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Once an application is known, the next step is to deal with individual models within that application. Once again, comes through with a few methods to handle this situation. Retrieving models from the cache typically takes one of two forms, depending on how much is known about the model in advance. In the first case, consider pure introspection. Remember from the previous section that provides access to all known applications with a single call to the method, which returns application modules. Since these modules are actually the modules within each application, it may seem easy to just use or iterate over to get the models that were defined. Unfortunately, like many uses of simple iteration, that would require the loop to check each individual object in the module to see if it is in fact a model or if it s something else entirely. After all, Python modules can contain anything, and many models make use of tuples and module-level constants to help do their work, so there s no guarantee that each item in the module s namespace is in fact a Django model. Instead, retrieves a list of proper Django models that are specific to the given application module. It s no coincidence that both and return application modules; is suitable for use with both of these methods. That means that a list of models can be retrieved even without an application, but knowing the application in advance reduces the number of models retrieved. The following code demonstrates how these techniques can be used in combination to retrieve a list of models for each of the known applications in use on the site.

HttpCookie cookie = new HttpCookie("Preferences"); // Set a value in it cookie["LanguagePref"] = "English"; // Add it to the current web response ResponseCookiesAdd(cookie); A cookie added in this way will persist until the user closes the browser and will be sent with every request To create a longer-lived cookie, you can set an expiration date, as shown here: // This cookie lives for one year cookieExpires = DateTimeNowAddYears(1);.

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In addition to the fields retrieved from the data source, you can add calculated columns. Calculated columns are ignored when retrieving and updating data. Instead, they represent a value that s computed using a combination of existing values. To create a calculated column, you simply create a new DataColumn object (specifying its name and type) and set the Expression property. Finally, you add the DataColumn to the Columns collection of the DataTable using the Add() method. As an example, here s a column that uses string concatenation to combine the first and last name into one field: DataColumn fullName = new DataColumn( "FullName", typeof(string), "TitleOfCourtesy + ' ' + LastName + ', ' + FirstName"); ds.Tables["Employees"].Columns.Add(fullName);

Of course, you can also execute a query that creates calculated columns. However, that approach makes it more difficult to update the data source later, and it creates more work for the data source. For that reason, it s often a better solution to create calculated columns in the DataSet.

As an additional option, can also be called with no argument, which will cause it to return all the models that are known to This is a useful shortcut to avoid some of the overhead associated with the extra loop in this example, as a quick way to grab all the models There s a catch, however When using directly, with no argument, all registered models are returned This may sound like a great idea, and sometimes it is, but remember that registers all models as they re encountered, regardless of where they were found The full list may include models that aren t part of an installed application Contrast that with the / combination, which only retrieves models if their applications are found in the setting In practice, may return different results if called without an argument than if it were called with each of the applications returned from .

You can also create a calculated column that incorporates information from related rows. For example, you might add a column in a Categories table that indicates the number of related product rows. In this case, you need to make sure you first define the relationship with a DataRelation object. You also need to use a SQL aggregate function such as AVG(), MAX(), MIN(), or COUNT(). Here s an example that creates three calculated columns, all of which use aggregate functions and table relationships: string connectionString = WebConfigurationManager.ConnectionStrings["Northwind"].ConnectionString; SqlConnection con = new SqlConnection(connectionString); string sqlCat = "SELECT CategoryID, CategoryName FROM Categories"; string sqlProd = "SELECT ProductName, CategoryID, UnitPrice FROM Products"; SqlDataAdapter da = new SqlDataAdapter(sqlCat, con); DataSet ds = new DataSet(); try { con.Open(); da.Fill(ds, "Categories"); da.SelectCommand.CommandText = sqlProd; da.Fill(ds, "Products"); } finally { con.Close(); } // Define the relationship between Categories and Products. DataRelation relat = new DataRelation("CatProds", ds.Tables["Categories"].Columns["CategoryID"], ds.Tables["Products"].Columns["CategoryID"]); // Add the relationship to the DataSet. ds.Relations.Add(relat); // Create the calculated columns. DataColumn count = new DataColumn( "Products (#)", typeof(int), "COUNT(Child(CatProds).CategoryID)"); DataColumn max = new DataColumn( "Most Expensive Product", typeof(decimal), "MAX(Child(CatProds).UnitPrice)"); DataColumn min = new DataColumn( "Least Expensive Product", typeof(decimal), "MIN(Child(CatProds).UnitPrice)"); // Add the columns. ds.Tables["Categories"].Columns.Add(count); ds.Tables["Categories"].Columns.Add(max); ds.Tables["Categories"].Columns.Add(min); // Show the data. GridView1.DataSource = ds.Tables["Categories"]; GridView1.DataBind();

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