Conclusion
The various integration technologies in Python make it easy to acquire data from any database. ODBC is our favorite because it turns the data into Python variables with the greatest speed and least lines of code; however, we have shown you how to get connected with a wide range of tools.
Once you fetch the data, manipulating it is easy in Python. Python
objects can hold numbers, strings, and dates; and sets of data can be
represented in native Python lists and tuples. This means the data is
right there in front of you; there’s no need to loop over the
properties of Recordset objects or cursors.
In this chapter, we have shown how to build the beginnings of a powerful toolkit for transforming and manipulating data in Python. This makes it easy to switch between different representations of data, as rows, dictionaries of keys and values, or objects.
Python is particularly well suited to writing data-laundering scripts and to constructing dynamic object models on top of a database.
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