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Tools for interfacing with SQLite databases
Python Shell

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dbtools
docs
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CHANGELOG.md
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MANIFEST.in
Makefile
README.md
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requirements.txt
setup.py

README.md

dbtools

A simple interface to SQLite databases.

Overview

This module handles simple interfacing with a SQLite database. Inspired by ipython-sql, dbtools returns pandas DataFrame objects from SELECT queries, and can handle basic forms of other SQL statements (CREATE, INSERT, UPDATE, DELETE, and DROP).

The goal is not to replicate the full functionality of SQLAlchemy or really to be used for object-relational mapping at all. This is meant to be used more for scientific data collection (e.g., behavioral experiments) as convenient access to a robust form of storage.

Installation

The easiest way to get dbtools is with pip:

pip install dbtools

Alternately, you can clone the repository and install from source:

git clone git@github.com:jhamrick/dbtools.git
cd dbtools
python setup.py install

There is also a Makefile in the root of the repository which is just a convenience wrapper around setup.py. So, make install is equivalent to python setup.py install. You can use whichever one you prefer.

Examples

Create and load

>>> from dbtools import Table
>>> tbl = Table.create("data.db", "People",
... [('id', int),
... ('name', str),
... ('age', int),
... ('height', float)],
... primary_key='id',
... autoincrement=True)
>>> tbl
People(id INTEGER PRIMARY KEY AUTOINCREMENT, name TEXT, age INTEGER, height REAL)
>>> type(tbl)
<class 'dbtools.table.Table'>

If a table already exists, we can just directly create a Table object:

>>> tbl = Table("data.db", "People")
>>> tbl
People(id INTEGER PRIMARY KEY AUTOINCREMENT, name TEXT, age INTEGER, height REAL)
>>> tbl.columns
(u'id', u'name', u'age', u'height')
>>> tbl.primary_key
u'id'
>>> tbl.autoincrement
True

Insert

Inserting with a list (excluding id, because it autoincrements):

>>> tbl.insert(["Alyssa P. Hacker", 25, 66.24])
>>> tbl.select()
                name  age  height
id
1   Alyssa P. Hacker   25   66.24
>>> type(tbl.select())
<class 'pandas.core.frame.DataFrame'>

Inserting with a dictionary:

>>> tbl.insert({
... 'name': 'Ben Bitdiddle',
... 'age': 24,
... 'height': 70.1})
>>> tbl.select()
                name  age  height
id
1   Alyssa P. Hacker   25   66.24
2      Ben Bitdiddle   24   70.10

You can insert as many things as you want as a time -- just pass them in as a list of lists and/or dictionaries.

Select

The previous two examples already used an instance of selection with tbl.select(), which is the equivalent of doing FROM People SELECT *. You can use slicing to select rows (but only if the primary key column is an integer and autoincrements). Note that because SQLite databases are one-indexed, indexing the zeroth element returns an empty DataFrame.

>>> tbl[1]
                name  age  height
id
1   Alyssa P. Hacker   25   66.24
>>> tbl[2:]
             name  age  height
id
2   Ben Bitdiddle   24    70.1

If you pass in a string or sequence of strings, it will treat them as column names and select those columns:

>>> tbl['name', 'height']
                name  height
id
1   Alyssa P. Hacker   66.24
2      Ben Bitdiddle   70.10

More advanced selection can be done through the select method by specifying the where keyword argument (and you can use the ? syntax from the sqlite3 library for untrusted inputs):

>>> tbl.select(where='age>24')
                name  age  height
id
1   Alyssa P. Hacker   25   66.24
>>> tbl.select(columns=['name', 'height'], where=('age>?', 24))
                name  height
id
1   Alyssa P. Hacker   66.24

Update

Updating data in the table works by taking a dictionary (with the keys being columns, and values being new data) and (optionally) a where keyword argument like in the select method to specify what data should be updated.

>>> tbl.update({'age': 26}, where='id=1')
>>> tbl.select()
                name  age  height
id
1   Alyssa P. Hacker   26   66.24
2      Ben Bitdiddle   24   70.10

Delete

Deleting a row or rows requires specifying a where keyword argument like in select and update (if it is not given, all rows are deleted).

>>> tbl.delete(where='height<70')
>>> tbl.select()
             name  age  height
id
2   Ben Bitdiddle   24    70.1

Drop

Finally, the drop method is used to drop (delete) an entire table from its database. Of course, this means it can't be accessed afterwards because it no longer exists.

>>> tbl.drop()
>>> tbl.select()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "dbtools/table.py", line 339, in select
    cur.execute(*cmd)
sqlite3.OperationalError: no such table: People
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