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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.

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

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.

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

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',)]

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

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:[email protected]:1521/sidname
sqlite://
sqlite:///foo.db

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.

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

Please note: if you have autopandas set to true, the displaylimit option will not apply. You can set the pandas display limit by using the pandas max_rows option as described in the pandas documentation.

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()

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

In [5]: %sql PERSIST dataframe

In [6]: %sql SELECT * FROM dataframe;

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()

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.

In[8]: result = %sql SELECT title, totalwords FROM work WHERE genretype = 'c'

In[9]: result.csv(filename='work.csv')

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
  • Michael Erasmus for DataFrame truth bugfix
  • Noam Finkelstein for README clarification