There is no such method native to EPPlus unfortunately. Its a tough nut to crack since you would have to use reflections if you truly want it to be generic. And because of Excel storing all numbers and dates as double you have to deal with alot of unboxing and type checks.
This is something I have been working on. Its an extension method that will do it via Generics
. It works but only under limited testing so make sure you check it yourself. I cant guarantee it is the most optimized (yet) but it is pretty decent at his point. You would use it like this:
IEnumerable<TestObject> newcollection = worksheet.ConvertSheetToObjects<TestObject>();
The extension:
public static IEnumerable<T> ConvertSheetToObjects<T>(this ExcelWorksheet worksheet) where T:new()
{
//DateTime Conversion
var convertDateTime = new Func<double, DateTime>(excelDate =>
{
if (excelDate < 1)
throw new ArgumentException("Excel dates cannot be smaller than 0.");
var dateOfReference = new DateTime(1900, 1, 1);
if (excelDate > 60d)
excelDate = excelDate - 2;
else
excelDate = excelDate - 1;
return dateOfReference.AddDays(excelDate);
});
//Get the properties of T
var tprops = (new T())
.GetType()
.GetProperties()
.ToList();
//Cells only contains references to cells with actual data
var groups = worksheet.Cells
.GroupBy(cell => cell.Start.Row)
.ToList();
//Assume the second row represents column data types (big assumption!)
var types = groups
.Skip(1)
.First()
.Select(rcell => rcell.Value.GetType())
.ToList();
//Assume first row has the column names
var colnames = groups
.First()
.Select((hcell, idx) => new { Name = hcell.Value.ToString(), index = idx })
.Where(o => tprops.Select(p => p.Name).Contains(o.Name))
.ToList();
//Everything after the header is data
var rowvalues = groups
.Skip(1) //Exclude header
.Select(cg => cg.Select(c => c.Value).ToList());
//Create the collection container
var collection = rowvalues
.Select(row =>
{
var tnew = new T();
colnames.ForEach(colname =>
{
//This is the real wrinkle to using reflection - Excel stores all numbers as double including int
var val = row[colname.index];
var type = types[colname.index];
var prop = tprops.First(p => p.Name == colname.Name);
//If it is numeric it is a double since that is how excel stores all numbers
if (type == typeof (double))
{
//Unbox it
var unboxedVal = (double) val;
//FAR FROM A COMPLETE LIST!!!
if (prop.PropertyType == typeof (Int32))
prop.SetValue(tnew, (int) unboxedVal);
else if (prop.PropertyType == typeof (double))
prop.SetValue(tnew, unboxedVal);
else if (prop.PropertyType == typeof (DateTime))
prop.SetValue(tnew, convertDateTime(unboxedVal));
else
throw new NotImplementedException(String.Format("Type '{0}' not implemented yet!", prop.PropertyType.Name));
}
else
{
//Its a string
prop.SetValue(tnew, val);
}
});
return tnew;
});
//Send it back
return collection;
}
A FULL example:
[TestMethod]
public void Read_To_Collection_Test()
{
//A collection to Test
var objectcollection = new List<TestObject>();
for (var i = 0; i < 10; i++)
objectcollection.Add(new TestObject {Col1 = i, Col2 = i*10, Col3 = Path.GetRandomFileName(), Col4 = DateTime.Now.AddDays(i)});
//Create a test file to convert back
byte[] bytes;
using (var pck = new ExcelPackage())
{
//Load the random data
var workbook = pck.Workbook;
var worksheet = workbook.Worksheets.Add("data");
worksheet.Cells.LoadFromCollection(objectcollection, true);
bytes = pck.GetAsByteArray();
}
//*********************************
//Convert from excel to a collection
using (var pck = new ExcelPackage(new MemoryStream(bytes)))
{
var workbook = pck.Workbook;
var worksheet = workbook.Worksheets["data"];
var newcollection = worksheet.ConvertSheetToObjects<TestObject>();
newcollection.ToList().ForEach(to => Console.WriteLine("{{ Col1:{0}, Col2: {1}, Col3: \"{2}\", Col4: {3} }}", to.Col1, to.Col2, to.Col3, to.Col4.ToShortDateString()));
}
}
//test object class
public class TestObject
{
public int Col1 { get; set; }
public int Col2 { get; set; }
public string Col3 { get; set; }
public DateTime Col4 { get; set; }
}
Console Output:
{ Col1:0, Col2: 0, Col3: "wrulvxbx.wdv", Col4: 10/30/2015 }
{ Col1:1, Col2: 10, Col3: "wflh34yu.0pu", Col4: 10/31/2015 }
{ Col1:2, Col2: 20, Col3: "ps0f1jg0.121", Col4: 11/1/2015 }
{ Col1:3, Col2: 30, Col3: "skoc2gx1.2xs", Col4: 11/2/2015 }
{ Col1:4, Col2: 40, Col3: "urs3jnbb.ob1", Col4: 11/3/2015 }
{ Col1:5, Col2: 50, Col3: "m4l2fese.4yz", Col4: 11/4/2015 }
{ Col1:6, Col2: 60, Col3: "v3dselpn.rqq", Col4: 11/5/2015 }
{ Col1:7, Col2: 70, Col3: "v2ggbaar.r31", Col4: 11/6/2015 }
{ Col1:8, Col2: 80, Col3: "da4vd35p.msl", Col4: 11/7/2015 }
{ Col1:9, Col2: 90, Col3: "v5dtpuad.2ao", Col4: 11/8/2015 }