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.. dataset documentation master file, created by
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sphinx-quickstart on Mon Apr 1 18:41:21 2013.
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You can adapt this file completely to your liking, but it should at least
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contain the root `toctree` directive.
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dataset: databases for lazy people
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==================================
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.. toctree::
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:hidden:
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Although managing data in relational database has plenty of benefits, we find them rarely being used in the typical day-to-day work with small to medium scale datasets. But why is that? Why do we see an awful lot of data stored in static files in CSV or JSON format?
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Because **programmers are lazy** they tend to prefer the easiest solution they find. And in **Python**, managing data in a databases simply wasn't the simplest solution to store a bunch of structured data. This is where **dataset** steps in!
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*In short, dataset makes reading and writing data in databases as simple as reading and writing JSON files.*
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::
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import dataset
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db = dataset.connect('sqlite:///database.db')
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db['sometable'].insert(dict(name='John Doe', age=37))
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db['sometable'].insert(dict(name='Jane Doe', age=34, gender='female'))
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Here is `similar code, without dataset <https://gist.github.com/gka/5296492>`_.
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Features
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--------
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* **Automatic schema**: If a table or column is written that does not
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exist in the database, it will be created automatically.
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* **Upserts**: Records are either created or updated, depending on
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whether an existing version can be found.
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* **Query helpers** for simple queries such as :py:meth:`all <dataset.Table.all>` rows in a table or
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all :py:meth:`distinct <dataset.Table.distinct>` values across a set of columns.
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* **Compatibility**: Being built on top of `SQLAlchemy <http://www.sqlalchemy.org/>`_, ``dataset`` works with all major databases, such as SQLite, PostgreSQL and MySQL.
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Contents
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--------
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.. toctree::
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:maxdepth: 2
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quickstart
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api
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