Skip to main content

RDBMS access via IPython

Project description

===========
ipython-sql
===========

:Author: Catherine Devlin, http://catherinedevlin.blogspot.com

Introduces a %sql (or %%sql) magic.

Connect to a database, using SQLAlchemy connect strings, then issue SQL
commands within IPython or IPython Notebook.

.. image:: https://raw.github.com/catherinedevlin/ipython-sql/master/examples/writers.png
:width: 600px
:alt: screenshot of ipython-sql in the Notebook

Examples::

In [1]: %load_ext sql

In [2]: %%sql postgresql://will:longliveliz@localhost/shakes
...: select * from character
...: where abbrev = 'ALICE'
...:
Out[2]: [(u'Alice', u'Alice', u'ALICE', u'a lady attending on Princess Katherine', 22)]

In [3]: result = _

In [4]: print(result)
charid charname abbrev description speechcount
=================================================================================
Alice Alice ALICE a lady attending on Princess Katherine 22

In [4]: result.keys
Out[5]: [u'charid', u'charname', u'abbrev', u'description', u'speechcount']

In [6]: result[0][0]
Out[6]: u'Alice'

In [7]: result[0].description
Out[7]: u'a lady attending on Princess Katherine'

After the first connection, connect info can be omitted::

In [8]: %sql select count(*) from work
Out[8]: [(43L,)]

Connections to multiple databases can be maintained. You can refer to
an existing connection by username@database::

In [9]: %%sql will@shakes
...: select charname, speechcount from character
...: where speechcount = (select max(speechcount)
...: from character);
...:
Out[9]: [(u'Poet', 733)]

In [10]: print(_)
charname speechcount
======================
Poet 733

You may use multiple SQL statements inside a single cell, but you will
only see any query results from the last of them, so this really only
makes sense for statements with no output::

In [11]: %%sql sqlite://
....: CREATE TABLE writer (first_name, last_name, year_of_death);
....: INSERT INTO writer VALUES ('William', 'Shakespeare', 1616);
....: INSERT INTO writer VALUES ('Bertold', 'Brecht', 1956);
....:
Out[11]: []


Bind variables (bind parameters) can be used in the "named" (:x) style.
The variable names used should be defined in the local namespace::

In [12]: name = 'Countess'

In [13]: %sql select description from character where charname = :name
Out[13]: [(u'mother to Bertram',)]

Connecting
----------

Connection strings are `SQLAlchemy`_ standard.

Some example connection strings::

mysql+pymysql://scott:tiger@localhost/foo
oracle://scott:tiger@127.0.0.1:1521/sidname
sqlite://
sqlite:///foo.db

.. _SQLAlchemy: http://docs.sqlalchemy.org/en/latest/core/engines.html#database-urls

Note that ``mysql`` and ``mysql+pymysql`` connections (and perhaps others)
don't read your client character set information from .my.cnf. You need
to specify it in the connection string::

mysql+pymysql://scott:tiger@localhost/foo?charset=utf8

Configuration
-------------

Query results are loaded as lists, so very large result sets may use up
your system's memory and/or hang your browser. There is no autolimit
by default.

::

In [2]: %config SqlMagic
SqlMagic options
--------------
SqlMagic.autolimit=<Int>
Current: 0
Automatically limit the size of the returned result sets
SqlMagic.short_errors=<Bool>
Current: True
Don't display the full traceback on SQL Programming Error
SqlMagic.style=<Unicode>
Current: 'DEFAULT'
Set the table printing style to any of prettytable's defined styles
(currently DEFAULT, MSWORD_FRIENDLY, PLAIN_COLUMNS, RANDOM)

Pandas
------

If you have installed ``pandas``, you can use a result set's
``.DataFrame()`` method::

In [3]: result = %sql SELECT * FROM character WHERE speechcount > 25

In [4]: dataframe = result.DataFrame()

.. _Pandas: http://pandas.pydata.org/

Graphing
--------

If you have installed ``matplotlib``, you can use a result set's
``.plot()``, ``.pie()``, and ``.bar()`` methods for quick plotting::

In[5]: result = %sql SELECT title, totalwords FROM work WHERE genretype = 'c'

In[6]: %matplotlib inline

In[7]: result.pie()

.. image:: https://raw.github.com/catherinedevlin/ipython-sql/master/examples/wordcount.png
:alt: pie chart of word count of Shakespeare's comedies


Installing
----------

Install the lastest release with:

pip install ipython-sql

or download from https://github.com/catherinedevlin/ipython-sql and:

cd ipython-sql
sudo python setup.py install

Development
-----------

https://github.com/catherinedevlin/ipython-sql

Credits
-------

- Matthias Bussonnier for help with configuration
- `Distribute`_
- `Buildout`_
- `modern-package-template`_

.. _Buildout: http://www.buildout.org/
.. _Distribute: http://pypi.python.org/pypi/distribute
.. _`modern-package-template`: http://pypi.python.org/pypi/modern-package-template



News
====

0.1
---

*Release date: 21-Mar-2013*

* Initial release

0.1.1
-----

*Release date: 29-Mar-2013*

* Release to PyPI

* Results returned as lists

* print(_) to get table form in text console

* set autolimit and text wrap in configuration


0.1.2
-----

*Release date: 29-Mar-2013*

* Python 3 compatibility

* use prettyprint package

* allow multiple SQL per cell

0.2.0
-----

*Release date: 30-May-2013*

* Accept bind variables (Thanks Mike Wilson!)

0.2.1
-----

*Release date: 15-June-2013*

* Recognize socket connection strings

* Bugfix - issue 4 (remember existing connections by case)

0.2.2
-----

*Release date: 30-July-2013*

Converted from an IPython Plugin to an Extension for 1.0 compatibility

0.2.2.1
-------

*Release date: 01-Aug-2013*

Deleted Plugin import left behind in 0.2.2

0.2.3
-----

*Release date: 20-Sep-2013*

* Contributions from Olivier Le Thanh Duong:

- SQL errors reported without internal IPython error stack

- Proper handling of configuration

* Added .DataFrame(), .pie(), .plot(), and .bar() methods to
result sets

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ipython-sql-0.2.3.tar.gz (8.6 kB view hashes)

Uploaded Source

Built Distributions

ipython_sql-0.2.3-py3.3.egg (17.6 kB view hashes)

Uploaded Source

ipython_sql-0.2.3-py2.7.egg (16.8 kB view hashes)

Uploaded Source

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page