Source code for lsst.verify.metaquery
#
# LSST Data Management System
#
# This product includes software developed by the
# LSST Project (http://www.lsst.org/).
#
# See COPYRIGHT file at the top of the source tree.
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the LSST License Statement and
# the GNU General Public License along with this program. If not,
# see <https://www.lsstcorp.org/LegalNotices/>.
#
from __future__ import print_function, division
__all__ = ['MetadataQuery']
from .jsonmixin import JsonSerializationMixin
[docs]class MetadataQuery(JsonSerializationMixin):
"""Query of `lsst.verify.Job.meta` metadata.
Parameters
----------
terms : `dict`, optional
A mapping of key-value query terms. In the default query mode, the
user-provided job metadata must have all these terms, and matching
values, to pass the query.
Examples
--------
A MetadataQuery returns `True` if all key-value terms found in
`MetadataQuery.terms` are equal to key-value metadata items.
>>> metadata = {'filter': 'r', 'camera': 'MegaCam'}
An example of a query with a conflicting term:
>>> query1 = MetadataQuery({'filter': 'r', 'camera': 'SDSS'})
>>> query1(metadata)
False
A query with matching terms (albeit, a subset of the metadata):
>>> query2 = MetadataQuery({'filter': 'r'})
>>> query2(metadata)
True
A query that overconstrains the available metadata:
>>> query3 = MetadataQuery({'filter': 'r', 'camera': 'MegaCam',
... 'photometric': True})
>>> query3(metadata)
False
The ``arg_driven=True`` mode reverses the matching logic so that all terms
in the user-provided metadata must be in the MetadataQuery:
>>> query3(metadata, arg_driven=True)
True
>>> query2(metadata, arg_driven=True)
False
"""
terms = None
"""Term mapping (`dict`). Metadata must have all keys and corresponding
values.
"""
def __init__(self, terms=None):
self.terms = terms or dict()
[docs] def __call__(self, metadata, arg_driven=False):
"""Determine if a metadata set matches the query terms.
Parameters
----------
metadata : `dict` or `lsst.verify.Metadata`
Metadata mapping. Typically this is a job's
`lsst.verify.Job.meta`.
arg_driven : `bool`, optional
If `False` (default), ``metadata`` matches the ``MetadataQuery``
if ``metadata`` has all the terms defined in ``MetadataQuery``,
and those terms match. If ``metadata`` has more terms than
``MetadataQuery``, it can still match.
If `True`, the orientation of the matching is reversed. Now
``metadata`` matches the ``MetadataQuery`` if ``MetadataQuery``
has all the terms defined in ``metadata`` and those terms match.
If ``MetadataQuery`` has more terms than ``metadata``, it can
still match.
Returns
-------
match : `bool`
`True` if the metadata matches the query terms; `False` otherwise.
"""
if arg_driven:
# Match if self.terms has all the terms defined in metadata
for arg_term, arg_term_value in metadata.items():
if arg_term not in self.terms:
return False
# If metadata can be floats, may need to do more sophisticated
# comparison
if arg_term_value != self.terms[arg_term]:
return False
else:
# Match if metadata has all the terms defined in this MetadataQuery
for term_key, term_value in self.terms.items():
if term_key not in metadata:
return False
# If metadata can be floats, may need to do more sophisticated
# comparison
if term_value != metadata[term_key]:
return False
return True
def __eq__(self, other):
return self.terms == other.terms
def __str__(self):
return str(self.terms)
def __repr__(self):
template = 'MetadataQuery({0!r})'
return template.format(self.terms)
@property
def json(self):
"""A JSON-serializable dict.
Keys are metadata keys. Values are the associated metadata values
of the query term.
"""
return self.jsonify_dict(self.terms)