===========
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
--------

.. code-block:: python

    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

.. code-block:: python

    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

For secure access, you may dynamically access your credentials (e.g. from your system environment or `getpass.getpass`) to avoid storing your password in the notebook itself. Use the `$` before any variable to access it in your `%sql` command.

.. code-block:: python

    In [11]: user = os.getenv('SOME_USER')
       ....: password = os.getenv('SOME_PASSWORD')
       ....: connection_string = "postgresql://{user}:{password}@localhost/some_database".format(user=user, password=password)
       ....: %sql $connection_string
    Out[11]: u'Connected: some_user@some_database'

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

.. code-block:: python

    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

.. code-block:: python

    In [12]: name = 'Countess'

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

As a convenience, dict-style access for result sets is supported, with the
leftmost column serving as key, for unique values.

.. code-block:: python

    In [14]: result = %sql select * from work
    43 rows affected.

    In [15]: result['richard2']
    Out[15]: (u'richard2', u'Richard II', u'History of Richard II', 1595, u'h', None, u'Moby', 22411, 628)

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.  However, `autolimit` (if set) limits the size of the result
set (usually with a `LIMIT` clause in the SQL).  `displaylimit` is similar,
but the entire result set is still pulled into memory (for later analysis);
only the screen display is truncated.

.. code-block:: python

    In [2]: %config SqlMagic
    SqlMagic options
    --------------
    SqlMagic.autolimit=<Int>
        Current: 0
        Automatically limit the size of the returned result sets
    SqlMagic.autopandas=<Bool>
        Current: False
        Return Pandas DataFrames instead of regular result sets
    SqlMagic.displaylimit=<Int>
        Current: 0
        Automatically limit the number of rows displayed (full result set is still
        stored)
    SqlMagic.feedback=<Bool>
        Current: True
        Print number of rows affected by DML
    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)

    In[3]: %config SqlMagic.feedback = False

Pandas
------

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

.. code-block:: python

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

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

The bogus non-standard pseudo-SQL command ``PERSIST`` will create a table name
in the database from the named DataFrame.

.. code-block:: python

    In [5]: %sql PERSIST dataframe

    In [6]: %sql SELECT * FROM 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

.. code-block:: python

    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

Dumping
-------

Result sets come with a ``.csv(filename=None)`` method.  This generates
comma-separated text either as a return value (if ``filename`` is not
specified) or in a file of the given name.

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

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

Credits
-------

- Matthias Bussonnier for help with configuration
- Olivier Le Thanh Duong for ``%config`` fixes and improvements
- Distribute_
- Buildout_
- modern-package-template_
- Mike Wilson for bind variable code
- Thomas Kluyver and Steve Holden for debugging help
- Berton Earnshaw for DSN connection syntax
- Andrés Celis for SQL Server bugfix

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