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