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Gregor Aisch 2013-04-03 02:05:37 +02:00
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@ -12,9 +12,9 @@ dataset: databases for lazy people
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?
Because **programmers are lazy**, and thus they tend to prefer the easiest solution they find. And managing data in a databases simply wasn't the simplest solution to store a bunch of structured data. This is where **dataset** steps in!
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!
In short, **dataset** makes reading and writing data in databases as simple as reading and writing JSON files.
*In short, dataset makes reading and writing data in databases as simple as reading and writing JSON files.*
::
@ -37,7 +37,7 @@ Features
whether an existing version can be found.
* **Query helpers** for simple queries such as :py:meth:`all <dataset.Table.all>` rows in a table or
all :py:meth:`distinct <dataset.Table.distinct>` values across a set of columns.
* **Compatibility**: Being built on top of `SQLAlchemy <http://www.sqlalchemy.org/>`_, ``dataset` works with all major databases, such as SQLite, PostgreSQL and MySQL.
* **Compatibility**: Being built on top of `SQLAlchemy <http://www.sqlalchemy.org/>`_, ``dataset`` works with all major databases, such as SQLite, PostgreSQL and MySQL.
Contents
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