[Spambayes-checkins] spambayes/spambayes storage.py,1.17,1.18

[Tony Meyer]

Update of /cvsroot/spambayes/spambayes/spambayes
In directory sc8-pr-cvs1:/tmp/cvs-serv26785/spambayes

Modified Files:
	storage.py 
Log Message:
Add a MySQLdb based classifier.

Index: storage.py
===================================================================
RCS file: /cvsroot/spambayes/spambayes/spambayes/storage.py,v
retrieving revision 1.17
retrieving revision 1.18
diff -C2 -d -r1.17 -r1.18
*** storage.py	7 Aug 2003 01:39:12 -0000	1.17
--- storage.py	7 Aug 2003 05:04:09 -0000	1.18
***************
*** 6,9 ****
--- 6,11 ----
      PickledClassifier - Classifier that uses a pickle db
      DBDictClassifier - Classifier that uses a shelve db
+     PGClassifier - Classifier that uses postgres
+     mySQLClassifier - Classifier that uses mySQL
      Trainer - Classifier training observer
      SpamTrainer - Trainer for spam
***************
*** 13,16 ****
--- 15,20 ----
      *Classifier are subclasses of Classifier (classifier.Classifier)
      that add automatic state store/restore function to the Classifier class.
+     All SQL based classifiers are subclasses of SQLClassifier, which is a
+     subclass of Classifier.
  
      PickledClassifier is a Classifier class that uses a cPickle
***************
*** 412,415 ****
--- 416,502 ----
              self.nspam = 0
              self.nham = 0
+ 
+ 
+ class mySQLClassifier(SQLClassifier):
+     '''Classifier object persisted in a mySQL database
+ 
+     It is assumed that the database already exists, and that the mySQL
+     server is currently running.'''
+  
+     def __init__(self, data_source_name):
+         self.table_definition = ("create table bayes ("
+                                  "  word varchar(255) not null default '',"
+                                  "  nspam integer not null default 0,"
+                                  "  nham integer not null default 0,"
+                                  "  primary key(word)"
+                                  ");")
+         self.host = "localhost"
+         self.username = "root"
+         self.password = ""
+         db_name = "spambayes"
+         source_info = data_source_name.split()
+         for info in source_info:
+             if info.startswith("host"):
+                 self.host = info[5:]
+             elif info.startswith("user"):
+                 self.username = info[5:]
+             elif info.startswith("pass"):
+                 self.username = info[5:]
+             elif info.startswith("dbname"):
+                 db_name = info[7:]
+         SQLClassifier.__init__(self, db_name)
+ 
+     def cursor(self):
+         return self.db.cursor()
+ 
+     def fetchall(self, c):
+         return c.fetchall()
+ 
+     def commit(self, c):
+         self.db.commit()
+ 
+     def load(self):
+         '''Load state from database'''
+ 
+         import MySQLdb
+         
+         if options.verbose:
+             print 'Loading state from',self.db_name,'database'
+ 
+         self.db = MySQLdb.connect(host=self.host, db=self.db_name,
+                                   user=self.username, passwd=self.password)
+ 
+         c = self.cursor()
+         try:
+             c.execute("select count(*) from bayes")
+         except MySQLdb.ProgrammingError:
+             self.db.rollback()
+             self.create_bayes()
+         
+         if self._has_key(self.statekey):
+             row = self._get_row(self.statekey)
+             self.nspam = int(row[1])
+             self.nham = int(row[2])
+             if options.verbose:
+                 print '%s is an existing database, with %d spam and %d ham' \
+                       % (self.db_name, self.nspam, self.nham)
+         else:
+             # new database
+             if options.verbose:
+                 print self.db_name,'is a new database'
+             self.nspam = 0
+             self.nham = 0
+ 
+     def _wordinfoget(self, word):
+         if isinstance(word, unicode):
+             word = word.encode("utf-8")
+ 
+         row = self._get_row(word)
+         if row:
+             item = self.WordInfoClass()
+             item.__setstate__((row[1], row[2]))
+             return item
+         else:
+             return None