Homec4science
Diffusion invenio-infoscience (master) Browse

R3600/invenio/legacy/bibclassify/ontology_reader.py
6e6919333ba1master

Last Change
Raw File

ontology_reader.py
View Options

# -*- coding: utf-8 -*-
##
## This file is part of Invenio.
## Copyright (C) 2008, 2009, 2010, 2011, 2012, 2013, 2014 CERN.
##
## Invenio 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 2 of the
## License, or (at your option) any later version.
##
## Invenio 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 GNU General Public License
## along with Invenio; if not, write to the Free Software Foundation, Inc.,
## 59 Temple Place, Suite 330, Boston, MA 02111-1307, USA.
"""
BibClassify ontology reader.
The ontology reader reads currently either a RDF/SKOS taxonomy or a
simple controlled vocabulary file (1 word per line). The first role of
this module is to manage the cached version of the ontology file. The
second role is to hold all methods responsible for the creation of
regular expressions. These methods are grammatically related as we take
care of different forms of the same words. The grammatical rules can be
configured via the configuration file.
The main method from this module is get_regular_expressions.
This module is standalone safe.
"""
from datetime import datetime, timedelta
from six import iteritems
import cPickle
import os
import re
import sys
import tempfile
import time
import urllib2
import traceback
import xml.sax
import thread
import time
try:
import rdflib
rdflib_exceptions_Error = rdflib.exceptions.Error
except ImportError:
rdflib = None
rdflib_exceptions_Error = None
from invenio.legacy.bibclassify import config as bconfig
log = bconfig.get_logger("bibclassify.ontology_reader")
from invenio import config
from invenio.modules.classifier.registry import taxonomies
# only if not running in a stanalone mode
if bconfig.STANDALONE:
dbquery = None
from urllib2 import urlopen
else:
from invenio.legacy import dbquery
from invenio.utils.url import make_invenio_opener
urlopen = make_invenio_opener('BibClassify').open
_contains_digit = re.compile("\d")
_starts_with_non = re.compile("(?i)^non[a-z]")
_starts_with_anti = re.compile("(?i)^anti[a-z]")
_split_by_punctuation = re.compile("(\W+)")
_CACHE = {}
def get_cache(taxonomy_id):
"""Returns thread-safe cache for the given taxonomy id,
@var taxonomy_id: str, identifier of the taxonomy
@return: dictionary object (empty if no taxonomy_id
is found), you must not change anything inside it.
Create a new dictionary and use set_cache if you want
to update the cache!
"""
# Because of a standalone mode, we don't use the
# invenio.data_cacher.DataCacher, but it has no effect
# on proper functionality.
if _CACHE.has_key(taxonomy_id):
ctime, taxonomy = _CACHE[taxonomy_id]
# check it is fresh version
onto_name, onto_path, onto_url = _get_ontology(taxonomy_id)
cache_path = _get_cache_path(onto_name)
# if source exists and is newer than the cache hold in memory
if os.access(onto_path, os.R_OK) and os.path.getmtime(cache_path) > ctime:
log.info('Forcing taxonony rebuild as cached version is newer/updated.')
return {} # force cache rebuild
# if cache exists and is newer than the cache hold in memory
if os.access(cache_path, os.R_OK) and os.path.getmtime(cache_path) > ctime:
log.info('Forcing taxonony rebuild as source file is newer/updated.')
return {}
log.info('Taxonomy retrieved from cache')
return taxonomy
return {}
def set_cache(taxonomy_id, contents):
"""Updates cache in a thread-safe manner"""
lock = thread.allocate_lock()
lock.acquire()
try:
_CACHE[taxonomy_id] = (time.time(), contents)
finally:
lock.release()
def get_regular_expressions(taxonomy_name, rebuild=False, no_cache=False):
"""Returns a list of patterns compiled from the RDF/SKOS ontology.
Uses cache if it exists and if the taxonomy hasn't changed."""
# Translate the ontology name into a local path. Check if the name
# relates to an existing ontology.
onto_name, onto_path, onto_url = _get_ontology(taxonomy_name)
if not onto_path:
log.error("Unable to locate the taxonomy: '%s'." % taxonomy_name)
raise Exception("Unable to locate the taxonomy: '%s'." % taxonomy_name)
cache_path = _get_cache_path(onto_name)
log.debug('Taxonomy discovered, now we load it (from cache: %s, onto_path: %s, cache_path: %s)'
% (not no_cache, onto_path, cache_path))
if os.access(cache_path, os.R_OK):
if os.access(onto_path, os.R_OK):
if rebuild or no_cache:
log.debug("Cache generation was manually forced.")
if os.access(onto_path, os.R_OK):
return _build_cache(onto_path, skip_cache=no_cache)
else:
# ontology file not found. Use the cache instead.
log.warning("The ontology couldn't be located. However "
"a cached version of it is available. Using it as a "
"reference.")
return _get_cache(cache_path, source_file=onto_path)
if (os.path.getmtime(cache_path) >
os.path.getmtime(onto_path)):
# Cache is more recent than the ontology: use cache.
log.debug("Normal situation, cache is older than ontology, so we load it from cache")
return _get_cache(cache_path, source_file=onto_path)
else:
# Ontology is more recent than the cache: rebuild cache.
log.warning("Cache '%s' is older than '%s'. We will rebuild the cache" %
(cache_path, onto_path))
return _build_cache(onto_path, skip_cache=no_cache)
elif os.access(onto_path, os.R_OK):
if not no_cache and os.path.exists(cache_path) and not os.access(cache_path, os.W_OK):
log.error('We cannot read/write into: %s. Aborting!' % cache_path)
raise Exception('We cannot read/write into: %s. Aborting!' % cache_path)
elif not no_cache and os.path.exists(cache_path):
log.warning('Cache %s exists, but is not readable!' % cache_path)
log.info("Cache not available. Building it now: %s" % onto_path)
return _build_cache(onto_path, skip_cache=no_cache)
else:
log.error("We miss both source and cache of the taxonomy: %s" % taxonomy_name)
raise Exception("We miss both source and cache of the taxonomy: %s" % taxonomy_name)
def _get_remote_ontology(onto_url, time_difference=None):
"""Checks if the online ontology is more recent than the local ontology. If
yes, try to download and store it in Invenio's cache directory. Return a
boolean describing the success of the operation.
Returns path to the downloaded ontology"""
if onto_url is None:
return False
dl_dir = ((config.CFG_CACHEDIR or tempfile.gettempdir()) + os.sep +
"bibclassify" + os.sep)
if not os.path.exists(dl_dir):
os.mkdir(dl_dir)
local_file = dl_dir + os.path.basename(onto_url)
remote_modif_time = _get_last_modification_date(onto_url)
try:
local_modif_seconds = os.path.getmtime(local_file)
except OSError:
# The local file does not exist. Download the ontology.
download = True
log.info("The local ontology could not be found.")
else:
local_modif_time = datetime(*time.gmtime(local_modif_seconds)[0:6])
# Let's set a time delta of 1 hour and 10 minutes.
time_difference = time_difference or timedelta(hours=1, minutes=10)
download = remote_modif_time > local_modif_time + time_difference
if download:
log.info("The remote ontology '%s' is more recent "
"than the local ontology." % onto_url)
if download:
if not _download_ontology(onto_url, local_file):
log.warning("Error downloading the ontology from: %s" % onto_url)
return local_file
def _get_ontology(ontology):
"""Returns the (name, path, url) to the short ontology name.
@var ontology: name of the ontology or path to the file or url"""
onto_name = onto_path = onto_url = None
# first assume we got the path to the file
if os.access(ontology, os.R_OK):
onto_name = os.path.split(os.path.abspath(ontology))[1]
onto_path = os.path.abspath(ontology)
onto_url = ""
else:
# if not, try to find it in a known locations
discovered_file = _discover_ontology(ontology)
if discovered_file:
onto_name = os.path.split(discovered_file)[1]
onto_path = discovered_file
# i know, this sucks
x = ontology.lower()
if "http:" in x or "https:" in x or "ftp:" in x or "file:" in x:
onto_url = ontology
else:
onto_url = ""
else:
# not found, look into a database (it is last because when bibclassify
# runs in a standalone mode, it has no database - [rca, old-heritage]
if not bconfig.STANDALONE:
result = dbquery.run_sql("SELECT name, location from clsMETHOD WHERE name LIKE %s",
('%' + ontology + '%',))
for onto_short_name, url in result:
onto_name = onto_short_name
onto_path = _get_remote_ontology(url)
onto_url = url
return (onto_name, onto_path, onto_url)
def _discover_ontology(ontology_name):
"""
Looks for the file in a known places (Inside invenio/etc/bibclassify) and
a few other places like current dir
@var ontology: string, name or path name or url
@return: absolute path of a file if found, or None
"""
last_part = os.path.split(os.path.abspath(ontology_name))[1].lower()
if last_part in taxonomies:
return taxonomies.get(last_part)
elif last_part + ".rdf" in taxonomies:
return taxonomies.get(last_part + ".rdf")
else:
log.debug("No taxonomy with pattern '%s' found" % ontology_name)
#FIXME: review
# places = [config.CFG_CACHEDIR,
# config.CFG_ETCDIR,
# os.path.join(config.CFG_CACHEDIR, "bibclassify"),
# os.path.join(config.CFG_ETCDIR, "bibclassify"),
# os.path.abspath('.'),
# os.path.abspath(os.path.join(os.path.dirname(__file__), "../../../etc/bibclassify")),
# os.path.join(os.path.dirname(__file__), "bibclassify"),
# config.CFG_WEBDIR ]
# log.debug("Searching for taxonomy using string: %s" % last_part)
# log.debug("Possible patterns: %s" % possible_patterns)
# for path in places:
# try:
# if os.path.isdir(path):
# log.debug("Listing: %s" % path)
# for filename in os.listdir(path):
# #log.debug('Testing: %s' % filename)
# for pattern in possible_patterns:
# filename_lc = filename.lower()
# if pattern == filename_lc and os.path.exists(os.path.join(path, filename)):
# filepath = os.path.abspath(os.path.join(path, filename))
# if (os.access(filepath, os.R_OK)):
# log.debug("Found taxonomy at: %s" % filepath)
# return filepath
# else:
# log.warning('Found taxonony at: %s, but it is not readable. Continue searching...' % filepath)
# except OSError as os_error_msg:
# log.warning('OS Error when listing path "%s": %s' % (str(path), str(os_error_msg)))
# log.debug("No taxonomy with pattern '%s' found" % ontology_name)
class KeywordToken:
# this tells pickle that the class we are pickling is coming from
# module 'bibclassify_ontology_reader' instead of invenio.legacy.bibclassify.ontology_reader
#__module__ = os.path.splitext(os.path.basename(__file__))[0]
def __init__(self, subject, store=None, namespace=None, type='HEP'):
"""KeywordToken is a class used for the extracted keywords
It can be initialized with values from RDF store or from
sinmple strings. Specialty of this class is that objects are
hashable by subject - so in the dictionary two objects with the
same subject appears as one -- @see: self.__hash__ and self.__cmp__
@var subject: string or RDF object
@keyword store: RDF graph object (will be used to get info about the subject)
@keyword namespace: RDF namespace object, used together with store
@keyword type: string, type of this keyword
"""
self.id = subject
self.type = type
self.short_id = subject
self.concept = ""
self.regex = []
self.nostandalone = False
self.spires = False
self.fieldcodes = []
self.compositeof = []
self.core = False
self._composite = '#Composite' in subject # True means composite keyword
self.__hash = None
# the tokens are coming possibly from a normal text file
if store is None:
subject = subject.strip()
self.concept = subject
self.regex = _get_searchable_regex(basic=[subject])
self.nostandalone = False
self.fieldcodes = []
self.core = False
if subject.find(' ') > -1:
self._composite = True
# definitions from rdf
else:
self.short_id = self.short_id.split('#')[-1]
#find alternate names for this label
basic_labels = []
#turn those patterns into regexes only for simple keywords
if self._composite is False:
try:
for label in store.objects(subject, namespace["prefLabel"]):
basic_labels.append(str(label)) # XXX shall i make it unicode?
except TypeError:
pass
self.concept = basic_labels[0]
else:
try:
self.concept = str(store.value(subject, namespace["prefLabel"],
any=True))
except KeyError:
log.warning("Keyword with subject %s has no prefLabel. We use raw name" %
self.short_id)
self.concept = self.short_id
# this is common both to composite and simple keywords
try:
for label in store.objects(subject, namespace["altLabel"]):
basic_labels.append(str(label))
except TypeError:
pass
#hidden labels are special (possibly regex) codes
hidden_labels = []
try:
for label in store.objects(subject, namespace["hiddenLabel"]):
hidden_labels.append(unicode(label))
except TypeError:
pass
# compile regular expression that will identify this token
self.regex = _get_searchable_regex(basic_labels, hidden_labels)
try:
for note in map(lambda s: str(s).lower().strip(),
store.objects(subject, namespace["note"])):
if note == 'core':
self.core = True
elif note in ("nostandalone", "nonstandalone"):
self.nostandalone = True
elif 'fc:' in note:
self.fieldcodes.append(note[3:].strip())
except TypeError:
pass
# spiresLabel does not have multiple values
spires_label = store.value(subject, namespace["spiresLabel"])
if spires_label:
self.spires = str(spires_label)
# important for comparisons
self.__hash = hash(self.short_id)
# extract composite parts ids
if store is not None and self.isComposite():
small_subject = self.id.split("#Composite.")[-1]
component_positions = []
for label in store.objects(self.id, namespace["compositeOf"]):
strlabel = str(label).split("#")[-1]
component_name = label.split("#")[-1]
component_positions.append((small_subject.find(component_name), strlabel))
component_positions.sort()
if not component_positions:
log.error("Keyword is marked as composite, but no composite components refs found: %s" \
% self.short_id)
else:
self.compositeof = map(lambda x: x[1], component_positions)
def refreshCompositeOf(self, single_keywords, composite_keywords,
store=None, namespace=None):
"""Re-checks sub-parts of this keyword - this should be called after the whole
RDF was processed, because it is using a cache of single keywords and if that
one is incomplete, you will not identify all parts
"""
def _get_ckw_components(new_vals, label):
if label in single_keywords:
new_vals.append(single_keywords[label])
elif ('Composite.%s' % label) in composite_keywords:
for l in composite_keywords['Composite.%s' % label].compositeof:
_get_ckw_components(new_vals, l)
elif label in composite_keywords:
for l in composite_keywords[label].compositeof:
_get_ckw_components(new_vals, l)
else:
# One single or composite keyword is not present in the taxonomy. This is due to an error in the taxonomy description.
log.error(
"The composite term \"%s\" should be made of single keywords, but at least one is missing" % self.id)
if store is not None:
log.error("Needed components: %s" % list(store.objects(self.id, namespace["compositeOf"])))
log.error("Missing is: %s" % label)
raise Exception()
if self.compositeof:
new_vals = []
try:
for label in self.compositeof:
_get_ckw_components(new_vals, label)
self.compositeof = new_vals
except:
# the composites will be empty (better than to have confusing, partial matches)
self.compositeof = []
log.error(
'We reset this composite keyword, so that it does not match anything. Please fix the taxonomy.')
def isComposite(self):
return self._composite
def getComponents(self):
return self.compositeof
def getType(self):
return self.type
def setType(self, value):
self.type = value
def __hash__(self):
"""this might change in the future but for the moment we want to think that if the concept
is the same, then it is the same keyword - this sucks, but it is sort of how it is necessary
to use now"""
return self.__hash
def __cmp__(self, other):
if self.__hash < other.__hash__():
return -1
elif self.__hash == other.__hash__():
return 0
else:
return 1
def __str__(self, spires=False):
"""Returns the best output for the keyword."""
if spires:
if self.spires:
return self.spires
elif self._composite:
return self.concept.replace(':', ',')
# default action
return self.concept
def output(self, spires=False):
return self.__str__(spires=spires)
def __repr__(self):
return "<KeywordToken: %s>" % self.short_id
def _build_cache(source_file, skip_cache=False):
"""Builds the cached data by parsing the RDF taxonomy file or a
vocabulary file.
@var source_file: source file of the taxonomy, RDF file
@keyword skip_cache: boolean, if True, build cache will not be
saved (pickled) - it is saved as <source_file.db> """
if rdflib:
if rdflib.__version__ >= '2.3.2':
store = rdflib.ConjunctiveGraph()
else:
store = rdflib.Graph()
else:
store = None
if skip_cache:
log.info("You requested not to save the cache to disk.")
else:
cache_path = _get_cache_path(source_file)
cache_dir = os.path.dirname(cache_path)
# Make sure we have a cache_dir readable and writable.
try:
os.makedirs(cache_dir)
except:
pass
if os.access(cache_dir, os.R_OK):
if not os.access(cache_dir, os.W_OK):
log.error("Cache directory exists but is not writable. Check your permissions for: %s" % cache_dir)
raise Exception(
"Cache directory exists but is not writable. Check your permissions for: %s" % cache_dir)
else:
log.error("Cache directory does not exist (and could not be created): %s" % cache_dir)
raise Exception("Cache directory does not exist (and could not be created): %s" % cache_dir)
timer_start = time.clock()
namespace = None
single_keywords, composite_keywords = {}, {}
try:
if not rdflib:
raise ImportError() # will be caught below
log.info("Building RDFLib's conjunctive graph from: %s" % source_file)
try:
store.parse(source_file)
except urllib2.URLError as exc:
if source_file[0] == '/':
store.parse("file://" + source_file)
else:
store.parse("file:///" + source_file)
except rdflib_exceptions_Error as e:
log.error("Serious error reading RDF file")
log.error(e)
log.error(traceback.format_exc())
raise rdflib.exceptions.Error(e)
except (xml.sax.SAXParseException, ImportError) as e:
# File is not a RDF file. We assume it is a controlled vocabulary.
log.error(e)
log.error("The ontology file is probably not a valid RDF file. \
Assuming it is a controlled vocabulary file.")
filestream = open(source_file, "r")
for line in filestream:
keyword = line.strip()
kt = KeywordToken(keyword)
single_keywords[kt.short_id] = kt
if not len(single_keywords):
raise Exception('Probably a wrong dictionary')
else: #ok, no exception happened
log.info("Now building cache of keywords")
# File is a RDF file.
namespace = rdflib.Namespace("http://www.w3.org/2004/02/skos/core#")
single_count = 0
composite_count = 0
for subject, pref_label in store.subject_objects(namespace["prefLabel"]):
kt = KeywordToken(subject, store=store, namespace=namespace)
if kt.isComposite():
composite_count += 1
composite_keywords[kt.short_id] = kt
#log.info("saved composite: %s" % kt.short_id)
else:
single_keywords[kt.short_id] = kt
single_count += 1
cached_data = {}
cached_data["single"] = single_keywords
cached_data["composite"] = composite_keywords
cached_data["creation_time"] = time.gmtime()
cached_data["version_info"] = {'rdflib': rdflib and rdflib.__version__, 'bibclassify': bconfig.VERSION}
log.debug("Building taxonomy... %d terms built in %.1f sec." %
(len(single_keywords) + len(composite_keywords),
time.clock() - timer_start))
log.info("Total count of single keywords: %d " % len(single_keywords))
log.info("Total count of composite keywords: %d " % len(composite_keywords))
if not skip_cache:
cache_path = _get_cache_path(source_file)
cache_dir = os.path.dirname(cache_path)
log.debug("Writing the cache into: %s" % cache_path)
# test again, it could have changed
if os.access(cache_dir, os.R_OK):
if os.access(cache_dir, os.W_OK):
# Serialize.
filestream = None
try:
filestream = open(cache_path, "wb")
except IOError as msg:
# Impossible to write the cache.
log.error("Impossible to write cache to '%s'." % cache_path)
log.error(msg)
else:
log.debug("Writing cache to file %s" % cache_path)
cPickle.dump(cached_data, filestream, 1)
if filestream:
filestream.close()
else:
raise Exception(
"Cache directory exists but is not writable. Check your permissions for: %s" % cache_dir)
else:
raise Exception("Cache directory does not exist (and could not be created): %s" % cache_dir)
# now when the whole taxonomy was parsed, find sub-components of the composite kws
# it is important to keep this call after the taxonomy was saved, because we don't
# want to pickle regexes multiple times (as they are must be re-compiled at load time)
for kt in composite_keywords.values():
kt.refreshCompositeOf(single_keywords, composite_keywords,
store=store, namespace=namespace)
# house-cleaning
if store:
store.close()
return (single_keywords, composite_keywords)
def _capitalize_first_letter(word):
"""Returns a regex pattern with the first letter accepting both lowercase
and uppercase."""
if word[0].isalpha():
# These two cases are necessary in order to get a regex pattern
# starting with '[xX]' and not '[Xx]'. This allows to check for
# colliding regex afterwards.
if word[0].isupper():
return "[" + word[0].swapcase() + word[0] + "]" + word[1:]
else:
return "[" + word[0] + word[0].swapcase() + "]" + word[1:]
return word
def _convert_punctuation(punctuation, conversion_table):
"""Returns a regular expression for a punctuation string."""
if punctuation in conversion_table:
return conversion_table[punctuation]
return re.escape(punctuation)
def _convert_word(word):
"""Returns the plural form of the word if it exists, the word itself
otherwise."""
out = None
# Acronyms.
if word.isupper():
out = word + "s?"
# Proper nouns or word with digits.
elif word.istitle():
out = word + "('?s)?"
elif _contains_digit.search(word):
out = word
if out is not None:
return out
# Words with non or anti prefixes.
if _starts_with_non.search(word):
word = "non-?" + _capitalize_first_letter(_convert_word(word[3:]))
elif _starts_with_anti.search(word):
word = "anti-?" + _capitalize_first_letter(_convert_word(word[4:]))
if out is not None:
return _capitalize_first_letter(out)
# A few invariable words.
if word in bconfig.CFG_BIBCLASSIFY_INVARIABLE_WORDS:
return _capitalize_first_letter(word)
# Some exceptions that would not produce good results with the set of
# general_regular_expressions.
if word in bconfig.CFG_BIBCLASSIFY_EXCEPTIONS:
return _capitalize_first_letter(bconfig.CFG_BIBCLASSIFY_EXCEPTIONS[word])
for regex in bconfig.CFG_BIBCLASSIFY_UNCHANGE_REGULAR_EXPRESSIONS:
if regex.search(word) is not None:
return _capitalize_first_letter(word)
for regex, replacement in bconfig.CFG_BIBCLASSIFY_GENERAL_REGULAR_EXPRESSIONS:
stemmed = regex.sub(replacement, word)
if stemmed != word:
return _capitalize_first_letter(stemmed)
return _capitalize_first_letter(word + "s?")
def _get_cache(cache_file, source_file=None):
"""Get the cached taxonomy using the cPickle module. No check is done at
that stage.
@var cache_file: fullpath to the file holding pickled data
@keyword source_file: if we discover the cache is obsolete, we
will build a new cache, therefore we need the source path
of the cache
@return: (single_keywords, composite_keywords)"""
timer_start = time.clock()
filestream = open(cache_file, "rb")
try:
#bibclassify_ontology_reader = sys.modules['bibclassify_ontology_reader']
cached_data = cPickle.load(filestream)
if cached_data['version_info']['rdflib'] != (rdflib and rdflib.__version__) or \
cached_data['version_info']['bibclassify'] != bconfig.VERSION:
raise KeyError
except (cPickle.UnpicklingError, AttributeError, DeprecationWarning, EOFError) as e:
log.warning("The existing cache in %s is not readable. "
"Removing and rebuilding it." % cache_file)
filestream.close()
os.remove(cache_file)
return _build_cache(source_file)
except KeyError:
log.warning("The existing cache %s is not up-to-date. "
"Removing and rebuilding it." % cache_file)
filestream.close()
os.remove(cache_file)
if source_file and os.path.exists(source_file):
return _build_cache(source_file)
else:
log.error("The cache contains obsolete data (and it was deleted), \
however I can't build a new cache, the source does not exist or is inaccessible! - %s" %
source_file)
filestream.close()
single_keywords = cached_data["single"]
composite_keywords = cached_data["composite"]
# the cache contains only keys of the composite keywords, not the objects
# so now let's resolve them into objects
for kw in composite_keywords.values():
kw.refreshCompositeOf(single_keywords, composite_keywords)
log.debug("Retrieved taxonomy from cache %s created on %s" %
(cache_file, time.asctime(cached_data["creation_time"])))
log.debug("%d terms read in %.1f sec." %
(len(single_keywords) + len(composite_keywords),
time.clock() - timer_start))
return (single_keywords, composite_keywords)
def _get_cache_path(source_file):
"""Returns the path where the cache of this taxonomy should
be written/located
@var onto_name: name of the ontology or the full path
@return: string, abs path to the cache file in the tmpdir/bibclassify
"""
local_name = os.path.basename(source_file)
cache_name = local_name + ".db"
cache_dir = os.path.join(config.CFG_CACHEDIR, "bibclassify")
if not os.path.isdir(cache_dir):
os.makedirs(cache_dir)
return os.path.abspath(os.path.join(cache_dir, cache_name))
def _get_last_modification_date(url):
"""Get the last modification date of the ontology."""
request = urllib2.Request(url)
request.get_method = lambda: "HEAD"
http_file = urlopen(request)
date_string = http_file.headers["last-modified"]
parsed = time.strptime(date_string, "%a, %d %b %Y %H:%M:%S %Z")
return datetime(*(parsed)[0:6])
def _download_ontology(url, local_file):
"""Downloads the ontology and stores it in CFG_CACHEDIR."""
log.debug("Copying remote ontology '%s' to file '%s'." % (url,
local_file))
try:
url_desc = urlopen(url)
file_desc = open(local_file, 'w')
file_desc.write(url_desc.read())
file_desc.close()
except IOError as e:
print e
return False
except:
log.warning("Unable to download the ontology. '%s'" %
sys.exc_info()[0])
return False
else:
log.debug("Done copying.")
return True
def _get_searchable_regex(basic=None, hidden=None):
"""Returns the searchable regular expressions for the single
keyword."""
# Hidden labels are used to store regular expressions.
basic = basic or []
hidden = hidden or []
hidden_regex_dict = {}
for hidden_label in hidden:
if _is_regex(hidden_label):
hidden_regex_dict[hidden_label] = \
re.compile(bconfig.CFG_BIBCLASSIFY_WORD_WRAP % hidden_label[1:-1])
else:
pattern = _get_regex_pattern(hidden_label)
hidden_regex_dict[hidden_label] = \
re.compile(bconfig.CFG_BIBCLASSIFY_WORD_WRAP % pattern)
# We check if the basic label (preferred or alternative) is matched
# by a hidden label regex. If yes, discard it.
regex_dict = {}
# Create regex for plural forms and add them to the hidden labels.
for label in basic:
pattern = _get_regex_pattern(label)
regex_dict[label] = re.compile(bconfig.CFG_BIBCLASSIFY_WORD_WRAP % pattern)
# Merge both dictionaries.
regex_dict.update(hidden_regex_dict)
return regex_dict.values()
def _get_regex_pattern(label):
"""Returns a regular expression of the label that takes care of
plural and different kinds of separators."""
parts = _split_by_punctuation.split(label)
for index, part in enumerate(parts):
if index % 2 == 0:
# Word
if not parts[index].isdigit() and len(parts[index]) > 1:
parts[index] = _convert_word(parts[index])
else:
# Punctuation
if not parts[index + 1]:
# The separator is not followed by another word. Treat
# it as a symbol.
parts[index] = _convert_punctuation(parts[index],
bconfig.CFG_BIBCLASSIFY_SYMBOLS)
else:
parts[index] = _convert_punctuation(parts[index],
bconfig.CFG_BIBCLASSIFY_SEPARATORS)
return "".join(parts)
def _is_regex(string):
"""Checks if a concept is a regular expression."""
return string[0] == "/" and string[-1] == "/"
def check_taxonomy(taxonomy):
"""Checks the consistency of the taxonomy and outputs a list of
errors and warnings."""
if not rdflib:
raise Exception("The taxonomy checking is possible only with RDFLIB")
log.info("Building graph with Python RDFLib version %s" %
rdflib.__version__)
if rdflib.__version__ >= '2.3.2':
store = rdflib.ConjunctiveGraph()
else:
store = rdflib.Graph()
try:
store.parse(taxonomy)
except:
log.error("The taxonomy is not a valid RDF file. Are you "
"trying to check a controlled vocabulary?")
raise Exception('Error in RDF file')
log.info("Graph was successfully built.")
prefLabel = "prefLabel"
hiddenLabel = "hiddenLabel"
altLabel = "altLabel"
composite = "composite"
compositeOf = "compositeOf"
note = "note"
both_skw_and_ckw = []
# Build a dictionary we will reason on later.
uniq_subjects = {}
for subject in store.subjects():
uniq_subjects[subject] = None
subjects = {}
for subject in uniq_subjects:
strsubject = str(subject).split("#Composite.")[-1]
strsubject = strsubject.split("#")[-1]
if (strsubject == "http://cern.ch/thesauri/HEPontology.rdf" or
strsubject == "compositeOf"):
continue
components = {}
for predicate, value in store.predicate_objects(subject):
strpredicate = str(predicate).split("#")[-1]
strobject = str(value).split("#Composite.")[-1]
strobject = strobject.split("#")[-1]
components.setdefault(strpredicate, []).append(strobject)
if strsubject in subjects:
both_skw_and_ckw.append(strsubject)
else:
subjects[strsubject] = components
log.info("Taxonomy contains %s concepts." % len(subjects))
no_prefLabel = []
multiple_prefLabels = []
bad_notes = []
# Subjects with no composite or compositeOf predicate
lonely = []
both_composites = []
bad_hidden_labels = {}
bad_alt_labels = {}
# Problems with composite keywords
composite_problem1 = []
composite_problem2 = []
composite_problem3 = []
composite_problem4 = {}
composite_problem5 = []
composite_problem6 = []
stemming_collisions = []
interconcept_collisions = {}
for subject, predicates in iteritems(subjects):
# No prefLabel or multiple prefLabels
try:
if len(predicates[prefLabel]) > 1:
multiple_prefLabels.append(subject)
except KeyError:
no_prefLabel.append(subject)
# Lonely and both composites.
if not composite in predicates and not compositeOf in predicates:
lonely.append(subject)
elif composite in predicates and compositeOf in predicates:
both_composites.append(subject)
# Multiple or bad notes
if note in predicates:
bad_notes += [(subject, n) for n in predicates[note]
if n not in ('nostandalone', 'core')]
# Bad hidden labels
if hiddenLabel in predicates:
for lbl in predicates[hiddenLabel]:
if lbl.startswith("/") ^ lbl.endswith("/"):
bad_hidden_labels.setdefault(subject, []).append(lbl)
# Bad alt labels
if altLabel in predicates:
for lbl in predicates[altLabel]:
if len(re.findall("/", lbl)) >= 2 or ":" in lbl:
bad_alt_labels.setdefault(subject, []).append(lbl)
# Check composite
if composite in predicates:
for ckw in predicates[composite]:
if ckw in subjects:
if compositeOf in subjects[ckw]:
if not subject in subjects[ckw][compositeOf]:
composite_problem3.append((subject, ckw))
else:
if not ckw in both_skw_and_ckw:
composite_problem2.append((subject, ckw))
else:
composite_problem1.append((subject, ckw))
# Check compositeOf
if compositeOf in predicates:
for skw in predicates[compositeOf]:
if skw in subjects:
if composite in subjects[skw]:
if not subject in subjects[skw][composite]:
composite_problem6.append((subject, skw))
else:
if not skw in both_skw_and_ckw:
composite_problem5.append((subject, skw))
else:
composite_problem4.setdefault(skw, []).append(subject)
# Check for stemmed labels
if compositeOf in predicates:
labels = (altLabel, hiddenLabel)
else:
labels = (prefLabel, altLabel, hiddenLabel)
patterns = {}
for label in [lbl for lbl in labels if lbl in predicates]:
for expression in [expr for expr in predicates[label]
if not _is_regex(expr)]:
pattern = _get_regex_pattern(expression)
interconcept_collisions.setdefault(pattern,
[]).append((subject, label))
if pattern in patterns:
stemming_collisions.append((subject,
patterns[pattern],
(label, expression)
))
else:
patterns[pattern] = (label, expression)
print "\n==== ERRORS ===="
if no_prefLabel:
print "\nConcepts with no prefLabel: %d" % len(no_prefLabel)
print "\n".join([" %s" % subj for subj in no_prefLabel])
if multiple_prefLabels:
print ("\nConcepts with multiple prefLabels: %d" %
len(multiple_prefLabels))
print "\n".join([" %s" % subj for subj in multiple_prefLabels])
if both_composites:
print ("\nConcepts with both composite properties: %d" %
len(both_composites))
print "\n".join([" %s" % subj for subj in both_composites])
if bad_hidden_labels:
print "\nConcepts with bad hidden labels: %d" % len(bad_hidden_labels)
for kw, lbls in iteritems(bad_hidden_labels):
print " %s:" % kw
print "\n".join([" '%s'" % lbl for lbl in lbls])
if bad_alt_labels:
print "\nConcepts with bad alt labels: %d" % len(bad_alt_labels)
for kw, lbls in iteritems(bad_alt_labels):
print " %s:" % kw
print "\n".join([" '%s'" % lbl for lbl in lbls])
if both_skw_and_ckw:
print ("\nKeywords that are both skw and ckw: %d" %
len(both_skw_and_ckw))
print "\n".join([" %s" % subj for subj in both_skw_and_ckw])
print
if composite_problem1:
print "\n".join(["SKW '%s' references an unexisting CKW '%s'." %
(skw, ckw) for skw, ckw in composite_problem1])
if composite_problem2:
print "\n".join(["SKW '%s' references a SKW '%s'." %
(skw, ckw) for skw, ckw in composite_problem2])
if composite_problem3:
print "\n".join(["SKW '%s' is not composite of CKW '%s'." %
(skw, ckw) for skw, ckw in composite_problem3])
if composite_problem4:
for skw, ckws in iteritems(composite_problem4):
print "SKW '%s' does not exist but is " "referenced by:" % skw
print "\n".join([" %s" % ckw for ckw in ckws])
if composite_problem5:
print "\n".join(["CKW '%s' references a CKW '%s'." % kw
for kw in composite_problem5])
if composite_problem6:
print "\n".join(["CKW '%s' is not composed by SKW '%s'." % kw
for kw in composite_problem6])
print "\n==== WARNINGS ===="
if bad_notes:
print ("\nConcepts with bad notes: %d" % len(bad_notes))
print "\n".join([" '%s': '%s'" % note for note in bad_notes])
if stemming_collisions:
print ("\nFollowing keywords have unnecessary labels that have "
"already been generated by BibClassify.")
for subj in stemming_collisions:
print " %s:\n %s\n and %s" % subj
print "\nFinished."
sys.exit(0)
def test_cache(taxonomy_name='HEP', rebuild_cache=False, no_cache=False):
cache = get_cache(taxonomy_name)
if not cache:
set_cache(taxonomy_name, get_regular_expressions(taxonomy_name,
rebuild=rebuild_cache, no_cache=no_cache))
cache = get_cache(taxonomy_name)
return (thread.get_ident(), cache)
log.info('Loaded ontology reader')
if __name__ == '__main__':
test_cache()
c4science · Help