LS.FileReader

A lightweight C# utility to read CSV, Excel (XLSX), and JSON files into strongly-typed models using attribute-based mapping and optional streaming support.

• ✅ Supports .csv, .xlsx, .json
• ✅ Attribute-based property mapping
• ✅ Read<T>() for small files (sync, memory-based)
• ✅ ReadAsync<T>() for large files (async stream)
• ✅ Built with clean architecture & extensibility
• ✨ Created with AI-assisted engineering (OpenAI ChatGPT)
• ⚙️ Powered by ExcelDataReader

---

🔧 Installation

dotnet add package LS.FileReader

---

🚀 Quick Start

1. Define your model with HeaderColumnAttribute

using LS.FileReader.Attributes;

public class PersonDto
{
    [HeaderColumn("Name", "FullName")]
    public string Name { get; set; }

    [HeaderColumn("Age")]
    public int Age { get; set; }

    [HeaderColumn("DOB")]
    public DateTime BirthDate { get; set; }
}

---

2. Use ILsFileReader.Read<T>() to fully load and parse the file

var reader = new LsFileReader();

var result = reader.Read<PersonDto>(formFile); // Supports .csv, .xlsx, .json

foreach (var person in result.Data)
{
    Console.WriteLine($"{person.Name}, {person.Age}");
}

foreach (var error in result.ErrorRows)
{
    Console.WriteLine($"Row {error.RowIndex} failed: {error.Error}");
}

---

3. Use ReadAsync<T>() for large files (streaming)

await foreach (var row in reader.ReadAsync<PersonDto>(formFile))
{
    if (row.IsSuccess)
    {
        var person = row.Data;
        // Process person
        // Do something at here, add to db / signal r notify
    }
    else
    {
        Console.WriteLine($"Row {row.RowIndex} failed: {row.Error}");
    }
}

---

4. Use ReadAsync<T>() + FileEstimateHelper for large files (streaming) and batch process

var batch = new List<PersonDto>();
var batchSize = 100;
var lastNotifyTime = DateTime.UtcNow;
var estimatedTotalRows = 0;

await foreach (var row in reader.ReadAsync<PersonDto>(formFile))
{
    if (!row.IsSuccess)
    {
        Console.WriteLine($"Row {row.RowIndex} failed: {row.Error}");
        continue;
    }

    // Estimate total rows once (based on file size and column count)
    if (estimatedTotalRows == 0)
    {
        estimatedTotalRows = FileEstimateHelper.EstimateTotalRows(formFile, row.ColumnCount);
    }

    batch.Add(row.Data);

    if (batch.Count >= batchSize)
    {
        await db.SaveBatchAsync(batch); // Replace with your batch save logic
        batch.Clear();
    }

    // Notify progress every 250ms
    if ((DateTime.UtcNow - lastNotifyTime).TotalMilliseconds >= 250)
    {
        double percent = (double)row.RowIndex / estimatedTotalRows * 100;
        await notifier.SendProgressAsync(connectionId, percent);
        lastNotifyTime = DateTime.UtcNow;
    }
}

// Flush remaining rows
if (batch.Count > 0)
{
    await db.SaveBatchAsync(batch);
}

---

📂 Supported Formats

Format	Method	Notes
.csv	Read<T>(), ReadAsync<T>()	Header must match column/alias
.xlsx	Read<T>(), ReadAsync<T>()	First sheet is used by default
.json	Read<T>() only	Must be JSON array

---

📘 Notes

• All file reads are limited to 10MB to avoid memory spikes.
• Property names are matched case-insensitively to headers or aliases.
• Internally uses System.Text.Json for JSON and ExcelDataReader for Excel files.

---

👤 Author

• Laoseng (developer)
• OpenAI ChatGPT (AI-assisted architecture & implementation)

---

📝 License

MIT License
Includes Excel parsing powered by ExcelDataReader (MIT)