Efficiently Reading CSV Files into Object Lists in C#

In software development, reading data from CSV files into object-oriented structures is a common task. This article addresses a specific scenario where a CSV file containing financial data with various types such as DateTime and decimal needs to be parsed into a list of custom objects in C#.

Problem Description

The user has a CSV file with a header line and data rows. Each row includes fields for date, open, high, low, close, volume, and adjusted close. The goal is to skip the header and read each data line into a DailyValues object, which is then added to a list.

Solution Approach

The optimal solution, as provided in the accepted answer, leverages C#'s file I/O capabilities and LINQ to achieve this efficiently. The core idea is to use File.ReadAllLines to read all lines, skip the header with Skip(1), and then transform each line using a static method FromCsv.

Code Implementation

using System;
using System.Collections.Generic;
using System.Linq;
using System.IO;

namespace CsvDemo
{
    class Program
    {
        static void Main(string[] args)
        {
            List<DailyValues> values = File.ReadAllLines("C:\\Users\\Josh\\Sample.csv")
                                           .Skip(1)
                                           .Select(v => DailyValues.FromCsv(v))
                                           .ToList();
        }
    }

    class DailyValues
    {
        DateTime Date;
        decimal Open;
        decimal High;
        decimal Low;
        decimal Close;
        decimal Volume;
        decimal AdjClose;

        public static DailyValues FromCsv(string csvLine)
        {
            string[] values = csvLine.Split(',');
            DailyValues dailyValues = new DailyValues();
            dailyValues.Date = Convert.ToDateTime(values[0]);
            dailyValues.Open = Convert.ToDecimal(values[1]);
            dailyValues.High = Convert.ToDecimal(values[2]);
            dailyValues.Low = Convert.ToDecimal(values[3]);
            dailyValues.Close = Convert.ToDecimal(values[4]);
            dailyValues.Volume = Convert.ToDecimal(values[5]);
            dailyValues.AdjClose = Convert.ToDecimal(values[6]);
            return dailyValues;
        }
    }
}

In this code, File.ReadAllLines reads the entire file into a string array. The Skip(1) method ignores the first line (the header). Then, Select applies the FromCsv method to each remaining line, which splits the CSV string and converts each part to the appropriate type using Convert.ToDateTime and Convert.ToDecimal. Finally, ToList converts the IEnumerable<DailyValues> to a List<DailyValues>.

Additional Considerations

While this approach is straightforward, it lacks error handling. In production code, it is advisable to use TryParse methods to handle invalid data gracefully. For example, instead of Convert.ToDateTime, use DateTime.TryParse to avoid exceptions. Additionally, for large files, streaming approaches with StreamReader might be more memory-efficient than reading all lines at once.

Conclusion

This method provides an efficient and readable way to parse CSV files into object lists in C#. By combining file I/O with LINQ, developers can achieve concise code that is easy to maintain and extend. For robust applications, incorporating error handling and considering performance optimizations is recommended.