Source code for lsst.verify.metaquery

#
# LSST Data Management System
#
# This product includes software developed by the
# LSST Project (http://www.lsst.org/).
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# This program is free software: you can redistribute it and/or modify
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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)