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353 lines
9.7 KiB
Python
353 lines
9.7 KiB
Python
2 years ago
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#!/usr/bin/env python
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""" PickleShare - a small 'shelve' like datastore with concurrency support
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Like shelve, a PickleShareDB object acts like a normal dictionary. Unlike
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shelve, many processes can access the database simultaneously. Changing a
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value in database is immediately visible to other processes accessing the
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same database.
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Concurrency is possible because the values are stored in separate files. Hence
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the "database" is a directory where *all* files are governed by PickleShare.
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Example usage::
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from pickleshare import *
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db = PickleShareDB('~/testpickleshare')
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db.clear()
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print "Should be empty:",db.items()
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db['hello'] = 15
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db['aku ankka'] = [1,2,313]
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db['paths/are/ok/key'] = [1,(5,46)]
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print db.keys()
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del db['aku ankka']
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This module is certainly not ZODB, but can be used for low-load
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(non-mission-critical) situations where tiny code size trumps the
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advanced features of a "real" object database.
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Installation guide: pip install pickleshare
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Author: Ville Vainio <vivainio@gmail.com>
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License: MIT open source license.
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"""
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from __future__ import print_function
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__version__ = "0.7.5"
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try:
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from pathlib import Path
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except ImportError:
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# Python 2 backport
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from pathlib2 import Path
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import os,stat,time
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try:
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import collections.abc as collections_abc
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except ImportError:
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import collections as collections_abc
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try:
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import cPickle as pickle
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except ImportError:
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import pickle
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import errno
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import sys
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if sys.version_info[0] >= 3:
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string_types = (str,)
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else:
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string_types = (str, unicode)
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def gethashfile(key):
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return ("%02x" % abs(hash(key) % 256))[-2:]
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_sentinel = object()
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class PickleShareDB(collections_abc.MutableMapping):
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""" The main 'connection' object for PickleShare database """
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def __init__(self,root):
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""" Return a db object that will manage the specied directory"""
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if not isinstance(root, string_types):
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root = str(root)
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root = os.path.abspath(os.path.expanduser(root))
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self.root = Path(root)
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if not self.root.is_dir():
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# catching the exception is necessary if multiple processes are concurrently trying to create a folder
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# exists_ok keyword argument of mkdir does the same but only from Python 3.5
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try:
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self.root.mkdir(parents=True)
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except OSError as e:
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if e.errno != errno.EEXIST:
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raise
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# cache has { 'key' : (obj, orig_mod_time) }
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self.cache = {}
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def __getitem__(self,key):
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""" db['key'] reading """
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fil = self.root / key
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try:
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mtime = (fil.stat()[stat.ST_MTIME])
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except OSError:
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raise KeyError(key)
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if fil in self.cache and mtime == self.cache[fil][1]:
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return self.cache[fil][0]
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try:
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# The cached item has expired, need to read
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with fil.open("rb") as f:
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obj = pickle.loads(f.read())
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except:
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raise KeyError(key)
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self.cache[fil] = (obj,mtime)
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return obj
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def __setitem__(self,key,value):
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""" db['key'] = 5 """
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fil = self.root / key
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parent = fil.parent
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if parent and not parent.is_dir():
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parent.mkdir(parents=True)
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# We specify protocol 2, so that we can mostly go between Python 2
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# and Python 3. We can upgrade to protocol 3 when Python 2 is obsolete.
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with fil.open('wb') as f:
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pickle.dump(value, f, protocol=2)
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try:
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self.cache[fil] = (value, fil.stat().st_mtime)
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except OSError as e:
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if e.errno != errno.ENOENT:
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raise
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def hset(self, hashroot, key, value):
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""" hashed set """
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hroot = self.root / hashroot
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if not hroot.is_dir():
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hroot.mkdir()
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hfile = hroot / gethashfile(key)
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d = self.get(hfile, {})
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d.update( {key : value})
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self[hfile] = d
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def hget(self, hashroot, key, default = _sentinel, fast_only = True):
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""" hashed get """
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hroot = self.root / hashroot
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hfile = hroot / gethashfile(key)
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d = self.get(hfile, _sentinel )
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#print "got dict",d,"from",hfile
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if d is _sentinel:
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if fast_only:
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if default is _sentinel:
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raise KeyError(key)
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return default
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# slow mode ok, works even after hcompress()
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d = self.hdict(hashroot)
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return d.get(key, default)
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def hdict(self, hashroot):
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""" Get all data contained in hashed category 'hashroot' as dict """
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hfiles = self.keys(hashroot + "/*")
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hfiles.sort()
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last = len(hfiles) and hfiles[-1] or ''
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if last.endswith('xx'):
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# print "using xx"
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hfiles = [last] + hfiles[:-1]
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all = {}
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for f in hfiles:
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# print "using",f
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try:
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all.update(self[f])
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except KeyError:
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print("Corrupt",f,"deleted - hset is not threadsafe!")
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del self[f]
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self.uncache(f)
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return all
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def hcompress(self, hashroot):
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""" Compress category 'hashroot', so hset is fast again
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hget will fail if fast_only is True for compressed items (that were
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hset before hcompress).
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"""
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hfiles = self.keys(hashroot + "/*")
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all = {}
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for f in hfiles:
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# print "using",f
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all.update(self[f])
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self.uncache(f)
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self[hashroot + '/xx'] = all
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for f in hfiles:
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p = self.root / f
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if p.name == 'xx':
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continue
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p.unlink()
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def __delitem__(self,key):
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""" del db["key"] """
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fil = self.root / key
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self.cache.pop(fil,None)
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try:
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fil.unlink()
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except OSError:
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# notfound and permission denied are ok - we
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# lost, the other process wins the conflict
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pass
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def _normalized(self, p):
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""" Make a key suitable for user's eyes """
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return str(p.relative_to(self.root)).replace('\\','/')
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def keys(self, globpat = None):
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""" All keys in DB, or all keys matching a glob"""
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if globpat is None:
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files = self.root.rglob('*')
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else:
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files = self.root.glob(globpat)
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return [self._normalized(p) for p in files if p.is_file()]
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def __iter__(self):
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return iter(self.keys())
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def __len__(self):
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return len(self.keys())
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def uncache(self,*items):
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""" Removes all, or specified items from cache
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Use this after reading a large amount of large objects
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to free up memory, when you won't be needing the objects
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for a while.
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"""
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if not items:
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self.cache = {}
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for it in items:
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self.cache.pop(it,None)
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def waitget(self,key, maxwaittime = 60 ):
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""" Wait (poll) for a key to get a value
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Will wait for `maxwaittime` seconds before raising a KeyError.
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The call exits normally if the `key` field in db gets a value
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within the timeout period.
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Use this for synchronizing different processes or for ensuring
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that an unfortunately timed "db['key'] = newvalue" operation
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in another process (which causes all 'get' operation to cause a
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KeyError for the duration of pickling) won't screw up your program
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logic.
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"""
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wtimes = [0.2] * 3 + [0.5] * 2 + [1]
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tries = 0
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waited = 0
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while 1:
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try:
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val = self[key]
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return val
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except KeyError:
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pass
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if waited > maxwaittime:
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raise KeyError(key)
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time.sleep(wtimes[tries])
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waited+=wtimes[tries]
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if tries < len(wtimes) -1:
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tries+=1
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def getlink(self,folder):
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""" Get a convenient link for accessing items """
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return PickleShareLink(self, folder)
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def __repr__(self):
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return "PickleShareDB('%s')" % self.root
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class PickleShareLink:
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""" A shortdand for accessing nested PickleShare data conveniently.
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Created through PickleShareDB.getlink(), example::
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lnk = db.getlink('myobjects/test')
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lnk.foo = 2
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lnk.bar = lnk.foo + 5
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"""
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def __init__(self, db, keydir ):
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self.__dict__.update(locals())
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def __getattr__(self,key):
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return self.__dict__['db'][self.__dict__['keydir']+'/' + key]
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def __setattr__(self,key,val):
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self.db[self.keydir+'/' + key] = val
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def __repr__(self):
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db = self.__dict__['db']
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keys = db.keys( self.__dict__['keydir'] +"/*")
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return "<PickleShareLink '%s': %s>" % (
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self.__dict__['keydir'],
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";".join([Path(k).basename() for k in keys]))
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def main():
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import textwrap
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usage = textwrap.dedent("""\
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pickleshare - manage PickleShare databases
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Usage:
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pickleshare dump /path/to/db > dump.txt
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pickleshare load /path/to/db < dump.txt
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pickleshare test /path/to/db
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""")
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DB = PickleShareDB
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import sys
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if len(sys.argv) < 2:
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print(usage)
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return
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cmd = sys.argv[1]
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args = sys.argv[2:]
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if cmd == 'dump':
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if not args: args= ['.']
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db = DB(args[0])
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import pprint
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pprint.pprint(db.items())
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elif cmd == 'load':
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cont = sys.stdin.read()
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db = DB(args[0])
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data = eval(cont)
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db.clear()
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for k,v in db.items():
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db[k] = v
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elif cmd == 'testwait':
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db = DB(args[0])
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db.clear()
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print(db.waitget('250'))
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elif cmd == 'test':
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test()
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stress()
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if __name__== "__main__":
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main()
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