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So, if a dataset doesn t have to be connected to a database, how do you populate it with data and save its data back to the database This is where data adapters come in. Think of data adapters as bridges between datasets and data sources. Without a data adapter, a dataset can t access any kind of data source. The data adapter takes care of all connection details for the dataset, populates it with data, and updates the data source. In this chapter, we ll cover the following: Datasets and data adapters How data is stored in a dataset with data tables, data rows, and data columns How to get different views of the data in a dataset



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This example, taken from the django.contrib.auth.models.User model, shows how both list_display and list_filter work: class User(models.Model): ... class Admin: list_display = ('username', 'email', 'first_name', 'last_name', 'is_staff') list_filter = ('is_staff', 'is_superuser')

Manipulating data in a dataset Persisting changes in the dataset back to the original data source Working with datasets and XML Using data tables without datasets Typed and untyped datasets

Set list_per_page to control how many items appear on each paginated admin change list page. By default, this is set to 100.





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We ll begin this chapter with a quick presentation of all the new objects you ll need to understand in order to work with datasets and data adapters. You ll start by looking at the difference between datasets and data readers and then move on to look in more detail at how data is structured within a dataset and how a dataset works in collaboration with a data adapter.

In object-oriented programming, the term object loosely means a collection of data (attributes) with a set of methods for accessing and manipulating those data. There are several reasons for using objects instead of sticking with global variables and functions. Some of the most important benefits of objects include the following: Polymorphism Encapsulation Inheritance Roughly, these terms mean that you can use the same operations on objects of different classes, and they will work as if by magic (polymorphism); you hide unimportant details of how objects work from the outside world (encapsulation), and you can create specialized classes of objects from general ones (inheritance).

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If you simply want to read and display data, then you need to use only a data reader, as you saw in the previous chapter, particularly if you re working with large quantities of data. In situations where you need to loop through thousands or millions of rows, you want a fast sequential reader (reading rows from the result set one at a time), and the data reader does this job in an efficient way. If you need to manipulate the data in any way and then update the database, then you need to use a dataset. A data adapter fills a dataset by using a data reader; additional resources are needed to save data for disconnected use. You need to think about whether you really need a dataset; otherwise, you ll just be wasting resources. Unless you need to update the data source or use other dataset features such as reading and writing to XML files, exporting database schemas, and creating XML views of a database, you should use a data reader.

Set list_select_related to tell Django to use select_related() in retrieving the list of objects on the admin change list page. This can save you a bunch of database queries if you re using related objects in the admin change list display. The value should be either True or False. The default is False unless one of the list_display fields is a ForeignKey. For more on select_related(), see Appendix C.

The notion of a dataset in ADO.NET is a big step in the world of multi-tiered database application development. When retrieving or modifying large amounts of data, maintaining an open connection to a data source while waiting for users to make requests is an enormous waste of precious resources. Datasets help tremendously here, because they enable you to store and modify large amounts of data in a local cache, view the data as tables, and process the data in an offline mode (in other words, disconnected from the database).

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