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Every time a row is added, modified, or deleted, its row state changes to the appropriate one in Table 8-1. This is useful if you re interested in retrieving, sorting, or filtering specific rows based on their state (for example, all new rows in the data table or all rows that have been modified). You then looped through the rows in the data view:



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Returns the object matching the given lookup parameters, which should be in the format described in the Field Lookups section. This raises AssertionError if more than one object was found. get() raises a DoesNotExist exception if an object wasn t found for the given parameters. The DoesNotExist exception is an attribute of the model class, for example: >>> Entry.objects.get(id='foo') # raises Entry.DoesNotExist The DoesNotExist exception inherits from django.core.exceptions.ObjectDoesNotExist, so you can target multiple DoesNotExist exceptions: >>> from django.core.exceptions import ObjectDoesNotExist >>> try: ... e = Entry.objects.get(id=3) ... b = Blog.objects.get(id=1) ... except ObjectDoesNotExist: ... print "Either the entry or blog doesn't exist."

' Display data from data view For Each drv As DataRowView In dv For i As Integer = 0 To dv.Table.Columns.Count - 1 Console.Write(drv(i).PadRight(20)) Next Console.WriteLine() Next

create(**kwargs)





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Note In 9, you see how classes can call methods in their superclasses (more specifically, the constructors of their superclasses). Those methods are called directly on the class; they haven t bound their self parameter to anything and are therefore called unbound methods.

Just as a data row represents a single row in a data table, a data row view (perhaps it would have been better to call it a data view row) represents a single row in a data view. You retrieve the filtered and the sorted column data for each data row view and output it to the console. As this simple example suggests, data views offer a powerful and flexible means of dynamically changing what data you work with in a data table.

This is a convenience method for creating an object and saving it all in one step. It lets you compress two common steps: >>> p = Person(first_name="Bruce", last_name="Springsteen") >>> p.save() into a single line: >>> p = Person.objects.create(first_name="Bruce", last_name="Springsteen")

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In the following sections, you ll work through a practical example showing a number of ways to update data in data tables programmatically. Note that here you ll just modify the data in the dataset but not update the data in the database. You ll see in the Propagating Changes to a Data Source section how to persist in the original data source changes made to a dataset.

s Note Changes you make to a dataset aren t automatically propagated to a database. To save the changes

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