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    <p>You may find that <code>pickle</code> and databases don't work too well together.</p> <p>Python's <a href="http://docs.python.org/library/pickle.html" rel="nofollow">pickle</a> is for serializing Python objects to a format, that can then be read back in to Python objects by Python. Although it's very easy to serialize with <code>pickle</code>, you can't* query this serialized format, you can't* read it into a program in another language. Check out <a href="http://docs.python.org/library/pickle.html#module-cPickle" rel="nofollow">cPickle</a>, another Python module, for faster <code>pickle</code>-ing.</p> <p>Databases, on the other hand, are great for persisting data <em>in such a way that it is queryable and non-language-specific</em>. But the cost is that it's generally harder to get/put data into/from the database. That's why there's special tools like <a href="http://www.sqlalchemy.org/" rel="nofollow">SQL Alchemy</a>, and endless blog-based debates about the benefits/horrors of Object-Relation-Mapping software.</p> <p><code>Pickle</code>-ing objects, and then sending them to a database such as MySQL or SQL Server is probably not a good idea. However, check out <a href="http://docs.python.org/library/shelve.html#module-shelve" rel="nofollow">shelve</a>, another Python module for database-like persistence of Python objects.</p> <p>So, to sum up:</p> <ul> <li>use <code>pickle</code> or <code>shelve</code> if you just need to save the data for later use by a Python program</li> <li>map objects to a database if you want to persist the data for general use, with the understanding that this requires more effort</li> <li>performance-wise, <code>cPickle</code> will probably win over a database + object/relation mapping</li> </ul> <hr> <p>*: at least, not without a lot of effort and/or special libraries.</p>
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    1. POWhat is the best way to store big vector to database with python?
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    1. USMatt Fenwick
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    1. COThanks, for good answer.
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