/gh/Ja7ad/algo)
[![Go Report Card](https://goreportcard.com/badge/github.com/Ja7ad/algo)](https://goreportcard.com/report/github.com/Ja7ad/algo)

**`algo`** is a Golang library featuring a variety of **efficient** and **well-optimized** algorithms designed for diverse **problem-solving needs**.

The purpose of this package is to implement specific algorithms in a simplified manner based on formulaic documentation available on Wikipedia or other sources. These algorithms 
been validated in terms of functionality and testing.

- [📚 Available Algorithms](#-available-algorithms)
- [🚀 Installation >= go 1.19](#-installation--go-119)
- [✅ Usage Example](#-usage-example)
- [📌 Contribution](#-contribution)
- [📜 License](#-license)

## 📚 Available Algorithms

| Algorithm                                        | Description |
|--------------------------------------------------|-------------|
| [Random Weighted Selection](./rws/README.md)     | Selects items randomly based on assigned weights. Useful in load balancing, gaming, and AI. |
| [Reservoir Sampling Algorithm R](./rs/README.md) | Basic reservoir sampling, replaces elements with probability `k/i`. Efficient for uniform random sampling. |
| [Reservoir Sampling Algorithm L](./rs/README.md) | Optimized reservoir sampling for large `N`, reduces unnecessary replacements using skipping. |
| [Weighted Reservoir Sampling](./rs/README.md)    | Selects items with probability proportional to their weights using a heap-based approach. Used in recommendation systems and A/B testing. |
| [Random Sort Reservoir Sampling](./rs/README.md) | Uses a min-heap and random priorities to maintain the top `k` elements in a streaming dataset. |
| [Consistent Hashing](./ch/README.md)             | Used by distributed systems (CDNs, databases) to evenly distribute requests across servers. |

## 🚀 Installation >= go 1.19

```shell
go get -u github.com/Ja7ad/algo
```

## ✅ Usage Example

Here’s how you can use the **Random Weighted Selection** algorithm:

```go
package main

import (
	"fmt"
	"log"
	"github.com/Ja7ad/algo/rws"
)

func main() {
	// Define items with weights
	weightedItems := map[int]string{
		3: "Apple",
		1: "Banana",
		6: "Cherry",
	}

// Create a selector
	selector, err := rws.NewWeightedSelector(weightedItems)
	if err != nil {
		log.Fatal(err)
	}

// Pick a random item
	selectedItem, _ := selector.Pick()
	fmt.Println("Selected:", selectedItem)
}
```

For more details, check the [Random Weighted Selection documentation](./rws/README.md).

## 📌 Contribution

We welcome contributions! Feel free to submit pull requests, open issues, or suggest new algorithms.

## 📜 License

This project is licensed under the **MIT License**.

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