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Another well-known data structure is the heap, a kind of priority queue. A priority queue lets you add objects in an arbitrary order and at any time (possibly in-between the adding) find (and possibly remove) the smallest element. It does so much more efficiently than, say, using min on a list. In fact, there is no separate heap type in Python only a module with some heapmanipulating functions. The module is called heapq (with the q standing for queue), and it contains six functions, the first four of which are directly related to heap manipulation. You must use a list as the heap object itself. The heappush function is used to add an item to a heap. Note that you shouldn t use it on any old list only one that has been built through the use of the various heap functions. The reason for this is that the order of the elements is important (even though it may look a bit haphazard; the elements aren t exactly sorted).



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views.py, filled it with view functions, and pointed our URLconf at those functions. No apps were needed. However, there s one requirement regarding the app convention: if you re using Django s database layer (models), you must create a Django app. Models must live within apps. Thus, in order to start writing our models, we ll need to create a new app. Within the mysite project directory you created in 2, type this command to create a new app named books: python manage.py startapp books This command does not produce any output, but it does create a books directory within the mysite directory. Let s look at the contents of that directory: books/ __init__.py models.py views.py These files will contain the models and views for this app. Have a look at models.py and views.py in your favorite text editor. Both files are empty, except for an import in models.py. This is the blank slate for your Django app.





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In the sp_DbException_1 stored procedure, you first found the number of orders in the Orders table and stored the number in a variable called @ordercount:

As we discussed earlier in this chapter, the M in MTV stands for Model A Django model is a description of the data in your database, represented as Python code It s your data layout the equivalent of your SQL CREATE TABLE statements except it s in Python instead of SQL, and it includes more than just database column definitions Django uses a model to execute SQL code behind the scenes and return convenient Python data structures representing the rows in your database tables Django also uses models to represent higher-level concepts that SQL can t necessarily handle If you re familiar with databases, your immediate thought might be, Isn t it redundant to define data models in Python and in SQL Django works the way it does for several reasons: Introspection requires overhead and is imperfect.

Then, if @ordercount was greater than ten, you raised an error using the RAISERROR statement:

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if @ordercount > 10 raiserror ( 'Orders Count is greater than 10 - Notify the Business Manager', 16, 1 )

In order to provide convenient dataaccess APIs, Django needs to know the database layout somehow, and there are two ways of accomplishing this The first way is to explicitly describe the data in Python, and the second way is to introspect the database at runtime to determine the data models This second way seems cleaner, because the metadata about your tables lives in only one place, but it introduces a few problems First, introspecting a database at runtime obviously requires overhead If the framework had to introspect the database each time it processed a request, or even when the Web server was initialized, this would incur an unacceptable level of overhead (While some believe that level of overhead is acceptable, Django s developers aim to trim as much framework overhead as possible, and this approach has succeeded in making Django faster than its high-level framework competitors in benchmarks.

Then, in the Button3_Click method, you executed the stored procedure using the ExecuteNonQuery method within a Try block:

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