Designing for Reuse and Growth

I admit it: PyErrata may be thrifty, but it's also a bit self-centered. The database interfaces presented in the prior sections work as planned and serve to separate all database processing from CGI scripting details. But as shown in this book, these interfaces aren't as generally reusable as they could be; moreover, they are not yet designed to scale up to larger database applications.

Let's wrap up this chapter by donning our software code review hats for just a few moments and exploring some design alternatives for PyErrata. In this section, I highlight the PyErrata database interface's obstacles to general applicability, not as self-deprecation, but to show how programming decisions can impact reusability.

Something else is going on in this section too. There is more concept than code here, and the code that is here is more like an experimental design than a final product. On the other hand, because that design is coded in Python, it can be run to test the feasibility of design alternatives; as we've seen, Python can be used as a form of executable pseudocode.

14.8.1 Reusability

As we saw, code reuse is pervasive within PyErrata: top-level calls filter down to common browse and submit modules, which in turn call database classes that reuse a common module. But what about sharing PyErrata code with other systems? Although not designed with generality in mind, PyErrata's database interface modules could almost be reused to implement other kinds of file- and shelve-based databases outside the context of PyErrata itself. However, we need a few more tweaks to turn these interfaces into widely useful tools.

As is, shelve and file-directory names are hardcoded into the storage-specific subclass modules, but another system could import and reuse their Dbase classes and provide different directory names. Less generally, though, the dbcommon module adds two attributes to all new records (submit-time and report-state) that may or may not be relevant outside PyErrata. It also assumes that stored values are mappings (dictionaries), but that is less PyErrata-specific.

If we were to rewrite these classes for more general use, it would make sense to first repackage the four DbaseErrata and DbaseComment classes in modules of their own (they are very specific instances of file and shelve databases). We would probably also want to somehow relocate dbcommon's insertion of submit-time and report-state attributes from the dbcommon module to these four classes themselves (these attributes are specific to PyErrata databases). For instance, we might define a new DbasePyErrata class that sets these attributes and is a mixed-in superclass to the four PyErrata storage-specific database classes:

# in new module
class DbasePyErrata:
 def storeItem(self, newdata):
 secsSinceEpoch = time.time( )
 timeTuple = time.localtime(secsSinceEpoch)
 y_m_d_h_m_s = timeTuple[:6] 
 newdata['Submit date'] = '%s/%02d/%02d, %02d:%02d:%02d' % y_m_d_h_m_s
 newdata['Report state'] = 'Not yet verified'

# in dbshelve
class Dbase(MutexCntl, dbcommon.Dbase):
 # as is

# in dbfiles
class Dbase(dbcommon.Dbase):
 # as is

# in new file module
class DbaseErrata(DbasePyErrata, dbfiles.Dbase):
 dirname = 'DbaseFiles/errataDB/'
class DbaseComment(DbasePyErrata, dbfiles.Dbase):
 dirname = 'DbaseFiles/commentDB/'

# in new shelve module
class DbaseErrata(DbasePyErrata, dbshelve.Dbase):
 filename = 'DbaseShelve/errataDB'
class DbaseComment(DbasePyErrata, dbshelve.Dbase):
 filename = 'DbaseShelve/commentDB'

There are more ways to structure this than we have space to cover here. The point is that by factoring out application-specific code, dbshelve and dbfiles modules not only serve to keep PyErrata interface and database code distinct, but also become generally useful data-storage tools.

14.8.2 Scalability

PyErrata's database interfaces were designed for this specific application's storage requirements alone and don't directly support very large databases. If you study the database code carefully, you'll notice that submit operations update a single item, but browse requests load entire report databases all at once into memory. This scheme works fine for the database sizes expected in PyErrata, but performs badly for larger data sets. We could extend the database classes to handle larger data sets too, but they would likely require new top-level interfaces altogether.

Before I stopped updating it, the static HTML file used to list errata from the first edition of this book held just some 60 reports, and I expect a similarly small data set for other books and editions. With such small databases, it's reasonable to load an entire database into memory (i.e., into Python lists and dictionaries) all at once, and frequently. Indeed, the time needed to transfer a web page containing 60 records across the Internet likely outweighs the time it takes to load 60 report files or shelve keys on the server.

On the other hand, the database may become too slow if many more reports than expected are posted. There isn't much we could do to optimize the "Simple list" and "With index" display options, since they really do display all records. But for the "Index only" option, we might be able to change our classes to load only records having a selected value in the designated report field.

For instance, we could work around database load bottlenecks by changing our classes to implement delayed loading of records: rather than returning the real database, load requests could return objects that look the same but fetch actual records only when needed. Such an approach might require no changes in the rest of the system's code, but may be complex to implement. Multiple shelve field indexing

Perhaps a better approach would be to define an entirely new top-level interface for the "Index only" option -- one that really does load only records matching a field value query. For instance, rather than storing all records in a single shelve, we could implement the database as a set of index shelves, one per record field, to associate records by field values. Index shelve keys would be values of the associated field; shelve values would be lists of records having that field value. The shelve entry lists might contain either redundant copies of records, or unique names of flat files holding the pickled record dictionaries, external to the index shelves (as in the current flat-file model).

For example, the PyErrata comment database could be structured as a directory of flat files to hold pickled report dictionaries, together with five shelves to index the values in all record fields (submitter-name, submitter-email, submit-mode, submit-date, report-state). In the report-state shelve, there would be one entry for each possible report state (verified, rejected, etc.); each entry would contain a list of records with just that report-state value. Field value queries would be fast, but store and load operations would become more complex:

  • To store a record in such a scheme, we would first pickle it to a uniquely named flat file, then insert that file's name into lists in all five shelves, using each field's value as shelve key.
  • To load just the records matching a field/value combination, we would first index that field's shelve on the value to fetch a filename list, and step through that list to load matching records only, from flat pickle files.

Let's take the leap from hypothetical to concrete, and prototype these ideas in Python. If you're following closely, you'll notice that what we're really talking about here is an extension to the flat-file database structure, one that merely adds index shelves. Hence, one possible way to implement the model is as a subclass of the current flat-file classes. Example 14-31 does just that, as proof of the design concept.

Example 14-31.

# add field index shelves to flat-file database mechanism;
# to optimize "index only" displays, use classes at end of this file;
# change browse, index, submit to use new loaders for "Index only" mode;
# minor nit: uses single lock file for all index shelve read/write ops;
# storing record copies instead of filenames in index shelves would be
# slightly faster (avoids opening flat files), but would take more space;
# falls back on original brute-force load logic for fields not indexed;
# creates empty file if doesn't yet exist, so never fails;
# to start, create DbaseFilesIndex/{commentDB,errataDB}/indexes.lck;

import sys; sys.path.insert(0, '..') # check admin parent dir first
from Mutex import mutexcntl # fcntl path okay: not 'nobody'
import dbfiles, shelve, pickle, string, sys

class Dbase(mutexcntl.MutexCntl, dbfiles.Dbase):
 def makeKey(self):
 return self.cachedKey
 def cacheKey(self): # save filename
 self.cachedKey = dbfiles.Dbase.makeKey(self) # need it here too
 return self.cachedKey

 def indexName(self, fieldname):
 return self.dirname + string.replace(fieldname, ' ', '-')

 def safeWriteIndex(self, fieldname, newdata, recfilename):
 index =
 keyval = newdata[fieldname] # recs have all fields
 reclist = index[keyval] # fetch, mod, rewrite
 reclist.append(recfilename) # add to current list
 index[keyval] = reclist
 except KeyError:
 index[keyval] = [recfilename] # add to new list

 def safeLoadKeysList(self, fieldname):
 if fieldname in self.indexfields:
 keys = )
 keys.sort( )
 keys, index = self.loadIndexedTable(fieldname)
 return keys

 def safeLoadByKey(self, fieldname, fieldvalue):
 if fieldname in self.indexfields:
 dbase =
 index = dbase[fieldvalue]
 reports = []
 for filename in index:
 pathname = self.dirname + filename + '.data'
 reports.append(pickle.load(open(pathname, 'r')))
 return reports 
 except KeyError:
 return []
 key, index = self.loadIndexedTable(fieldname)
 return index[fieldvalue]
 except KeyError:
 return []

 # top-level interfaces (plus dbcommon and dbfiles)

 def writeItem(self, newdata): 
 # extend to update indexes
 filename = self.cacheKey( )
 dbfiles.Dbase.writeItem(self, newdata)
 for fieldname in self.indexfields:
 fieldname, newdata, filename) 

 def loadKeysList(self, fieldname): 
 # load field's keys list only
 return self.sharedAction(self.safeLoadKeysList, fieldname)

 def loadByKey(self, fieldname, fieldvalue): 
 # load matching recs lisy only
 return self.sharedAction(self.safeLoadByKey, fieldname, fieldvalue)

class DbaseErrata(Dbase):
 dirname = 'DbaseFilesIndexed/errataDB/'
 filename = dirname + 'indexes'
 indexfields = ['Submitter name', 'Submit date', 'Report state']

class DbaseComment(Dbase): 
 dirname = 'DbaseFilesIndexed/commentDB/'
 filename = dirname + 'indexes'
 indexfields = ['Submitter name', 'Report state'] # index just these

# self-test

if __name__ == '__main__': 
 import os 
 dbase = DbaseComment( )
 os.system('rm %s*' % dbase.dirname) # empty dbase dir
 os.system('echo > %s.lck' % dbase.filename) # init lock file
 # 3 recs; normally have submitter-email and description, not page 
 # submit-date and report-state are added auto by rec store method
 records = [{'Submitter name': 'Bob', 'Page': 38, 'Submit mode': ''},
 {'Submitter name': 'Brian', 'Page': 40, 'Submit mode': ''},
 {'Submitter name': 'Bob', 'Page': 42, 'Submit mode': 'email'}]
 for rec in records: dbase.storeItem(rec)

 dashes = '-'*80
 def one(item):
 print dashes; print item
 def all(list): 
 print dashes
 for x in list: print x

 one('old stuff')
 all(dbase.loadSortedTable('Submitter name')) # load flat list
 all(dbase.loadIndexedTable('Submitter name')) # load, grouped
 #one(dbase.loadIndexedTable('Submitter name')[0])
 #all(dbase.loadIndexedTable('Submitter name')[1]['Bob'])
 #all(dbase.loadIndexedTable('Submitter name')[1]['Brian'])

 one('new stuff')
 one(dbase.loadKeysList('Submitter name')) # bob, brian
 all(dbase.loadByKey('Submitter name', 'Bob')) # two recs match
 all(dbase.loadByKey('Submitter name', 'Brian')) # one rec mathces
 one(dbase.loadKeysList('Report state')) # all match
 all(dbase.loadByKey('Report state', 'Not yet verified')) 

 one('boundary cases')
 all(dbase.loadByKey('Submit mode', '')) # not indexed: load
 one(dbase.loadByKey('Report state', 'Nonesuch')) # unknown value: []
 try: dbase.loadByKey('Nonesuch', 'Nonesuch') # bad fields: exc
 except: print 'Nonesuch failed'

This module's code is something of an executable prototype, but that's much of the point here. The fact that we can actually run experiments coded in Python helps pinpoint problems in a model early on.

For instance, I had to redefine the makeKey method here to cache filenames locally (they are needed for index shelves too). That's not quite right, and if I were to adopt this database interface, I would probably change the file class to return generated filenames, not discard them. Such misfits can often be uncovered only by writing real code -- a task that Python optimizes by design.

If this module is run as a top-level script, its self-test code at the bottom of the file executes with the following output. I don't have space to explain it in detail, but try to match it up with the module's self-test code to trace how queries are satisfied with and without field indexes:

[mark@toy .../Internet/Cgi-Web/PyErrata/AdminTools]$ python 
old stuff
{'Submit date': '2000/06/13, 11:45:01', 'Page': 38, 'Submit mode': '', 'Report s
tate': 'Not yet verified', 'Submitter name': 'Bob'}
{'Submit date': '2000/06/13, 11:45:01', 'Page': 42, 'Submit mode': 'email', 'Rep
ort state': 'Not yet verified', 'Submitter name': 'Bob'}
{'Submit date': '2000/06/13, 11:45:01', 'Page': 40, 'Submit mode': '', 'Report s
tate': 'Not yet verified', 'Submitter name': 'Brian'}
['Bob', 'Brian']
{'Bob': [{'Submit date': '2000/06/13, 11:45:01', 'Page': 38, 'Submit mode': '',
'Report state': 'Not yet verified', 'Submitter name': 'Bob'}, {'Submit date': '2
000/06/13, 11:45:01', 'Page': 42, 'Submit mode': 'email', 'Report state': 'Not y
et verified', 'Submitter name': 'Bob'}], 'Brian': [{'Submit date': '2000/06/13, 
11:45:01', 'Page': 40, 'Submit mode': '', 'Report state': 'Not yet verified', 'S
ubmitter name': 'Brian'}]}
new stuff
['Bob', 'Brian']
{'Submit date': '2000/06/13, 11:45:01', 'Page': 38, 'Submit mode': '', 'Report s
tate': 'Not yet verified', 'Submitter name': 'Bob'}
{'Submit date': '2000/06/13, 11:45:01', 'Page': 42, 'Submit mode': 'email', 'Rep
ort state': 'Not yet verified', 'Submitter name': 'Bob'}
{'Submit date': '2000/06/13, 11:45:01', 'Page': 40, 'Submit mode': '', 'Report s
tate': 'Not yet verified', 'Submitter name': 'Brian'}
['Not yet verified']
{'Submit date': '2000/06/13, 11:45:01', 'Page': 38, 'Submit mode': '', 'Report s
tate': 'Not yet verified', 'Submitter name': 'Bob'}
{'Submit date': '2000/06/13, 11:45:01', 'Page': 40, 'Submit mode': '', 'Report s
tate': 'Not yet verified', 'Submitter name': 'Brian'}
{'Submit date': '2000/06/13, 11:45:01', 'Page': 42, 'Submit mode': 'email', 'Rep
ort state': 'Not yet verified', 'Submitter name': 'Bob'}
boundary cases
{'Submit date': '2000/06/13, 11:45:01', 'Page': 38, 'Submit mode': '', 'Report s
tate': 'Not yet verified', 'Submitter name': 'Bob'}
{'Submit date': '2000/06/13, 11:45:01', 'Page': 40, 'Submit mode': '', 'Report s
tate': 'Not yet verified', 'Submitter name': 'Brian'}
Nonesuch failed

[mark@toy .../PyErrata/AdminTools]$ ls DbaseFilesIndexed/commentDB/ Submitter-name indexes.log Report-state indexes.lck

[mark@toy .../PyErrata/AdminTools]$ more DbaseFilesIndexed/commentDB/indexes.log 
960918301.266 Requested: 895, writer
960918301.266 Aquired: 895
960918301.36 Released: 895
960918301.36 Requested: 895, writer
960918301.361 Aquired: 895
960918301.419 Released: 895
960918301.422 Requested: 895, writer
960918301.422 Aquired: 895
960918301.46 Released: 895

One drawback to this interface is that it works only on a machine that supports the fcntl.flock call (notice that I ran the previous test on Linux). If you want to use these classes to support indexed file/shelve databases on other machines, you could delete or stub out this call in the mutex module to do nothing and return. You won't get safe updates if you do, but many applications don't need to care:

 import fcntl
 from FCNTL import *
except ImportError:
 class fakeFcntl:
 def flock(self, fileno, flag): return
 fcntl = fakeFcntl( )

You might instead instrument MutexCntl.lockFile to do nothing in the presence of a command-line argument flag, mix in a different MutexCntl class at the bottom that does nothing on lock calls, or hunt for platform-specific locking mechanisms (e.g., the Windows extensions package exports a Windows-only file locking call; see its documentation for details).

Regardless of whether you use locking or not, the dbaseindexed flat-files plus multiple-shelve indexing scheme can speed access by keys for large databases. However, it would also require changes to the top-level CGI script logic that implements "Index only" displays, and so is not without seams. It may also perform poorly for very large databases, as record information would span multiple files. If pressed, we could finally extend the database classes to talk to a real database system such as Oracle, MySQL, PostGres, or Gadfly (described in Chapter 16).

All of these options are not without trade-offs, but we have now come dangerously close to stepping beyond the scope of this chapter. Because the PyErrata database modules were designed with neither general applicability nor broad scalability in mind, additional mutations are left as suggested exercises.

Introducing Python

Part I: System Interfaces

System Tools

Parallel System Tools

Larger System Examples I

Larger System Examples II

Part II: GUI Programming

Graphical User Interfaces

A Tkinter Tour, Part 1

A Tkinter Tour, Part 2

Larger GUI Examples

Part III: Internet Scripting

Network Scripting

Client-Side Scripting

Server-Side Scripting

Larger Web Site Examples I

Larger Web Site Examples II

Advanced Internet Topics

Part IV: Assorted Topics

Databases and Persistence

Data Structures

Text and Language

Part V: Integration

Extending Python

Embedding Python

VI: The End

Conclusion Python and the Development Cycle

Programming Python
Python Programming for the Absolute Beginner, 3rd Edition
ISBN: 1435455002
EAN: 2147483647
Year: 2000
Pages: 245 © 2008-2020.
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