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A more granular way to use the caching framework is by caching the output of individual views. This has the same effects as the per-site cache (including the omission of caching on requests with GET and POST parameters). It applies to whichever views you specify, rather than the whole site. Do this by using a decorator, which is a wrapper around your view function that alters its behavior to use caching. The per-view cache decorator is called cache_page and is located in the django.views.decorators.cache module, for example: from django.views.decorators.cache import cache_page def my_view(request, param): # ... my_view = cache_page(my_view, 60 * 15) Alternatively, if you re using Python 2.4 or greater, you can use decorator syntax. This example is equivalent to the preceding one: from django.views.decorators.cache import cache_page @cache_page(60 * 15) def my_view(request, param): # ... cache_page takes a single argument: the cache timeout, in seconds. In the preceding example, the result of the my_view() view will be cached for 15 minutes. (Note that we ve written it as 60 * 15 for the purpose of readability. 60 * 15 will be evaluated to 900 that is, 15 minutes multiplied by 60 seconds per minute.) The per-view cache, like the per-site cache, is keyed off of the URL. If multiple URLs point at the same view, each URL will be cached separately. Continuing the my_view example, if your URLconf looks like this: urlpatterns = ('', (r'^foo/(\d{1,2})/$', my_view), ) then requests to /foo/1/ and /foo/23/ will be cached separately, as you may expect. But once a particular URL (e.g., /foo/23/) has been requested, subsequent requests to that URL will use the cache.

The two results look similar; however, there is an important difference between sets consisting of a single element, such as {'SMITH'}, and a literal value, such as 'SMITH'. In mathematics, sets with a single element are commonly referred to as singleton sets, or just singletons. Listing 8-34 shows another instructive mistake. Listing 8-34. Error Message: Not a Single-Group Group Function select deptno , sum(msal) from employees; select deptno * ERROR at line 1: ORA-00937: not a single-group group function In the absence of a GROUP BY clause, the SUM function would return a single row, while DEPTNO would produce 14 department numbers. Two columns with different row counts cannot be presented side-byside in a single result. After the correction in Listing 8-35, the error message disappears, and you get the desired results. Listing 8-35. Correction of the Error Message in Listing 8-34 select , from group by deptno sum(msal) employees deptno;

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My intention is not to cover all of the nitty-gritty details of the Java JDBC API entire books are devoted to fully exploring JDBC but rather to give you a jump-start in understanding JDBC conceptually if and when you do decide to delve into it in detail. JDBC is one of the key component technologies of the Java 2 Platform, Enterprise Edition (J2EE), for example, and is a fairly common ingredient in most industrial-strength information system applications. We ll revisit J2EE conceptually at the end of 17.

DEPTNO SUM(MSAL) -------- ------------10 8750 20 10875 30 9250

The examples in the previous section have hard-coded the fact that the view is cached, because cache_page alters the my_view function in place. This approach couples your view to the cache system, which is not ideal for several reasons. For instance, you might want to reuse the view functions on another, cacheless site, or you might want to distribute the views to people who might want to use them without being cached. The solution to these problems is to specify the per-view cache in the URLconf rather than next to the view functions themselves. Doing so is easy: simply wrap the view function with cache_page when you refer to it in the URLconf. Here s the old URLconf from earlier: urlpatterns = ('', (r'^foo/(\d{1,2})/$', my_view), ) Here s the same thing, with my_view wrapped in cache_page: from django.views.decorators.cache import cache_page urlpatterns = ('', (r'^foo/(\d{1,2})/$', cache_page(my_view, 60 * 15)), ) If you take this approach, don t forget to import cache_page within your URLconf.

There is a tendency for folks who are just learning about classes and objects to relate the concept of an object to that of a row in a database table, where the table as a whole represents an entire class of similar objects; this is illustrated in Figure 15-6.

We often do persist the state of an object within a relational database, as illustrated conceptually in Figure 15-7: We query a database to read data in for the purpose of initializing an object s attribute values, temporarily creating an in-memory copy of the object as persisted in the database. We record changes to the object s state (attribute values) in the database to persist them.

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