🖱️ mimic

Human-like mouse movement generation for Go.

Generate natural, curved cursor trajectories using pluggable algorithms instead of robotic straight lines.

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Overview

mimic is a Go library for generating human-like mouse movements. Real users never move the cursor in a perfectly straight line at constant speed — they curve, drift, accelerate, and hesitate. mimic reproduces that behavior through configurable, algorithm-driven path generation.

Each generated movement is a sequence of timestamped points, making it suitable for automation, UI testing, and simulating realistic human input.

Features

• Multiple algorithms — Bézier curves and Perlin noise, selectable at runtime.
• Configurable realism — tune noise, speed, control points, and resolution.
• Per-point timing — every point carries a time.Duration for accurate playback.
• Simple interface — one Mimic interface, one method: GenerateMovement.
• Zero runtime dependencies — visualization tooling is confined to tests only.

Installation

go get github.com/combo23/mimic

Requires Go 1.23 or later.

Quick Start

package main

import (
	"fmt"

	"github.com/combo23/mimic"
	"github.com/combo23/mimic/models"
)

func main() {
	opts := models.MovementOptions{
		StartPoint:    models.Point{X: 0, Y: 0},
		EndPoint:      models.Point{X: 1920, Y: 1080},
		NoiseLevel:    1,
		Resolution:    models.Point{X: 1920, Y: 1080},
		ControlPoints: 20,
		Speed:         1000,
	}

	m := mimic.NewMimic(mimic.BezierAlgorithm)
	movement := m.GenerateMovement(opts)

	for _, p := range movement.Points {
		fmt.Println(p.String()) // (x, y) took <duration>
	}
}

API

Selecting an algorithm

m := mimic.NewMimic(mimic.BezierAlgorithm) // or mimic.PerlinAlgorithm

Algorithm	Constant	Description
Bézier curve	mimic.BezierAlgorithm	Smooth, intentional paths via control points.
Perlin noise	mimic.PerlinAlgorithm	Organic, gently wandering paths.

MovementOptions

Field	Type	Description
StartPoint	models.Point	Starting coordinates.
EndPoint	models.Point	Target coordinates.
NoiseLevel	float64	Amount of randomness (0.0–1.0).
Resolution	models.Point	Screen resolution (width × height).
ControlPoints	int	Number of control points for the Bézier curve (min 2).
Speed	float64	Movement speed in pixels per second.

Return value

GenerateMovement returns a *models.Movement:

type Movement struct {
	Points        []Point // the generated path, each with X, Y, and Timing
	ControlPoints []Point // control points used to shape the path
}

Supported Algorithms

Bézier curve

Produces smooth, deliberate trajectories shaped by a configurable number of control points.

Perlin noise

Produces organic, naturally wandering paths driven by gradient noise.

Testing

go test -race ./...

The tests package also renders movement visualizations (the images above) using gonum/plot.

Contributing

Contributions are welcome! Please open an issue for feature requests and bug reports, or submit a pull request.

License

Released under the MIT License.