added __doc__ strings etc.

This commit is contained in:
Guido van Rossum 1995-02-09 17:18:10 +00:00
parent 6de668f3aa
commit cc6764c1ba
3 changed files with 172 additions and 49 deletions

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@ -1,9 +1,50 @@
"""A generic interface to all dbm clones."""
"""A generic interface to all dbm clones.
Instead of
import dbm
d = dbm.open(file, 'rw', 0666)
use
import anydbm
d = anydbm.open(file)
The returned object is a dbm, gdbm or (on the Mac) dbmac object,
dependent on availability of the modules (tested in this order).
It has the following interface (key and data are strings):
d[key] = data # store data at key (may override data at
# existing key)
data = d[key] # retrieve data at key (raise KeyError if no
# such key)
del d[key] # delete data stored at key (raises KeyError
# if no such key)
flag = d.has_key(key) # true if the key exists
list = d.keys() # return a list of all existing keys (slow!)
Future versions may change the order in which implementations are
tested for existence, add interfaces to other db-like implementations
(e.g. BSD Hash), and (in the presence of multiple implementations)
decide which module to use based upon the extension or contents of an
existing database file.
The open function has an optional second argument. This can be set to
'r' to open the database for reading only. Don't pas an explicit 'w'
or 'rw' to open it for writing, as the different interfaces have
different interpretation of their mode argument if it isn't 'r'.
"""
try:
import dbm
def open(file, mode = 'rw'):
return dbm.open(file, mode, 0666)
def open(filename, mode = 'rw'):
return dbm.open(filename, mode, 0666)
except ImportError:
import dbmac
open = dbmac.open
try:
import gdbm
def open(filename, mode = 'w'):
return gdbm.open(filename, mode, 0666)
except ImportError:
import dbmac
open = dbmac.open

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@ -1,49 +1,73 @@
# Generic (shallow and deep) copying operations
# =============================================
#
# The difference between shallow and deep copying is only relevant for
# compound objects (objects that contain other objects, like lists or class
# instances).
#
# - A shallow copy constructs a new compound object and then (to the extent
# possible) inserts *the same objects* into in that the original contains.
#
# - A deep copy constructs a new compound object and then, recursively,
# inserts *copies* into it of the objects found in the original.
#
# Two problems often exist with deep copy operations that don't exist with
# shallow copy operations:
#
# (a) recursive objects (compound objects that, directly or indirectly,
# contain a reference to themselves) may cause a recursive loop
#
# (b) because deep copy copies *everything* it may copy too much, e.g.
# administrative data structures that should be shared even between copies
#
# Python's deep copy operation avoids these problems by:
#
# (a) keeping a table of objects already copied during the current copying pass
#
# (b) letting user-defined classes override the copying operation or the set
# of components copied
#
# This version does not copy types like module, class, function, method,
# nor stack trace, stack frame, nor file, socket, window, nor array,
# nor any similar types.
"""\
Generic (shallow and deep) copying operations
=============================================
Interface summary:
import copy
x = copy.copy(y) # make a shallow copy of y
x = copy.deepcopy(y) # make a deep copy of y
For module specific errors, copy.Error is raised.
The difference between shallow and deep copying is only relevant for
compound objects (objects that contain other objects, like lists or
class instances).
- A shallow copy constructs a new compound object and then (to the
extent possible) inserts *the same objects* into in that the
original contains.
- A deep copy constructs a new compound object and then, recursively,
inserts *copies* into it of the objects found in the original.
Two problems often exist with deep copy operations that don't exist
with shallow copy operations:
(a) recursive objects (compound objects that, directly or indirectly,
contain a reference to themselves) may cause a recursive loop
(b) because deep copy copies *everything* it may copy too much, e.g.
administrative data structures that should be shared even between
copies
Python's deep copy operation avoids these problems by:
(a) keeping a table of objects already copied during the current
copying pass
(b) letting user-defined classes override the copying operation or the
set of components copied
This version does not copy types like module, class, function, method,
nor stack trace, stack frame, nor file, socket, window, nor array, nor
any similar types.
Classes can use the same interfaces to control copying that they use
to control pickling: they can define methods called __getinitargs__(),
__getstate__() and __setstate__(). See the __doc__ string of module
"pickle" for information on these methods.
"""
import types
Error = 'copy.Error'
def copy(x):
"""Shallow copy operation on arbitrary Python objects.
See the module's __doc__ string for more info.
"""
try:
copierfunction = _copy_dispatch[type(x)]
except KeyError:
try:
copier = x.__copy__
except AttributeError:
raise Error, "un(shallow)copyable object of type %s" % type(x)
raise Error, \
"un(shallow)copyable object of type %s" % type(x)
y = copier()
else:
y = copierfunction(x)
@ -100,6 +124,11 @@ d[types.InstanceType] = _copy_inst
del d
def deepcopy(x, memo = None):
"""Deep copy operation on arbitrary Python objects.
See the module's __doc__ string for more info.
"""
if memo is None:
memo = {}
d = id(x)
@ -111,7 +140,8 @@ def deepcopy(x, memo = None):
try:
copier = x.__deepcopy__
except AttributeError:
raise Error, "un-deep-copyable object of type %s" % type(x)
raise Error, \
"un-deep-copyable object of type %s" % type(x)
y = copier(memo)
else:
y = copierfunction(x, memo)

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@ -1,9 +1,43 @@
"""Manage shelves of pickled objects."""
"""Manage shelves of pickled objects.
A "shelf" is a persistent, dictionary-like object. The difference
with dbm databases is that the values (not the keys!) in a shelf can
be essentially arbitrary Python objects -- anything that the "pickle"
module can handle. This includes most class instances, recursive data
types, and objects containing lots of shared sub-objects. The keys
are ordinary strings.
To summarize the interface (key is a string, data is an arbitrary
object):
import shelve
d = shelve.open(filename) # open, with (g)dbm filename
d[key] = data # store data at key (overwrites old data if
# using an existing key)
data = d[key] # retrieve data at key (raise KeyError if no
# such key)
del d[key] # delete data stored at key (raises KeyError
# if no such key)
flag = d.has_key(key) # true if the key exists
list = d.keys() # a list of all existing keys (slow!)
d.close() # close it
Dependent on the implementation, closing a persistent dictionary may
or may not be necessary to flush changes to disk.
"""
import pickle
import StringIO
class Shelf:
"""Base class for shelf implementations.
This is initialized with a dictionary-like object.
See the module's __doc__ string for an overview of the interface.
"""
def __init__(self, dict):
self.dict = dict
@ -18,7 +52,8 @@ class Shelf:
return self.dict.has_key(key)
def __getitem__(self, key):
return pickle.Unpickler(StringIO.StringIO(self.dict[key])).load()
f = StringIO.StringIO(self.dict[key])
return pickle.Unpickler(f).load()
def __setitem__(self, key, value):
f = StringIO.StringIO()
@ -30,14 +65,31 @@ class Shelf:
del self.dict[key]
def close(self):
self.db.close()
if hasattr(self.db, 'close'):
self.db.close()
self.db = None
class DbShelf(Shelf):
def __init__(self, file):
import anydbm
Shelf.__init__(self, anydbm.open(file))
def __del__(self):
self.close()
def open(file):
return DbShelf(file)
class DbShelf(Shelf):
"""Shelf implementation using the "anydbm" generic dbm interface.
This is initialized with the filename for the dbm database.
See the module's __doc__ string for an overview of the interface.
"""
def __init__(self, filename):
import anydbm
Shelf.__init__(self, anydbm.open(filename))
def open(filename):
"""Open a persistent dictionary for reading and writing.
Argument is the filename for the dbm database.
See the module's __doc__ string for an overview of the interface.
"""
return DbShelf(filename)