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"""A Task logger that presents our DB interface,
but exists entirely in memory and implemented with dicts.
Authors:
* Min RK
TaskRecords are dicts of the form:
{
'msg_id' : str(uuid),
'client_uuid' : str(uuid),
'engine_uuid' : str(uuid) or None,
'header' : dict(header),
'content': dict(content),
'buffers': list(buffers),
'submitted': datetime,
'started': datetime or None,
'completed': datetime or None,
'resubmitted': datetime or None,
'result_header' : dict(header) or None,
'result_content' : dict(content) or None,
'result_buffers' : list(buffers) or None,
}
With this info, many of the special categories of tasks can be defined by query:
pending: completed is None
client's outstanding: client_uuid = uuid && completed is None
MIA: arrived is None (and completed is None)
etc.
EngineRecords are dicts of the form:
{
'eid' : int(id),
'uuid': str(uuid)
}
This may be extended, but is currently.
We support a subset of mongodb operators:
$lt,$gt,$lte,$gte,$ne,$in,$nin,$all,$mod,$exists
"""
#-----------------------------------------------------------------------------
# Copyright (C) 2010-2011 The IPython Development Team
#
# Distributed under the terms of the BSD License. The full license is in
# the file COPYING, distributed as part of this software.
#-----------------------------------------------------------------------------
from datetime import datetime
from IPython.config.configurable import LoggingConfigurable
from IPython.utils.traitlets import Dict, Unicode, Instance
filters = {
'$lt' : lambda a,b: a < b,
'$gt' : lambda a,b: b > a,
'$eq' : lambda a,b: a == b,
'$ne' : lambda a,b: a != b,
'$lte': lambda a,b: a <= b,
'$gte': lambda a,b: a >= b,
'$in' : lambda a,b: a in b,
'$nin': lambda a,b: a not in b,
'$all': lambda a,b: all([ a in bb for bb in b ]),
'$mod': lambda a,b: a%b[0] == b[1],
'$exists' : lambda a,b: (b and a is not None) or (a is None and not b)
}
class CompositeFilter(object):
"""Composite filter for matching multiple properties."""
def __init__(self, dikt):
self.tests = []
self.values = []
for key, value in dikt.iteritems():
self.tests.append(filters[key])
self.values.append(value)
def __call__(self, value):
for test,check in zip(self.tests, self.values):
if not test(value, check):
return False
return True
class BaseDB(LoggingConfigurable):
"""Empty Parent class so traitlets work on DB."""
# base configurable traits:
session = Unicode("")
class DictDB(BaseDB):
"""Basic in-memory dict-based object for saving Task Records.
This is the first object to present the DB interface
for logging tasks out of memory.
The interface is based on MongoDB, so adding a MongoDB
backend should be straightforward.
"""
_records = Dict()
def _match_one(self, rec, tests):
"""Check if a specific record matches tests."""
for key,test in tests.iteritems():
if not test(rec.get(key, None)):
return False
return True
def _match(self, check):
"""Find all the matches for a check dict."""
matches = []
tests = {}
for k,v in check.iteritems():
if isinstance(v, dict):
tests[k] = CompositeFilter(v)
else:
tests[k] = lambda o: o==v
for rec in self._records.itervalues():
if self._match_one(rec, tests):
matches.append(rec)
return matches
def _extract_subdict(self, rec, keys):
"""extract subdict of keys"""
d = {}
d['msg_id'] = rec['msg_id']
for key in keys:
d[key] = rec[key]
return d
def add_record(self, msg_id, rec):
"""Add a new Task Record, by msg_id."""
if self._records.has_key(msg_id):
raise KeyError("Already have msg_id %r"%(msg_id))
self._records[msg_id] = rec
def get_record(self, msg_id):
"""Get a specific Task Record, by msg_id."""
if not self._records.has_key(msg_id):
raise KeyError("No such msg_id %r"%(msg_id))
return self._records[msg_id]
def update_record(self, msg_id, rec):
"""Update the data in an existing record."""
self._records[msg_id].update(rec)
def drop_matching_records(self, check):
"""Remove a record from the DB."""
matches = self._match(check)
for m in matches:
del self._records[m['msg_id']]
def drop_record(self, msg_id):
"""Remove a record from the DB."""
del self._records[msg_id]
def find_records(self, check, keys=None):
"""Find records matching a query dict, optionally extracting subset of keys.
Returns dict keyed by msg_id of matching records.
Parameters
----------
check: dict
mongodb-style query argument
keys: list of strs [optional]
if specified, the subset of keys to extract. msg_id will *always* be
included.
"""
matches = self._match(check)
if keys:
return [ self._extract_subdict(rec, keys) for rec in matches ]
else:
return matches
def get_history(self):
"""get all msg_ids, ordered by time submitted."""
msg_ids = self._records.keys()
return sorted(msg_ids, key=lambda m: self._records[m]['submitted'])
class NoDB(DictDB):
"""A blackhole db backend that actually stores no information.
Provides the full DB interface, but raises KeyErrors on any
method that tries to access the records. This can be used to
minimize the memory footprint of the Hub when its record-keeping
functionality is not required.
"""
def add_record(self, msg_id, record):
pass
def get_record(self, msg_id):
raise KeyError("NoDB does not support record access")
def update_record(self, msg_id, record):
pass
def drop_matching_records(self, check):
pass
def drop_record(self, msg_id):
pass
def find_records(self, check, keys=None):
raise KeyError("NoDB does not store information")
def get_history(self):
raise KeyError("NoDB does not store information")