goTableViewTable Viewer for Go

Zero dependencies. Auto-inference. Fluent API. Lightning fast.

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🚀

Zero Dependencies

Uses Windows API directly via syscall. No external dependencies except golang.org/x/sys/windows.

📊

Auto-Inference

Automatically extracts columns from structs. No manual configuration needed.

🔄

Fluent API

Chainable methods for clean, readable code. Build tables with ease.

📄

Pagination Built-in

Handle 100K+ rows efficiently with built-in pagination support.

🔍

Smart Search

Filter data in real-time. Search all columns or specific ones.

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Lightweight

Minimal execution overhead. Direct Windows API calls for best performance.

Quick Start

Install goTableView with a single command:

bash

go get github.com/mansoldof/goTableView

Create your first table in 30 seconds:

package main

import "github.com/mansoldof/goTableView"

func main() {
    // Simple table with string data
    gotableview.New("My First Table").
        Columns("Name", "Age", "City").
        Row("Alice", "30", "NYC").
        Row("Bob", "25", "LA").
        Show()
}

Why goTableView?

Perfect for Beginners

goTableView is designed with simplicity in mind. Whether you're new to Go or just need a quick way to visualize data, our API is intuitive and easy to learn.

// From structs - automatic column detection
type Person struct {
    Name   string
    Age    int
    Salary float64
}

people := []Person{
    {"Alice", 30, 75000},
    {"Bob", 25, 60000},
}

gotableview.FromStructs("Employees", people).Show()

Built for Windows

Native Windows ListView control provides familiar interface and excellent performance. No web browsers, no terminal limitations.

Data Pipeline Integration

Perfect companion for plyGO data pipelines. plyGO is a lightweight, type-safe data manipulation library for Go inspired by dplyr.

bash

go get github.com/mansoldof/plyGO

package main

import "github.com/mansoldof/goTableView"
import "github.com/mansoldof/plyGO"

func main() {

type Employee struct {
    Name       string
    Age        int
    Department string
    Salary     float64
}

employees := []Employee{
    {"Alice", 40, "Engineering", 75000},
    {"Bob", 25, "Marketing", 60000},
    {"Charlie", 35, "Engineering", 90000},
    {"Diana", 28, "Sales", 70000},
}

gotableview.FromStructs("Initial dataset", employees).Show()

result := plygo.From(employees).
    Where("Age").GreaterThan(30).
    OrderBy("Salary").Desc().
    Collect()

gotableview.FromStructs("Filtered dataset", result).Show()


}