1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
|
Storm is an Object Relational Mapper for Python developed at
Canonical. API docs, a manual, and a tutorial are available from:
http://storm.canonical.com/
Introduction
============
The project was in development for more than a year for use in
Canonical projects such as Launchpad and Landscape before being
released as free software on July 9th, 2007.
Design:
* Clean and lightweight API offers a short learning curve and
long-term maintainability.
* Storm is developed in a test-driven manner. An untested line of
code is considered a bug.
* Storm needs no special class constructors, nor imperative base
classes.
* Storm is well designed (different classes have very clear
boundaries, with small and clean public APIs).
* Designed from day one to work both with thin relational
databases, such as SQLite, and big iron systems like PostgreSQL.
* Storm is easy to debug, since its code is written with a KISS
principle, and thus is easy to understand.
* Designed from day one to work both at the low end, with trivial
small databases, and the high end, with applications accessing
billion row tables and committing to multiple database backends.
* It's very easy to write and support backends for Storm (current
backends have around 100 lines of code).
Features:
* Storm is fast.
* Storm lets you efficiently access and update large datasets by
allowing you to formulate complex queries spanning multiple
tables using Python.
* Storm allows you to fallback to SQL if needed (or if you just
prefer), allowing you to mix "old school" code and ORM code
* Storm handles composed primary keys with ease (no need for
surrogate keys).
* Storm doesn't do schema management, and as a result you're free
to manage the schema as wanted, and creating classes that work
with Storm is clean and simple.
* Storm works very well connecting to several databases and using
the same Python types (or different ones) with all of them.
* Storm can handle obj.attr = <A SQL expression> assignments, when
that's really needed (the expression is executed at INSERT/UPDATE
time).
* Storm handles relationships between objects even before they were
added to a database.
* Storm works well with existing database schemas.
* Storm will flush changes to the database automatically when
needed, so that queries made affect recently modified objects.
License
=======
Copyright (C) 2006-2009 Canonical, Ltd. All contributions must have
copyright assigned to Canonical.
This library is free software; you can redistribute it and/or
modify it under the terms of the GNU Lesser General Public
License as published by the Free Software Foundation; either
version 2.1 of the License, or (at your option) any later version.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA
02110-1301 USA
On Ubuntu systems, the complete text of the GNU Lesser General
Public Version 2.1 License is in /usr/share/common-licenses/LGPL-2.1
Developing Storm
================
SHORT VERSION: If you are running ubuntu, or probably debian, the
following should work. If not, and for reference, the long version
is below.
$ dev/ubuntu-deps
$ make develop
$ dev/db-setup
$ make check
LONG VERSION:
The following instructions describe the procedure for setting up a
development environment and running the test suite.
Installing dependencies
-----------------------
The following instructions assume that you're using Ubuntu. The same procedure
will probably work without changes on a Debian system and with minimal changes
on a non-Debian-based linux distribution. In order to run the test suite, and
exercise all supported backends, you will need to install PostgreSQL, along
with the related Python database drivers:
$ sudo apt-get install \
postgresql pgbouncer \
build-essential
These will take a few minutes to download (its a bit under 200MB all
together).
The Python dependencies for running tests can mostly be installed with
apt-get:
$ apt-get install \
python-fixtures python-psycopg2 \
python-testresources python-transaction python-twisted \
python-zope.component python-zope.security
Two modules - pgbouncer and timeline - are not yet packaged in
Ubuntu. These can be installed from PyPI:
http://pypi.python.org/pypi/pgbouncer
http://pypi.python.org/pypi/timeline
Alternatively, dependencies can be downloaded as eggs into the current
directory with:
$ make develop
This ensures that all dependencies are available, downloading from
PyPI as appropriate.
Setting up database users and access security
---------------------------------------------
PostgreSQL needs to be setup to allow TCP/IP connections from
localhost. Edit /etc/postgresql/8.3/main/pg_hba.conf and make sure
the following line is present:
host all all 127.0.0.1/32 trust
This will probably (with PostgresSQL 8.4) entail changing 'md5' to
'trust'.
In order to run the two-phase commit tests, you will also need to
change the max_prepared_transactions value in postgres.conf to
something like
max_prepared_transactions = 200
Now save and close, then restart the server:
$ sudo /etc/init.d/postgresql-8.4 restart
Lets create our PostgreSQL user now. As noted in the Ubuntu PostgreSQL
documentation, the easiest thing is to create a user with the same name as your
username. Run the following command to create a user for yourself (if prompted
for a password, leave it blank):
$ sudo -u postgres createuser --superuser $USER
Creating test databases
-----------------------
The test suite needs some local databases in place to exercise PostgreSQL
functionality. Run:
$ createdb storm_test
Running the tests
-----------------
Finally, its time to run the tests! Go into the base directory of
the storm branch you want to test, and run:
$ make check
They'll take a while to run. All tests should pass: failures mean
there's a problem with your environment or a bug in Storm.
|