README

A high-performance Laravel package for importing and exporting large datasets with cloud storage support, automatic chunking, queue processing, and memory-efficient generators.

Built on top of OpenSpout for maximum performance and minimal memory usage.

🌟 Features

• ⚡ High Performance: Process millions of rows with minimal memory usage
• ☁️ Cloud Storage: Native support for AWS S3, Google Cloud Storage, Azure, and more
• 🔄 Auto Chunking: Automatically splits large files into smaller chunks
• 📋 Queue Support: Background processing with Laravel Queues
• 🧠 Memory Efficient: Uses PHP generators to handle large datasets
• 📁 Multiple Formats: Excel (XLSX), CSV, ODS support
• ✅ Data Validation: Built-in validation with Laravel's validator
• 🎯 Laravel Integration: Seamless integration with Laravel ecosystem
• 🧪 Well Tested: Comprehensive test suite with performance benchmarks

📋 Requirements

-- OpenSpout 4.0+

🐳 Docker

Use Docker para rodar a suíte de testes em um ambiente PHP 8.3 isolado:

# Build da imagem
docker build -t data-processor-tests .

# Run os testes (usa o código já copiado na imagem, sem volume mount)
docker run --rm data-processor-tests

📦 Installation

You can install the package via composer: bash composer require wesleydeveloper/data-processor

Publish the config file: bash php artisan vendor:publish --tag="data-processor-config"

🚀 Quick Start

Import Data

Create an import class:

<?php

namespace App\Imports;

use Wesleydeveloper\DataProcessor\Contracts\Importable;
use Wesleydeveloper\DataProcessor\Contracts\ShouldQueue;
use Wesleydeveloper\DataProcessor\Contracts\WithChunking;
use Illuminate\Support\Facades\DB;

class UsersImport implements Importable, ShouldQueue, WithChunking
{
    public function rules(): array
    {
        return [
            'name' => 'required|string|max:255',
            'email' => 'required|email|unique:users,email',
            'phone' => 'nullable|string'
        ];
    }

    public function map(array $row): array
    {
        return [
            'name' => $row[0],
            'email' => $row[1],
            'phone' => $row[2] ?? null,
            'created_at' => now(),
            'updated_at' => now()
        ];
    }

    public function process(array $data): void
    {
        DB::table('users')->insert($data);
    }

    public function chunkSize(): int
    {
        return 1000;
    }

    // Queue configuration
    public function onQueue(): ?string
    {
        return 'imports';
    }

    public function timeout(): int
    {
        return 300;
    }

    public function memory(): int
    {
        return 512;
    }

    // Chunking configuration
    public function maxFileSize(): int
    {
        return 50 * 1024 * 1024; // 50MB
    }

    public function chunkRows(): int
    {
        return 10000;
    }
}

Process the import:

use Wesleydeveloper\DataProcessor\Facades\DataProcessor;
use App\Imports\UsersImport;

DataProcessor::import(new UsersImport(), 'users-import.xlsx');

Export Data

Create an export class:

<?php

namespace App\Exports;

use Wesleydeveloper\DataProcessor\Contracts\Exportable;
use App\Models\User;
use Generator;

class UsersExport implements Exportable
{
    public function query(): Generator
    {
        User::chunk(1000, function ($users) {
            foreach ($users as $user) {
                yield $user;
            }
        });
    }

    public function headings(): array
    {
        return ['ID', 'Name', 'Email', 'Created At'];
    }

    public function map($user): array
    {
        return [
            $user->id,
            $user->name,
            $user->email,
            $user->created_at->format('Y-m-d H:i:s')
        ];
    }

    public function chunkSize(): int
    {
        return 1000;
    }
}

Process the export:

use Wesleydeveloper\DataProcessor\Facades\DataProcessor;
use App\Exports\UsersExport;

DataProcessor::export(new UsersExport(), 'users-export.xlsx');