By building an IEnumerableT> wrapper for the data source, a LINQ query can still be made against a data source that does not support the IEnumerableT> interface. An object that implements the IEnumerableT> interface and transmits the LINQ query operations to the underlying data source is created to do this.   Utilizing the yield return statement is one method for developing such a wrapper. An iterator block is made using the yield return statement, a special kind of return statement. When a method with a yield return statement is invoked, the method does not instantly execute its statements; instead, it returns an object that can be used to iterate through the method's results.   Consider the scenario where you wish to use LINQ to query a huge file that is represented by a data source. By writing a method that reads the file one line at a time and uses yield return to return each line as it is read, you might turn the file into an IEnumerablestring> wrapper:  IEnumerable ReadLines(string filePath)  {  using (StreamReader reader = new StreamReader(filePath))  {  string line;  while ((line = reader.ReadLine()) != null)  {  yield return line;  }  }  }  You can now use this method as the data source for a LINQ query, like this:  string filePath = @"C:\\example.txt";  var query = from line in ReadLines(filePath)  where line.Contains("example")  select line; By developing a class that implements the IEnumerableT> interface and has its own logic for how to retrieve data from the data source, you can also create a generic wrapper for the data source.   Utilizing LINQ's AsEnumerable() extension method is another technique to create an IEnumerableT> wrapper for a data source that does not support the interface. By creating an IEnumerableT> wrapper for the data source using the AsEnumerable() function, you may use LINQ query operators on the data source without changing the data source itself.   If this is the case, the query will be run locally, and depending on the size of the data source, it may use more memory and have a larger performance cost.