Commit 1f7fd3ac authored by Guido van Rossum's avatar Guido van Rossum

Adding AMK's guide (merge)

parent 5c0bad8d
PYTHONSRC=$$HOME/projects/python
TEX_FILES = gfdl.tex introduction.tex modules.tex prog-zodb.tex \
storages.tex transactions.tex zeo.tex zodb.tex
MKHOWTO=$(PYTHONSRC)/Doc/tools/mkhowto
zodb.dvi: $(TEX_FILES)
$(MKHOWTO) --dvi zodb.tex
html:
-rm -rf zodb
$(MKHOWTO) --html --iconserver=/python/writing/icons zodb.tex
# rm -f /home/amk/www/zodb/guide/*
# cp -p zodb/* /home/amk/www/zodb/guide/
This directory contains Andrew Kuchling's programmers guide to ZODB
and ZEO. It is taken from Andrew's zodb.sf.net project on
SourceForge. The SF version should be considered the canonical
version, so don't make edits here for now.
Eventually, we'll finish merging the two projects and then the version
here will be the canonical one. For now, we have to manually keep the
two directories in sync.
Update text to use BTrees, not BTree
Write section on __setstate__
Connection.sync seems to work now; note this
Continue working on it
Suppress the full GFDL text in the PDF/PS versions
% Administration
% Importing and exporting data
% Disaster recovery/avoidance
% Security
import sys, time, os, random
from ZEO import ClientStorage
import ZODB
from ZODB.POSException import ConflictError
from Persistence import Persistent
import BTree
class ChatSession(Persistent):
"""Class for a chat session.
Messages are stored in a B-tree, indexed by the time the message
was created. (Eventually we'd want to throw messages out,
add_message(message) -- add a message to the channel
new_messages() -- return new messages since the last call to
this method
"""
def __init__(self, name):
"""Initialize new chat session.
name -- the channel's name
"""
self.name = name
# Internal attribute: _messages holds all the chat messages.
self._messages = BTree.BTree()
def new_messages(self):
"Return new messages."
# self._v_last_time is the time of the most recent message
# returned to the user of this class.
if not hasattr(self, '_v_last_time'):
self._v_last_time = 0
new = []
T = self._v_last_time
for T2, message in self._messages.items():
if T2 > T:
new.append( message )
self._v_last_time = T2
return new
def add_message(self, message):
"""Add a message to the channel.
message -- text of the message to be added
"""
while 1:
try:
now = time.time()
self._messages[ now ] = message
get_transaction().commit()
except ConflictError:
# Conflict occurred; this process should pause and
# wait for a little bit, then try again.
time.sleep(.2)
pass
else:
# No ConflictError exception raised, so break
# out of the enclosing while loop.
break
# end while
def get_chat_session(conn, channelname):
"""Return the chat session for a given channel, creating the session
if required."""
# We'll keep a B-tree of sessions, mapping channel names to
# session objects. The B-tree is stored at the ZODB's root under
# the key 'chat_sessions'.
root = conn.root()
if not root.has_key('chat_sessions'):
print 'Creating chat_sessions B-tree'
root['chat_sessions'] = BTree.BTree()
get_transaction().commit()
sessions = root['chat_sessions']
# Get a session object corresponding to the channel name, creating
# it if necessary.
if not sessions.has_key( channelname ):
print 'Creating new session:', channelname
sessions[ channelname ] = ChatSession(channelname)
get_transaction().commit()
session = sessions[ channelname ]
return session
if __name__ == '__main__':
if len(sys.argv) != 2:
print 'Usage: %s <channelname>' % sys.argv[0]
sys.exit(0)
storage = ClientStorage.ClientStorage( ('localhost', 9672) )
db = ZODB.DB( storage )
conn = db.open()
s = session = get_chat_session(conn, sys.argv[1])
messages = ['Hi.', 'Hello', 'Me too', "I'M 3L33T!!!!"]
while 1:
# Send a random message
msg = random.choice(messages)
session.add_message( '%s: pid %i' % (msg,os.getpid() ))
# Display new messages
for msg in session.new_messages():
print msg
# Wait for a few seconds
pause = random.randint( 1, 4 )
time.sleep( pause )
This diff is collapsed.
% Indexing Data
% BTrees
% Full-text indexing
%Introduction
% What is ZODB?
% What is ZEO?
% OODBs vs. Relational DBs
% Other OODBs
\section{Introduction}
This guide explains how to write Python programs that use the Z Object
Database (ZODB) and Zope Enterprise Objects (ZEO). The latest version
of the guide is always available at
\url{http://www.amk.ca/zodb/guide/}.
\subsection{What is the ZODB?}
The ZODB is a persistence system for Python objects. Persistent
programming languages provide facilities that automatically write
objects to disk and read them in again when they're required by a
running program. By installing the ZODB, you add such facilities to
Python.
It's certainly possible to build your own system for making Python
objects persistent. The usual starting points are the \module{pickle}
module, for converting objects into a string representation, and
various database modules, such as the \module{gdbm} or \module{bsddb}
modules, that provide ways to write strings to disk and read them
back. It's straightforward to combine the \module{pickle} module and
a database module to store and retrieve objects, and in fact the
\module{shelve} module, included in Python's standard library, does
this.
The downside is that the programmer has to explicitly manage objects,
reading an object when it's needed and writing it out to disk when the
object is no longer required. The ZODB manages objects for you,
keeping them in a cache and writing them out if they haven't been
accessed in a while.
\subsection{OODBs vs. Relational DBs}
Another way to look at it is that the ZODB is a Python-specific
object-oriented database (OODB). Commercial object databases for C++
or Java often require that you jump through some hoops, such as using
a special preprocessor or avoiding certain data types. As we'll see,
the ZODB has some hoops of its own to jump through, but in comparison
the naturalness of the ZODB is astonishing.
Relational databases (RDBs) are far more common than OODBs.
Relational databases store information in tables; a table consists of
any number of rows, each row containing several columns of
information. (Rows are more formally called relations, which is where
the term ``relational database'' originates.)
Let's look at a concrete example. The example comes from my day job
working for the MEMS Exchange, in a greatly simplified version. The
job is to track process runs, which are lists of manufacturing steps
to be performed in a semiconductor fab. A run is owned by a
particular user, and has a name and assigned ID number. Runs consist
of a number of operations; an operation is a single step to be
performed, such as depositing something on a wafer or etching
something off it.
Operations may have parameters, which are additional information
required to perform an operation. For example, if you're depositing
something on a wafer, you need to know two things: 1) what you're
depositing, and 2) how much should be deposited. You might deposit
100 microns of silicon oxide, or 1 micron of copper.
Mapping these structures to a relational database is straightforward:
\begin{verbatim}
CREATE TABLE runs (
int run_id,
varchar owner,
varchar title,
int acct_num,
primary key(run_id)
);
CREATE TABLE operations (
int run_id,
int step_num,
varchar process_id,
PRIMARY KEY(run_id, step_num),
FOREIGN KEY(run_id) REFERENCES runs(run_id),
);
CREATE TABLE parameters (
int run_id,
int step_num,
varchar param_name,
varchar param_value,
PRIMARY KEY(run_id, step_num, param_name)
FOREIGN KEY(run_id, step_num)
REFERENCES operations(run_id, step_num),
);
\end{verbatim}
In Python, you would write three classes named \class{Run},
\class{Operation}, and \class{Parameter}. I won't present code for
defining these classes, since that code is uninteresting at this
point. Each class would contain a single method to begin with, an
\method{__init__} method that assigns default values, such as 0 or
\code{None}, to each attribute of the class.
It's not difficult to write Python code that will create a \class{Run}
instance and populate it with the data from the relational tables;
with a little more effort, you can build a straightforward tool,
usually called an object-relational mapper, to do this automatically.
(See
\url{http://www.amk.ca/python/unmaintained/ordb.html} for a quick hack
at a Python object-relational mapper, and
\url{http://www.python.org/workshops/1997-10/proceedings/shprentz.html}
for Joel Shprentz's more successful implementation of the same idea;
Unlike mine, Shprentz's system has been used for actual work.)
However, it is difficult to make an object-relational mapper
reasonably quick; a simple-minded implementation like mine is quite
slow because it has to do several queries to access all of an object's
data. Higher performance object-relational mappers cache objects to
improve performance, only performing SQL queries when they actually
need to.
That helps if you want to access run number 123 all of a sudden. But
what if you want to find all runs where a step has a parameter named
'thickness' with a value of 2.0? In the relational version, you have
two unappealing choices:
\begin{enumerate}
\item Write a specialized SQL query for this case: \code{SELECT run_id
FROM operations WHERE param_name = 'thickness' AND param_value = 2.0}
If such queries are common, you can end up with lots of specialized
queries. When the database tables get rearranged, all these queries
will need to be modified.
\item An object-relational mapper doesn't help much. Scanning
through the runs means that the the mapper will perform the required
SQL queries to read run \#1, and then a simple Python loop can check
whether any of its steps have the parameter you're looking for.
Repeat for run \#2, 3, and so forth. This does a vast
number of SQL queries, and therefore is incredibly slow.
\end{enumerate}
An object database such as ZODB simply stores internal pointers from
object to object, so reading in a single object is much faster than
doing a bunch of SQL queries and assembling the results. Scanning all
runs, therefore, is still inefficient, but not grossly inefficient.
\subsection{What is ZEO?}
The ZODB comes with a few different classes that implement the
\class{Storage} interface. Such classes handle the job of
writing out Python objects to a physical storage medium, which can be
a disk file (the \class{FileStorage} class), a BerkeleyDB file
(\class{BerkeleyStorage}), a relational database
(\class{DCOracleStorage}), or some other medium. ZEO adds
\class{ClientStorage}, a new \class{Storage} that doesn't write to
physical media but just forwards all requests across a network to a
server. The server, which is running an instance of the
\class{StorageServer} class, simply acts as a front-end for some
physical \class{Storage} class. It's a fairly simple idea, but as
we'll see later on in this document, it opens up many possibilities.
\subsection{About this guide}
The primary author of this guide works on a project which uses the
ZODB and ZEO as its primary storage technology. We use the ZODB to
store process runs and operations, a catalog of available processes,
user information, accounting information, and other data. Part of the
goal of writing this document is to make our experience more widely
available. A few times we've spent hours or even days trying to
figure out a problem, and this guide is an attempt to gather up the
knowledge we've gained so that others don't have to make the same
mistakes we did while learning.
This document will always be a work in progress. If you wish to
suggest clarifications or additional topics, please send your comments to
\email{akuchlin@mems-exchange.org}.
\subsection{Acknowledgements}
I'd like to thank the people who've pointed out inaccuracies and bugs,
offered suggestions on the text, or proposed new topics that should be
covered: Jeff Bauer, Willem Broekema, Thomas Guettler,
Chris McDonough, George Runyan.
% links.tex
% Collection of relevant links
\section{Resources}
ZODB HOWTO, by Michel Pelletier:
\\
Goes into slightly more detail about the rules for writing applications using the ZODB.
\\
\url{http://www.zope.org/Members/michel/HowTos/ZODB-How-To}
Introduction to the Zope Object Database, by Jim Fulton:
\\
Goes into much greater detail, explaining advanced uses of the ZODB and
how it's actually implemented. A definitive reference, and highly recommended.
\\
\url{http://www.python.org/workshops/2000-01/proceedings/papers/fulton/zodb3.html}
Download link for ZEO: \\
\url{http://www.zope.org/Products/ZEO/}
% Related Modules
% PersistentMapping
% PersistentList
% BTree
% Catalog
\section{Related Modules}
The ZODB package includes a number of related modules that provide
useful data types such as BTrees or full-text indexes.
\subsection{\module{ZODB.PersistentMapping}}
The \class{PersistentMapping} class is a wrapper for mapping objects
that will set the dirty bit when the mapping is modified by setting or
deleting a key.
\begin{funcdesc}{PersistentMapping}{container = \{\}}
Create a \class{PersistentMapping} object that wraps the
mapping object \var{container}. If you don't specify a
value for \var{container}, a regular Python dictionary is used.
\end{funcdesc}
\class{PersistentMapping} objects support all the same methods as
Python dictionaries do.
\subsection{\module{ZODB.PersistentList}}
The \class{PersistentList} class is a wrapper for mutable sequence objects,
much as \class{PersistentMapping} is a wrapper for mappings.
\begin{funcdesc}{PersistentList}{initlist = []}
Create a \class{PersistentList} object that wraps the
mutable sequence object \var{initlist}. If you don't specify a
value for \var{initlist}, a regular Python list is used.
\end{funcdesc}
\class{PersistentList} objects support all the same methods as
Python lists do.
\subsection{B-tree Modules}
%here's one: how does one implement searching? i would have expected the
%btree objects to have ``find key nearest to this'' and ``next'' methods,
%(like bsddb's set_location)...
%
% -- erno
When programming with the ZODB, Python dictionaries aren't always what
you need. The most important case is where you want to store a very
large mapping. When a Python dictionary is accessed in a ZODB, the
whole dictionary has to be unpickled and brought into memory. If
you're storing something very large, such as a 100,000-entry user
database, unpickling such a large object will be slow. B-trees are a
balanced tree data structure that behave like a mapping but distribute
keys throughout a number of tree nodes. Nodes are then only unpickled
and brought into memory as they're accessed, so the entire tree
doesn't have to occupy memory (unless you really are touching every
single key).
There are four different BTree modules provided. One of them, the
\module{BTree} module, provides the most general data type; the keys
and values in the B-tree can be any Python object. Some specialized B-tree
modules require that the keys, and perhaps even the values, to be of a
certain type, and provide faster performance because of this limitation.
\begin{itemize}
\item[ \module{IOBTree} ] requires the keys to be integers.
The module name reminds you of this; the \module{IOBTree} module
maps Integers to Objects.
\item[ \module{OIBTree} ] requires the values to be integers,
mapping Objects to Integers.
\item[ \module{IIBTree} ] is strictest, requiring that both keys and values must be integers.
\end{itemize}
To use a B-tree, simply import the desired module and call the
constructor, always named \function{BTree()}, to get a B-tree
instance, and then use it like any other mapping:
\begin{verbatim}
import IIBTree
iimap = IIBTree.BTree()
iimap[1972] = 27
\end{verbatim}
This diff is collapsed.
% Storages
% FileStorage
% BerkeleyStorage
% OracleStorage
\section{Storages}
This chapter will examine the different \class{Storage} subclasses
that are considered stable, discuss their varying characteristics, and
explain how to administer them.
\subsection{Using Multiple Storages}
XXX explain mounting substorages
\subsection{FileStorage}
\subsection{BerkeleyStorage}
\subsection{OracleStorage}
%Transactions and Versioning
% Committing and Aborting
% Subtransactions
% Undoing
% Versions
% Multithreaded ZODB Programs
\section{Transactions and Versioning}
%\subsection{Committing and Aborting}
% XXX There seems very little to say about commit/abort...
\subsection{Subtransactions}
Subtransactions can be created within a transaction. Each
subtransaction can be individually committed and aborted, but the
changes within a subtransaction are not truly committed until the
containing transaction is committed.
The primary purpose of subtransactions is to decrease the memory usage
of transactions that touch a very large number of objects. Consider a
transaction during which 200,000 objects are modified. All the
objects that are modified in a single transaction have to remain in
memory until the transaction is committed, because the ZODB can't
discard them from the object cache. This can potentially make the
memory usage quite large. With subtransactions, a commit can be be
performed at intervals, say, every 10,000 objects. Those 10,000
objects are then written to permanent storage and can be purged from
the cache to free more space.
To commit a subtransaction instead of a full transaction,
pass a true value to the \method{commit()}
or \method{abort()} method of the \class{Transaction} object.
\begin{verbatim}
# Commit a subtransaction
get_transaction().commit(1)
# Abort a subtransaction
get_transaction().abort(1)
\end{verbatim}
A new subtransaction is automatically started on committing or
aborting the previous subtransaction.
\subsection{Undoing Changes}
Some types of \class{Storage} support undoing a transaction even after
it's been committed. You can tell if this is the case by calling the
\method{supportsUndo()} method of the \class{DB} instance, which
returns true if the underlying storage supports undo. Alternatively
you can call the \method{supportsUndo()} method on the underlying
storage instance.
If a database supports undo, then the \method{undoLog(\var{start},
\var{end}\optional{, func})} method on the \class{DB} instance returns
the log of past transactions, returning transactions between the times
\var{start} and \var{end}, measured in seconds from the epoch.
If present, \var{func} is a function that acts as a filter on the
transactions to be returned; it's passed a dictionary representing
each transaction, and only transactions for which \var{func} returns
true will be included in the list of transactions returned to the
caller of \method{undoLog()}. The dictionary contains keys for
various properties of the transaction. The most important keys are
\samp{id}, for the transaction ID, and \samp{time}, for the time at
which the transaction was committed.
\begin{verbatim}
>>> print storage.undoLog(0, sys.maxint)
[{'description': '',
'id': 'AzpGEGqU/0QAAAAAAAAGMA',
'time': 981126744.98,
'user_name': ''},
{'description': '',
'id': 'AzpGC/hUOKoAAAAAAAAFDQ',
'time': 981126478.202,
'user_name': ''}
...
\end{verbatim}
To store a description and a user name on a commit, get the current
transaction and call the \method{note(\var{text})} method to store a
description, and the
\method{setUser(\var{user_name})} method to store the user name.
While \method{setUser()} overwrites the current user name and replaces
it with the new value, the \method{note()} method always adds the text
to the transaction's description, so it can be called several times to
log several different changes made in the course of a single
transaction.
\begin{verbatim}
get_transaction().setUser('amk')
get_transaction().note('Change ownership')
\end{verbatim}
To undo a transaction, call the \method{DB.undo(\var{id})} method,
passing it the ID of the transaction to undo. If the transaction
can't be undone, a \exception{ZODB.POSException.UndoError} exception
will be raised, with the message ``non-undoable
transaction''. Usually this will happen because later transactions
modified the objects affected by the transaction you're trying to
undo.
\subsection{Versions}
While many subtransactions can be contained within a single regular
transaction, it's also possible to contain many regular transactions
within a long-running transaction, called a version in ZODB
terminology. Inside a version, any number of transactions can be
created and committed or rolled back, but the changes within a version
are not made visible to other connections to the same ZODB.
Not all storages support versions, but you can test for versioning
ability by calling \method{supportsVersions()} method of the
\class{DB} instance, which returns true if the underlying storage
supports versioning.
A version can be selected when creating the \class{Connection}
instance using the \method{DB.open(\optional{\var{version}})} method.
The \var{version} argument must be a string that will be used as the
name of the version.
\begin{verbatim}
vers_conn = db.open(version='Working version')
\end{verbatim}
Transactions can then be committed and aborted using this versioned
connection. Other connections that don't specify a version, or
provide a different version name, will not see changes committed
within the version named \samp{Working~version}. To commit or abort a
version, which will either make the changes visible to all clients or
roll them back, call the \method{DB.commitVersion()} or
\method{DB.abortVersion()} methods.
XXX what are the source and dest arguments for?
The ZODB makes no attempt to reconcile changes between different
versions. Instead, the first version which modifies an object will
gain a lock on that object. Attempting to modify the object from a
different version or from an unversioned connection will cause a
\exception{ZODB.POSException.VersionLockError} to be raised:
\begin{verbatim}
from ZODB.POSException import VersionLockError
try:
get_transaction().commit()
except VersionLockError, (obj_id, version):
print ('Cannot commit; object %s '
'locked by version %s' % (obj_id, version))
\end{verbatim}
The exception provides the ID of the locked object, and the name of
the version having a lock on it.
\subsection{Multithreaded ZODB Programs}
ZODB databases can be accessed from multithreaded Python programs.
The \class{Storage} and \class{DB} instances can be shared among
several threads, as long as individual \class{Connection} instances
are created for each thread.
XXX I can't think of anything else to say about multithreaded ZODB
programs. Suggestions? An example program?
This diff is collapsed.
\documentclass{howto}
\title{ZODB/ZEO Programming Guide}
\release{0.03}
\date{\today}
\author{A.M.\ Kuchling}
\authoraddress{akuchlin@mems-exchange.org}
\begin{document}
\maketitle
\tableofcontents
\copyright{Copyright 2002 A.M. Kuchling.
Permission is granted to copy, distribute and/or modify this document
under the terms of the GNU Free Documentation License, Version 1.1
or any later version published by the Free Software Foundation;
with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts.
A copy of the license is included in the appendix entitled ``GNU
Free Documentation License''.}
\input{introduction}
\input{prog-zodb}
\input{zeo}
\input{transactions}
%\input{storages}
%\input{indexing}
%\input{admin}
\input{modules}
\appendix
\input links.tex
\input gfdl.tex
\end{document}
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<LI><A href="node3.html">1.1 What is the ZODB?</a>
<LI><A href="node4.html">1.2 OODBs vs. Relational DBs</a>
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&#169;Copyright 2002 A.M. Kuchling.
Permission is granted to copy, distribute and/or modify this document
under the terms of the GNU Free Documentation License, Version 1.1
or any later version published by the Free Software Foundation;
with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts.
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<h1>ZODB/ZEO Programming Guide</h1>
<p><b><font size="+2">A.M. Kuchling</font></b></p>
<p>akuchlin@mems-exchange.org</p>
<p><strong>Release 0.03</strong><br>
<strong>February 8, 2002</strong></p>
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<LI><A href="node2.html">1 Introduction</a>
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<LI><A href="node3.html">1.1 What is the ZODB?</a>
<LI><A href="node4.html">1.2 OODBs vs. Relational DBs</a>
<LI><A href="node5.html">1.3 What is ZEO?</a>
<LI><A href="node6.html">1.4 About this guide</a>
<LI><A href="node7.html">1.5 Acknowledgements</a>
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<LI><A href="node9.html">2.1 Installing ZODB</a>
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<LI><A href="node13.html">2.3 Opening a ZODB</a>
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<LI><A href="node24.html">3.2 Installing ZEO</a>
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<LI><A href="node26.html">3.2.2 Installation</a>
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<LI><A href="node27.html">3.3 Configuring and Running a ZEO Server</a>
<LI><A href="node28.html">3.4 Testing the ZEO Installation</a>
<LI><A href="node29.html">3.5 ZEO Programming Notes</a>
<LI><A href="node30.html">3.6 Sample Application: chatter.py</a>
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<LI><A href="node31.html">4 Transactions and Versioning</a>
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<LI><A href="node32.html">4.1 Subtransactions</a>
<LI><A href="node33.html">4.2 Undoing Changes</a>
<LI><A href="node34.html">4.3 Versions</a>
<LI><A href="node35.html">4.4 Multithreaded ZODB Programs</a>
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<LI><A href="node36.html">5 Related Modules</a>
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<LI><A href="node37.html">5.1 <tt class="module">ZODB.PersistentMapping</tt></a>
<LI><A href="node38.html">5.2 <tt class="module">ZODB.PersistentList</tt></a>
<LI><A href="node39.html">5.3 B-tree Modules</a>
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<LI><A href="node40.html">A. Resources</a>
<LI><A href="node41.html">B. GNU Free Documentation License</a>
<UL>
<LI><A href="node42.html">Preamble</a>
<LI><A href="node43.html">B..1 Applicability and Definitions</a>
<LI><A href="node44.html">B..2 Verbatim Copying</a>
<LI><A href="node45.html">B..3 Copying in Quantity</a>
<LI><A href="node46.html">B..4 Modifications</a>
<LI><A href="node47.html">B..5 Combining Documents</a>
<LI><A href="node48.html">B..6 Collections of Documents</a>
<LI><A href="node49.html">B..7 Aggregation With Independent Works</a>
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<LI><A href="node51.html">B..9 Termination</a>
<LI><A href="node52.html">B..10 Future Revisions of This Licence</a>
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<H3><A NAME="SECTION000311000000000000000">
2.1.1 Requirements</A>
</H3>
<P>
You'll need Python, of course; version 1.5.2 works with some fixes,
and it also works with Python 2.0, which is what I primarily use.
<P>
The code is packaged using Distutils, the new distribution tools for
Python introduced in Python 2.0. If you're using 1.5.2, first you'll
have to get the latest Distutils release from the Distutils SIG page
at <a class="url" href="http://www.python.org/sigs/distutils-sig/download.html">http://www.python.org/sigs/distutils-sig/download.html</a> and
install it. This is simply a matter of untarring or unzipping the
release package, and then running <code>python setup.py install</code>.
<P>
If you're using 1.5.2 and have installed previous versions of the
Distutils, be sure to get the very latest version, since developing
the ZODB distribution turned up some bugs along the way. If you
encounter problems compiling <span class="file">ZODB/TimeStamp.c</span> or your compiler reports
an error like ``Can't create build/temp.linux2/ExtensionClass.o: No
such file or directory'', you need an updated version. Old versions of
Distutils have two bugs which affect the setup scripts. First, for a
long time the <code>define_macros</code> keyword in setup.py files didn't work due
to a Distutils bug, so I hacked TimeStamp.c in earlier releases. The
Distutils have since been fixed, and the hack became unnecessary, so I
removed it. Second, the code that creates directories tries to be
smart and caches them to save time by not trying to create a directory
twice, but this code was broken in old versions.
<P>
You'll need a C compiler to build the packages, because there are
various C extension modules. At the moment no one is making Windows
binaries available, so you'll need a Windows development environment to use the
<P>
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<H3><A NAME="SECTION000312000000000000000">
2.1.2 Installing the Packages</A>
</H3>
<P>
Download the ZODB tarball containing all the packages for both ZODB
and ZEO from <a class="url" href="http://www.amk.ca/files/zodb/">http://www.amk.ca/files/zodb/</a>.
<P>
To build the packages, you must go into the individual directories and
build and install them one by one. They should be built and installed
in this order:
<P>
<OL>
<LI><code>zodb-basic</code>
</LI>
<LI>ExtensionClass
</LI>
<LI>ZODB
</LI>
<LI><code>BTree</code> and <code>BTrees</code>
</LI>
<LI>ZEO
</LI>
</OL>
<P>
In particular, you must install ExtensionClass before building the
ZODB package; otherwise, the compilation in the ZODB package will die
complaining that it can't find ExtensionClass.h. You can manually
hack the #include path to make it work without installing
ExtensionClass first, but that's a bit hackish.
<P>
If you encounter any problems, please let me know at
<span class="email">akuchlin@mems-exchange.org</span>.
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<H2><A NAME="SECTION000320000000000000000">
2.2 How ZODB Works</A>
</H2>
<P>
The ZODB is conceptually simple. Python classes subclass a
<tt class="class">Persistent</tt> class to become ZODB-aware.
Instances of persistent objects are brought in from a permanent
storage medium, such as a disk file, when the program needs them, and
remain cached in RAM. The ZODB traps modifications to objects, so
that when a statement such as <code>obj.size = 1</code> is executed, the
modified object is marked as ``dirty''. On request, any dirty objects
are written out to permanent storage; this is called committing a
transaction. Transactions can also be aborted or rolled back, which
results in any changes being discarded, dirty objects reverting to
their initial state before the transaction began.
<P>
The term ``transaction'' has a specific technical meaning in computer
science. It's extremely important that the contents of a database
don't get corrupted by software or hardware crashes, and most database
software offers protection against such corruption by supporting four
useful properties, Atomicity, Consistency, Isolation, and Durability.
In computer science jargon these four terms are collectively dubbed
the ACID properties, forming an acronym from their names. The
definitions of the ACID properties are:
<P>
<DL COMPACT>
<DT>Atomicity</DT>
<DD>means that any changes to data made during a transaction
are all-or-nothing. Either all the changes are applied, or none of
them are. If a program makes a bunch of modifications and then
crashes, the database won't be partially modified, potentially leaving
the data in an inconsistent state; instead all the changes will be
forgotten. That's bad, but it's better than having a
partially-applied modification put the database into an inconsistent
state.
<P>
</DD>
<DT>Consistency</DT>
<DD>means that the data cannot be placed into a
logically invalid state; sanity checks can be written and enforced.
Usually this is done by defining a database schema, and requiring the
data always matches the schema. For example, this might enforce that
the <code>order_number</code> attribute is always an integer, and not a
string, tuple, or other object.
<P>
</DD>
<DT>Isolation</DT>
<DD>means that two programs or threads running in two
different transactions cannot see each other's changes until they
commit their transactions.
<P>
</DD>
<DT>Durability</DT>
<DD>means that once a transaction has been committed,
a subsequent crash will not cause any data to be lost or corrupted.
<P>
</DD>
</DL>
<P>
The ZODB provides 3 of the ACID properties. Only Consistency is not
supported; the ZODB has no notion of a database schema, and therefore
has no way of enforcing consistency with a schema.
<P>
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<H2><A NAME="SECTION000330000000000000000">
2.3 Opening a ZODB</A>
</H2>
<P>
There are 3 main interfaces supplied by the ZODB:
<tt class="class">Storage</tt>, <tt class="class">DB</tt>, and <tt class="class">Connection</tt> classes. The
<tt class="class">DB</tt> and <tt class="class">Connection</tt> interfaces both have single
implementations, but there are several different classes that
implement the <tt class="class">Storage</tt> interface.
<P>
<UL>
<LI><tt class="class">Storage</tt> classes are the lowest layer, and handle
storing and retrieving objects from some form of long-term storage.
A few different types of Storage have been written, such as
<tt class="class">FileStorage</tt>, which uses regular disk files, and
<tt class="class">BerkeleyStorage</tt>, which uses Sleepycat Software's BerkeleyDB
database. You could write a new Storage that stored objects in a
relational database or Metakit file, for example, if that would
better suit your application. Two example storages,
<tt class="class">DemoStorage</tt> and <tt class="class">MappingStorage</tt>, are available to use
as models if you want to write a new Storage.
<P>
</LI>
<LI>The <tt class="class">DB</tt> class sits on top of a storage, and mediates the
interaction between several connections. One <tt class="class">DB</tt> instance is
created per process.
<P>
</LI>
<LI>Finally, the <tt class="class">Connection</tt> class caches objects, and moves
them into and out of object storage. A multi-threaded program can
open a separate <tt class="class">Connection</tt> instance for each thread.
Different threads can then modify objects and commit their
modifications independently.
<P>
</LI>
</UL>
<P>
Preparing to use a ZODB requires 3 steps: you have to open the
<tt class="class">Storage</tt>, then create a <tt class="class">DB</tt> instance that uses the <tt class="class">Storage</tt>, and then get
a <tt class="class">Connection</tt> from the <tt class="class">DB instance</tt>. All this is only a few lines of
code:
<P>
<dl><dd><pre class="verbatim">
from ZODB import FileStorage, DB
storage = FileStorage.FileStorage('/tmp/test-filestorage.fs')
db = DB(storage)
conn = db.open()
</pre></dl>
<P>
Note that you can use a completely different data storage mechanism by
changing the first line that opens a <tt class="class">Storage</tt>; the above example uses a
<tt class="class">FileStorage</tt>. In section&nbsp;<A href="zeo.html#zeo">3</A>, ``How ZEO Works'',
you'll see how ZEO uses this flexibility to good effect.
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<H2><A NAME="SECTION000340000000000000000">
2.4 Writing a Persistent Class</A>
</H2>
<P>
Making a Python class persistent is quite simple; it simply needs to
subclass from the <tt class="class">Persistent</tt> class, as shown in this example:
<P>
<dl><dd><pre class="verbatim">
import ZODB
from Persistence import Persistent
class User(Persistent):
pass
</pre></dl>
<P>
The apparently unnecessary <code>import ZODB</code> statement is
needed for the following <code>from...import</code> statement to work
correctly, since the ZODB code does some magical tricks with
importing.
<P>
For simplicity, in the examples the <tt class="class">User</tt> class will
simply be used as a holder for a bunch of attributes. Normally the
class would define various methods that add functionality, but that
has no impact on the ZODB's treatment of the class.
<P>
The ZODB uses persistence by reachability; starting from a set of root
objects, all the attributes of those objects are made persistent,
whether they're simple Python data types or class instances. There's
no method to explicitly store objects in a ZODB database; simply
assign them as an attribute of an object, or store them in a mapping,
that's already in the database. This chain of containment must
eventually reach back to the root object of the database.
<P>
As an example, we'll create a simple database of users that allows
retrieving a <tt class="class">User</tt> object given the user's ID. First, we
retrieve the primary root object of the ZODB using the <tt class="method">root()</tt>
method of the <tt class="class">Connection</tt> instance. The root object behaves
like a Python dictionary, so you can just add a new key/value pair for
your application's root object. We'll insert a <tt class="class">BTree</tt> object
that will contain all the <tt class="class">User</tt> objects. (The
<tt class="class">BTree</tt> module is also included as part of Zope.)
<P>
<dl><dd><pre class="verbatim">
dbroot = conn.root()
# Ensure that a 'userdb' key is present
# in the root
if not dbroot.has_key('userdb'):
import BTree
dbroot['userdb'] = BTree.BTree()
userdb = dbroot['userdb']
</pre></dl>
<P>
Inserting a new user is simple: create the <tt class="class">User</tt> object, fill
it with data, insert it into the <tt class="class">BTree</tt> instance, and commit
this transaction.
<P>
<dl><dd><pre class="verbatim"># Create new User instance
newuser = User()
# Add whatever attributes you want to track
newuser.id = 'amk'
newuser.first_name = 'Andrew' ; newuser.last_name = 'Kuchling'
...
# Add object to the BTree, keyed on the ID
userdb[newuser.id] = newuser
# Commit the change
get_transaction().commit()
</pre></dl>
<P>
When you import the ZODB package, it adds a new function,
<tt class="function">get_transaction()</tt>, to Python's collection of built-in
functions. <tt class="function">get_transaction()</tt> returns a <tt class="class">Transaction</tt>
object, which has two important methods: <tt class="method">commit()</tt> and
<tt class="method">abort()</tt>. <tt class="method">commit()</tt> writes any modified objects
to disk, making the changes permanent, while <tt class="method">abort()</tt> rolls
back any changes that have been made, restoring the original state of
the objects. If you're familiar with database transactional
semantics, this is all what you'd expect.
<P>
Because the integration with Python is so complete, it's a lot like
having transactional semantics for your program's variables, and you
can experiment with transactions at the Python interpreter's prompt:
<P>
<dl><dd><pre class="verbatim">&gt;&gt;&gt; newuser
&lt;User instance at 81b1f40&gt;
&gt;&gt;&gt; newuser.first_name # Print initial value
'Andrew'
&gt;&gt;&gt; newuser.first_name = 'Bob' # Change first name
&gt;&gt;&gt; newuser.first_name # Verify the change
'Bob'
&gt;&gt;&gt; get_transaction().abort() # Abort transaction
&gt;&gt;&gt; newuser.first_name # The value has changed back
'Andrew'
</pre></dl>
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<H2><A NAME="SECTION000350000000000000000">
2.5 Rules for Writing Persistent Classes</A>
</H2>
<P>
Practically all persistent languages impose some restrictions on
programming style, warning against constructs they can't handle or
adding subtle semantic changes, and the ZODB is no exception.
Happily, the ZODB's restrictions are fairly simple to understand, and
in practice it isn't too painful to work around them.
<P>
The summary of rules is as follows:
<P>
<UL>
<LI>If you modify a mutable object that's the value of an object's
attribute, the ZODB can't catch that, and won't mark the object as
dirty.
The solution is to either set the dirty bit yourself when you modify
mutable objects, or use a wrapper for Python's lists and dictionaries
(<tt class="class">PersistentList</tt>,
<tt class="class">PersistentMapping</tt>)
that will set the dirty bit properly.
<P>
</LI>
<LI>Certain of Python's special methods don't work when they're
defined on ExtensionClasses. The most important ones are the
<tt class="method">__cmp__</tt> method, and the reversed versions of binary
arithmetic operations: <tt class="method">__radd__</tt>, <tt class="method">__rsub__</tt>, and so
forth.
<P>
</LI>
<LI>Python's built-in <tt class="function">isinstance()</tt> and <tt class="function">issubclass()</tt>
functions don't work properly on ExtensionClasses. Solution: use
custom <tt class="function">isinstance()</tt> and <tt class="function">issubclass()</tt> functions
that handle ExtensionClasses correctly.
<P>
</LI>
<LI>Recent versions of the ZODB allow writing a class with
<tt class="method">__setattr__</tt> , <tt class="method">__getattr__</tt>, or <tt class="method">__delattr__</tt> methods. (Older versions didn't support this at all.)
If you write such a <tt class="method">__setattr__</tt> or <tt class="method">__delattr__</tt> method,
its code has to set the dirty bit manually,
<P>
</LI>
</UL>
<P>
Let's look at each of these rules in detail.
<P>
<p><hr>
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<LI><A href="node16.html">2.5.1 Modifying Mutable Objects</a>
<LI><A href="node17.html">2.5.2 Some Special Methods Don't Work</a>
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<H3><A NAME="SECTION000351000000000000000">
2.5.1 Modifying Mutable Objects</A>
</H3>
<P>
The ZODB uses various Python hooks to catch attribute accesses, and
can trap most of the ways of modifying an object, but not all of them.
If you modify a <tt class="class">User</tt> object by assigning to one of its
attributes, as in <code>userobj.first_name = 'Andrew'</code>, the ZODB will
mark the object as having been changed, and it'll be written out on
the following <tt class="method">commit()</tt>.
<P>
The most common idiom that <i>isn't</i> caught by the ZODB is
mutating a list or dictionary. If <tt class="class">User</tt> objects have a
attribute named <code>friends</code> containing a list, calling
<code>userobj.friends.append(otherUser)</code> doesn't mark
<code>userobj</code> as modified; from the ZODB's point of
view, <code>userobj.friends</code> was only read, and its value, which
happened to be an ordinary Python list, was returned. The ZODB isn't
aware that the object returned was subsequently modified.
<P>
This is one of the few quirks you'll have to remember when using the
ZODB; if you modify a mutable attribute of an object in place, you
have to manually mark the object as having been modified by setting
its dirty bit to true. This is done by setting the
<tt class="member">_p_changed</tt> attribute of the object to true:
<P>
<dl><dd><pre class="verbatim">
userobj.friends.append(otherUser)
userobj._p_changed = 1
</pre></dl>
<P>
An obsolete way of doing this that's still supported is calling the
<tt class="method">__changed__()</tt> method instead, but setting <tt class="member">_p_changed</tt>
is the preferred way.
<P>
You can hide the implementation detail of having to mark objects as
dirty by designing your class's API to not use direct attribute
access; instead, you can use the Java-style approach of accessor
methods for everything, and then set the dirty bit within the accessor
method. For example, you might forbid accessing the <code>friends</code>
attribute directly, and add a <tt class="method">get_friend_list()</tt> accessor and
an <tt class="method">add_friend()</tt> modifier method to the class. <tt class="method">add_friend()</tt>
would then look like this:
<P>
<dl><dd><pre class="verbatim">
def add_friend(self, friend):
self.friends.append(otherUser)
self._p_changed = 1
</pre></dl>
<P>
Alternatively, you could use a ZODB-aware list or mapping type that
handles the dirty bit for you. The ZODB comes with a
<tt class="class">PersistentMapping</tt> class, and I've contributed a
<tt class="class">PersistentList</tt> class that's included in my ZODB distribution,
and may make it into a future upstream release of Zope.
<P>
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<H3><A NAME="SECTION000352000000000000000">
2.5.2 Some Special Methods Don't Work</A>
</H3>
<P>
Don't bother defining certain special methods on
ExtensionClasses, because they won't work. Most notably, the
<tt class="method">__cmp__</tt> method on an ExtensionClass will never be called.
Neither will the reversed versions of binary arithmetic operations,
such as <tt class="method">__radd__</tt> and <tt class="method">__rsub__</tt>.
<P>
This is a moderately annoying limitation. It means that the
<tt class="class">PersistentList</tt> class can't implement comparisons with regular
sequence objects, and therefore statements such as
<code>if perslist==[]</code> don't do what you expect; instead of performing the correct
comparison, they return some arbitrary fixed result, so the <code>if</code>
statement will always be true or always be false. There is no good
solution to this problem at the moment, so all you can do is design
class interfaces that don't need to overload
<tt class="method">__cmp__</tt> or the <tt class="method">__r*__</tt> methods.
<P>
This limitation is mostly Python's fault. As of Python 2.1, the most
recent version at this writing, the code which handles comparing two
Python objects contains a hard-wired check for objects that are class
instances, which means that <code>type(obj) == types.InstanceType</code>.
The code inside the Python interpreter looks like this:
<P>
<dl><dd><pre class="verbatim">
/* Code to compare objects v and w */
if (PyInstance_Check(v) || PyInstance_Check(w))
return PyInstance_DoBinOp(v, w, "__cmp__", "__rcmp__", do_cmp);
/* Do usual Python comparison of v,w */
c = PyObject_Compare(v, w);
</pre></dl>
<P>
While ExtensionClasses try to behave as much like regular Python
instances as possible, they are still not instances, and
<tt class="function">type()</tt> doesn't return the <code>InstanceType</code> object, so
no attempt is ever made to call <tt class="method">__cmp__</tt>. Perhaps Python 2.2
will repair this.
<P>
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<H3><A NAME="SECTION000353000000000000000">
2.5.3 Fixing <tt class="function">isinstance</tt> and <tt class="function">issubclass</tt></A>
</H3>
<P>
Python's built-in functions
<tt class="function">isinstance()</tt> and <tt class="function">issubclass</tt> don't
work on ExtensionClass instances, for much the same reason that
<tt class="method">__cmp__</tt> is never called; in some bits of the Python core code,
branches are taken only if an object is of the <tt class="class">InstanceType</tt>
type, and this can never be true for an ExtensionClass instance.
Python 2.1 tried to fix this, and changed these functions slightly in
an effort to make them work for ExtensionClasses; unfortunately, the
changes didn't work.
<P>
The solution is to use customized versions of these functions that
handle ExtensionClasses specially and fall back to the built-in
version otherwise. Here are the versions we've written at the MEMS Exchange:
<P>
<dl><dd><pre class="verbatim">
# The built-in 'isinstance()' and 'issubclass()' won't work on
# ExtensionClasses, so you have to use the versions supplied here.
# (But those versions work fine on regular instances and classes too,
# so you should *always* use them.)
def issubclass (class1, class2):
"""A version of 'issubclass' that works with extension classes
as well as regular Python classes.
"""
# Both class objects are regular Python classes, so use the
# built-in 'issubclass()'.
if type(class1) is ClassType and type(class2) is ClassType:
return __builtin__.issubclass(class1, class2)
# Both so-called class objects have a '__bases__' attribute: ie.,
# they aren't regular Python classes, but they sure look like them.
# Assume they are extension classes and reimplement what the builtin
# 'issubclass()' does behind the scenes.
elif hasattr(class1, '__bases__') and hasattr(class2, '__bases__'):
# XXX it appears that "ec.__class__ is type(ec)" for an
# extension class 'ec': could we/should we use this as an
# additional check for extension classes?
# Breadth-first traversal of class1's superclass tree. Order
# doesn't matter because we're just looking for a "yes/no"
# answer from the tree; if we were trying to resolve a name,
# order would be important!
stack = [class1]
while stack:
if stack[0] is class2:
return 1
stack.extend(list(stack[0].__bases__))
del stack[0]
else:
return 0
# Not a regular class, not an extension class: blow up for consistency
# with builtin 'issubclass()"
else:
raise TypeError, "arguments must be class or ExtensionClass objects"
# issubclass ()
def isinstance (object, klass):
"""A version of 'isinstance' that works with extension classes
as well as regular Python classes."""
if type(klass) is TypeType:
return __builtin__.isinstance(object, klass)
elif hasattr(object, '__class__'):
return issubclass(object.__class__, klass)
else:
return 0
</pre></dl>
<P>
I'd recommend putting these functions in a module that always gets
imported. The convention on my work project is to put them in
<span class="file">mems/lib/base.py</span>, which contains various fundamental classes
and functions for our system, and access them like this:
<P>
<dl><dd><pre class="verbatim">
from mems.lib import base
...
if base.isinstance(object, Class): ...
</pre></dl>
<P>
Don't insert the modified functions into Python's
<tt class="module">__builtin__</tt> module, or import just the
<tt class="function">isinstance()</tt> and <tt class="function">issubclass</tt> functions.
If you consistently use <tt class="function">base.isinstance()</tt>, then forgetting
to import the <tt class="module">base</tt> module will result in a
<tt class="exception">NameError</tt> exception. In the
case of a forgotten import, calling the functions directly would use
Python's built-in versions, leading to subtle bugs that might not be
noticed for some time.
<P>
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<H3><A NAME="SECTION000354000000000000000">
2.5.4 <tt class="method">__getattr__</tt>, <tt class="method">__delattr__</tt>, and <tt class="method">__setattr__</tt></A>
</H3>
<P>
Recent versions of ZODB allow writing persistent classes that have
<tt class="method">__getattr__</tt>, <tt class="method">__delattr__</tt>, or <tt class="method">__setattr__</tt>
methods. The one minor complication is that the machinery for
automatically detecting changes to the object is disabled while the
<tt class="method">__getattr__</tt>, <tt class="method">__delattr__</tt>, or <tt class="method">__setattr__</tt>
method is executing. This means that if the object is modified, the
object should be marked as dirty by setting the object's
<tt class="member">_p_changed</tt> method to true.
<P>
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<H1><A NAME="SECTION000200000000000000000">
1 Introduction</A>
</H1>
<P>
This guide explains how to write Python programs that use the Z Object
Database (ZODB) and Zope Enterprise Objects (ZEO). The latest version
of the guide is always available at
<a class="url" href="http://www.amk.ca/zodb/guide/">http://www.amk.ca/zodb/guide/</a>.
<P>
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<LI><A href="node4.html">1.2 OODBs vs. Relational DBs</a>
<LI><A href="node5.html">1.3 What is ZEO?</a>
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<LI><A href="node7.html">1.5 Acknowledgements</a>
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<H2><A NAME="SECTION000360000000000000000">
2.6 Writing Persistent Classes</A>
</H2>
<P>
Now that we've looked at the basics of programming using the ZODB,
we'll turn to some more subtle tasks that are likely to come up for
anyone using the ZODB in a production system.
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<H3><A NAME="SECTION000361000000000000000">
2.6.1 Changing Instance Attributes</A>
</H3>
<P>
Ideally, before making a class persistent you would get its interface
right the first time, so that no attributes would ever need to be
added, removed, or have their interpretation change over time. It's a
worthy goal, but also an impractical one unless you're gifted with
perfect knowledge of the future. Such unnatural foresight can't be
required of any person, so you therefore have to be prepared to handle
such structural changes gracefully. In object-oriented database
terminology, this is a schema update. The ZODB doesn't have an actual
schema specification, but you're changing the software's expectations
of the data contained by an object, so you're implicitly changing the
schema.
<P>
One way to handle such a change is to write a one-time conversion
program that will loop over every single object in the database and
update them to match the new schema. This can be easy if your network
of object references is quite structured, making it easy to find all
the instances of the class being modified. For example, if all
<tt class="class">User</tt> objects can be found inside a single dictionary or
B-tree, then it would be a simple matter to loop over every
<tt class="class">User</tt> instance with a <tt class="keyword">for</tt> statement.
This is more difficult if your object graph is less structured; if
<tt class="class">User</tt> objects can be found as attributes of any number of
different class instances, then there's no longer any easy way to find
them all, short of writing a generalized object traversal function
that would walk over every single object in a ZODB, checking each one
to see if it's an instance of <tt class="class">User</tt>.
<A NAME="tex2html1"
HREF="#foot287"><SUP>1</SUP></A>Some OODBs support a feature called extents, which allow quickly
finding all the instances of a given class, no matter where they are
in the object graph; unfortunately the ZODB doesn't offer extents as a
feature.
<P>
XXX Rest of section not written yet: __getstate__/__setstate__
<P>
<BR><HR><H4>Footnotes</H4>
<DL>
<DT><A NAME="foot287">...User.
</A><A NAME="foot287"
HREF="node21.html#tex2html1"><SUP>1</SUP></A>
<DD>XXX is there a convenience method for walking the object graph hiding
somewhere inside DC's code? Should there be a utility method for
doing this? Should I write one and include it in this section?
</DL>
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<H2><A NAME="SECTION000410000000000000000">
3.1 How ZEO Works</A>
</H2>
<P>
The ZODB, as I've described it so far, can only be used within a
single Python process (though perhaps with multiple threads). ZEO,
Zope Enterprise Objects, extends the ZODB machinery to provide access
to objects over a network. The name "Zope Enterprise Objects" is a
bit misleading; ZEO can be used to store Python objects and access
them in a distributed fashion without Zope ever entering the picture.
The combination of ZEO and ZODB is essentially a Python-specific
object database.
<P>
ZEO consists of about 1400 lines of Python code. The code is
relatively small because it contains only code for a TCP/IP server,
and for a new type of Storage, <tt class="class">ClientStorage</tt>.
<tt class="class">ClientStorage</tt> doesn't use disk files at all; it simply
makes remote procedure calls to the server, which then passes them on
a regular <tt class="class">Storage</tt> class such as <tt class="class">FileStorage</tt>. The
following diagram lays out the system:
<P>
XXX insert diagram here later
<P>
Any number of processes can create a <tt class="class">ClientStorage</tt>
instance, and any number of threads in each process can be using that
instance. <tt class="class">ClientStorage</tt> aggressively caches objects
locally, so in order to avoid using stale data, the ZEO server sends
an invalidate message to all the connected <tt class="class">ClientStorage</tt>
instances on every write operation. The invalidate message contains
the object ID for each object that's been modified, letting the
<tt class="class">ClientStorage</tt> instances delete the old data for the
given object from their caches.
<P>
This design decision has some consequences you should be aware of.
First, while ZEO isn't tied to Zope, it was first written for use with
Zope, which stores HTML, images, and program code in the database. As
a result, reads from the database are <i>far</i> more frequent than
writes, and ZEO is therefore better suited for read-intensive
applications. If every <tt class="class">ClientStorage</tt> is writing to the
database all the time, this will result in a storm of invalidate
messages being sent, and this might take up more processing time than
the actual database operations themselves.
<P>
On the other hand, for applications that have few writes in comparison
to the number of read accesses, this aggressive caching can be a major
win. Consider a Slashdot-like discussion forum that divides the load
among several Web servers. If news items and postings are represented
by objects and accessed through ZEO, then the most heavily accessed
objects - the most recent or most popular postings - will very
quickly wind up in the caches of the
<tt class="class">ClientStorage</tt> instances on the front-end servers. The
back-end ZEO server will do relatively little work, only being called
upon to return the occasional older posting that's requested, and to
send the occasional invalidate message when a new posting is added.
The ZEO server isn't going to be contacted for every single request,
so its workload will remain manageable.
<P>
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3.2 Installing ZEO</A>
</H2>
<P>
This section covers how to install the ZEO package, and how to
configure and run a ZEO Storage Server on a machine.
<P>
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<H3><A NAME="SECTION000421000000000000000">
3.2.1 Requirements</A>
</H3>
<P>
To run a ZEO server, you'll need Python 1.5.2 or 2.0, and the ZODB
packages from <a class="url" href="http://www.amk.ca/files/zodb/">http://www.amk.ca/files/zodb/</a>have to be installed.
<P>
<i>Note for Python 1.5.2 users</i>: ZEO requires updated versions
of the <tt class="module">asyncore.py</tt> and <tt class="module">asynchat.py</tt> modules that are
included in 1.5.2's standard library. Current versions of the ZODB
distribution install private versions of these modules, so you
shouldn't need to grab updated versions yourself. (The symptom of
this problem is a traceback on attempting to run a ZEO client program:
the traceback is ``TypeError: too many arguments; expected 2, got 3''
around line 100 of <span class="file">smac.py</span>.
<P>
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<H3><A NAME="SECTION000422000000000000000">
3.2.2 Installation</A>
</H3>
<P>
Installing the ZEO package is easy. Just run <code>python setup.py
install</code>. This will install the ZEO/ package into your Python
installation, and copy various files into their proper locations:
<span class="file">zeo.conf</span> will be put into <span class="file">/usr/local/etc/</span>, a <span class="file">zeo</span> startup
script will be put in <span class="file">/etc/rc.d/init.d/</span>, and the <span class="file">zeod</span>
daemon program will be placed in <span class="file">/usr/local/bin</span>.
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<H2><A NAME="SECTION000430000000000000000">
3.3 Configuring and Running a ZEO Server</A>
</H2>
<P>
Edit <code>/usr/local/etc/zeo.conf</code> appropriately for your desired
setup. This configuration file controls the port on which ZEO will
listen for connections, the user and group IDs under which the server
will be executed, and the location of the concrete <tt class="class">Storage</tt>
object that will be made network-accessible.
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3.5 ZEO Programming Notes</A>
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XXX The Connection.sync() method and its necessity (if it works at all!)
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