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s In general, try to exploit SQL, rather than code VB procedures, to get the data you need from the dataTip

In older versions of Python, there was a sharp distinction between types and classes. Built-in objects had types, your custom objects had classes. You c

values(*fields)



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base. Database servers are optimized to perform selections and sorts, as well as other things. Queries can be far more sophisticated and powerful than the ones you ve been playing with in this book. By carefully (and creatively) coding queries to return exactly what you need, you not only minimize resource demands (on memory, network bandwidth, and so on) but also reduce the code you must write to manipulate and format result set data.





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Returns a special QuerySet that evaluates to a list of dictionaries instead of model-instance objects. Each of those dictionaries represents an object, with the keys corresponding to the attribute names of model objects: # This list contains a Blog object. >>> Blog.objects.filter(name__startswith='Beatles') [Beatles Blog] # This list contains a dictionary. >>> Blog.objects.filter(name__startswith='Beatles').values() [{'id': 1, 'name': 'Beatles Blog', 'tagline': 'All the latest Beatles news.'}] values() takes optional positional arguments, *fields, which specify field names to which the SELECT should be limited. If you specify the fields, each dictionary will contain only the field keys/values for the fields you specify. If you don t specify the fields, each dictionary will contain a key and value for every field in the database table:

The loop through the second data table is interesting mainly for its first line:

which uses an ordinal index. Since you didn t rename the second data table (you could have done so with its TableName property), it was better to use the index rather than the name (customers1), since a change to the name in the Fill() call would require you to change it here, an unlikely thing to remember to do, if the case ever arose.

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>>> Blog.objects.values() [{'id': 1, 'name': 'Beatles Blog', 'tagline': 'All the latest Beatles news.'}], >>> Blog.objects.values('id', 'name') [{'id': 1, 'name': 'Beatles Blog'}] This method is useful when you know you re only going to need values from a small number of the available fields and you won t need the functionality of a model instance object. It s more efficient to select only the fields you need to use.

his chapter introduces a new concept: data structures. A data structure is a collection of data elements (such as numbers or characters or even other data structures) that is structured in some way, for example, by numbering the elements. The most basic data structure in Python is the sequence. Each element of a sequence is assigned a number its position, or index. The first index is zero, the second index is one, and so forth.

In the first example, PopDataSet (Listing 8-1), you saw how simple it is to get data into a dataset. The second example, FilterSort (Listing 8-2), was just a variation, demonstrating how multiple result sets are handled and how to filter and sort data tables. However, the two programs have one major difference. Did you notice it FilterSort doesn t explicitly open a connection! In fact, it s the first (but won t be the last) program you ve written that doesn t. Why doesn t it The answer is simple but very important. The Fill method automatically opens a connection if it s not open when Fill() is called. It then closes the connection after filling the dataset. However, if a connection is open when Fill() is called, it uses that connection and doesn t close it afterward. So, although datasets are completely independent of databases (and connections), just because you re using a dataset doesn t mean you re running disconnected from a database. If you want to run disconnected, use datasets, but don t open connections before filling them (or, if a connection is open, close it first). Datasets in themselves don t imply either connected or disconnected operations.

dates(field, kind, order)

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