def query(self, qs="", method="", method_arg="", limit="", sort_order=["rowid"], raw_results=False, **metadata):
"""query the PhiloLogic database"""
method = method or "proxy"
if isinstance(method_arg, str):
try:
method_arg = int(method_arg)
except:
if method == "cooc" or method == "sentence":
method_arg = 6
else:
method_arg = 0
if isinstance(limit, str):
try:
limit = int(limit)
except:
limit = 10000000
hash = hashlib.sha1()
hash.update(self.path.encode('utf8'))
has_metadata = False
corpus_file = None
for key, value in list(metadata.items()):
if isinstance(value, str):
if value == "":
pass
else:
value = [value]
metadata[key] = value
value = [v for v in value if v]
if value:
has_metadata = True
key_value = "%s=%s" % (key, "|".join(value))
hash.update(key_value.encode('utf8'))
if has_metadata:
corpus_hash = hash.hexdigest()
corpus_file = self.path + "/hitlists/" + corpus_hash + ".hitlist"
if not os.path.isfile(corpus_file):
# before we query, we need to figure out what type each parameter belongs to,
# and sort them into a list of dictionaries, one for each type.
metadata_dicts = [{} for level in self.locals["metadata_hierarchy"]]
# print >> sys.stderr, "querying %s" % repr(metadata.items())
for k, v in list(metadata.items()):
for i, params in enumerate(self.locals["metadata_hierarchy"]):
if v and (k in params):
metadata_dicts[i][k] = v
if k in self.locals["metadata_types"]:
this_type = self.locals["metadata_types"][k]
if this_type == "div":
metadata_dicts[i]["philo_type"] = ['"div"|"div1"|"div2"|"div3"']
else:
metadata_dicts[i]["philo_type"] = ['"%s"' % self.locals["metadata_types"][k]]
metadata_dicts = [d for d in metadata_dicts if d]
if "philo_id" in metadata:
if metadata_dicts:
metadata_dicts[-1]["philo_id"] = metadata["philo_id"]
else:
metadata_dicts.append({"philo_id": metadata["philo_id"]})
corpus = MetadataQuery.metadata_query(self, corpus_file, metadata_dicts, sort_order)
else:
if sort_order == ["rowid"]:
sort_order = None
corpus = HitList.HitList(corpus_file, 0, self, sort_order=sort_order, raw=raw_results)
corpus.finish()
if len(corpus) == 0:
return corpus
else:
corpus = None
if qs:
hash.update(qs.encode('utf8'))
hash.update(method.encode('utf8'))
hash.update(str(method_arg).encode('utf8'))
hash.update(str(limit).encode('utf8'))
search_hash = hash.hexdigest()
search_file = self.path + "/hitlists/" + search_hash + ".hitlist"
if sort_order == ["rowid"]:
sort_order = None
if not os.path.isfile(search_file):
return Query.query(self,
qs,
corpus_file,
self.width,
method,
method_arg,
limit,
filename=search_file,
sort_order=sort_order,
raw_results=raw_results)
else:
parsed = QuerySyntax.parse_query(qs)
grouped = QuerySyntax.group_terms(parsed)
split = Query.split_terms(grouped)
words_per_hit = len(split)
return HitList.HitList(search_file, words_per_hit, self, sort_order=sort_order, raw=raw_results)
else:
if corpus:
return corpus
else:
return self.get_all(self.locals["default_object_level"], sort_order)
def query(self, qs="", method="", method_arg="", limit="", sort_order=["rowid"], **metadata):
"""query the PhiloLogic database"""
method = method or "proxy"
if isinstance(method_arg, str):
try:
method_arg = int(method_arg)
except:
if method == "cooc" or method == "sentence":
method_arg = 6
else:
method_arg = 0
if isinstance(limit, str):
try:
limit = int(limit)
except:
limit = 10000000
hash = hashlib.sha1()
hash.update(self.path)
has_metadata = False
corpus_file = None
for key, value in metadata.items():
if isinstance(value, str):
if value == "":
pass
else:
value = [value]
metadata[key] = value
value = [v for v in value if v]
if value:
has_metadata = True
hash.update("%s=%s" % (key, "|".join(value)))
if has_metadata:
corpus_hash = hash.hexdigest()
corpus_file = self.path + "/hitlists/" + corpus_hash + ".hitlist"
corpus_width = 7
if not os.path.isfile(corpus_file):
# before we query, we need to figure out what type each parameter belongs to,
# and sort them into a list of dictionaries, one for each type.
metadata_dicts = [{} for level in self.locals["metadata_hierarchy"]]
# print >> sys.stderr, "querying %s" % repr(metadata.items())
for k, v in metadata.items():
for i, params in enumerate(self.locals["metadata_hierarchy"]):
if v and (k in params):
metadata_dicts[i][k] = v
if k in self.locals["metadata_types"]:
this_type = self.locals["metadata_types"][k]
if this_type == "div":
metadata_dicts[i]["philo_type"] = ['"div"|"div1"|"div2"|"div3"']
else:
metadata_dicts[i]["philo_type"] = ['"%s"' % self.locals["metadata_types"][k]]
metadata_dicts = [d for d in metadata_dicts if d]
if "philo_id" in metadata:
if metadata_dicts:
metadata_dicts[-1]["philo_id"] = metadata["philo_id"]
else:
metadata_dicts.append({"philo_id": metadata["philo_id"]})
corpus = MetadataQuery.metadata_query(self, corpus_file, metadata_dicts, sort_order)
else:
# print >> sys.stderr, "cached @ %s" % corpus_file
if sort_order == ["rowid"]:
sort_order = None
corpus = HitList.HitList(corpus_file, 0, self, sort_order=sort_order)
corpus.finish()
#print >> sys.stderr, "corpus file of length %d" % len(corpus)
if len(corpus) == 0:
return corpus
else:
corpus = None
if qs:
# words_per_hit = len(qs.split(" "))
# words_per_hit = len(qs.split("\n\n"))
hash.update(qs)
hash.update(method)
hash.update(str(method_arg))
hash.update(str(limit))
search_hash = hash.hexdigest()
search_file = self.path + "/hitlists/" + search_hash + ".hitlist"
if sort_order == ["rowid"]:
sort_order = None
if not os.path.isfile(search_file):
return Query.query(self, qs, corpus_file, self.width, method, method_arg, limit, filename=search_file, sort_order=sort_order)
else:
parsed = QuerySyntax.parse_query(qs)
grouped = QuerySyntax.group_terms(parsed)
split = Query.split_terms(grouped)
words_per_hit = len(split)
return HitList.HitList(search_file, words_per_hit, self, sort_order=sort_order)
else:
if corpus:
return corpus
else:
return self.get_all("doc", sort_order)
def query(self,
qs="",
method="",
method_arg=0,
limit=10000000,
**metadata):
"""query the PhiloLogic database"""
hash = hashlib.sha1()
hash.update(self.path)
has_metadata = False
corpus_file = None
for key, value in metadata.items():
if isinstance(value, str):
if value == "":
pass
else:
value = [value]
metadata[key] = value
value = [v for v in value if v]
if value:
has_metadata = True
hash.update("%s=%s" % (key, "|".join(value)))
if has_metadata:
corpus_hash = hash.hexdigest()
corpus_file = self.path + "/hitlists/" + corpus_hash + ".hitlist"
corpus_width = 7
if not os.path.isfile(corpus_file):
# before we query, we need to figure out what type each parameter belongs to,
# and sort them into a list of dictionaries, one for each type.
metadata_dicts = [
{} for level in self.locals["metadata_hierarchy"]
]
# print >> sys.stderr, "querying %s" % repr(metadata.items())
for k, v in metadata.items():
for i, params in enumerate(
self.locals["metadata_hierarchy"]):
if v and (k in params):
metadata_dicts[i][k] = v
if k in self.locals["metadata_types"]:
this_type = self.locals["metadata_types"][k]
if this_type == "div":
metadata_dicts[i]["philo_type"] = [
'"div"|"div1"|"div2"|"div3"'
]
else:
metadata_dicts[i]["philo_type"] = [
'"%s"' %
self.locals["metadata_types"][k]
]
metadata_dicts = [d for d in metadata_dicts if d]
if "philo_id" in metadata:
if metadata_dicts:
metadata_dicts[-1]["philo_id"] = metadata["philo_id"]
else:
metadata_dicts.append(
{"philo_id": metadata["philo_id"]})
corpus = MetadataQuery.metadata_query(self, corpus_file,
metadata_dicts)
else:
# print >> sys.stderr, "cached @ %s" % corpus_file
corpus = HitList.HitList(corpus_file, 0, self)
corpus.finish()
#print >> sys.stderr, "corpus file of length %d" % len(corpus)
if len(corpus) == 0:
return corpus
else:
corpus = None
if qs:
# words_per_hit = len(qs.split(" "))
# words_per_hit = len(qs.split("\n\n"))
hash.update(qs)
hash.update(method)
hash.update(str(method_arg))
hash.update(str(limit))
search_hash = hash.hexdigest()
search_file = self.path + "/hitlists/" + search_hash + ".hitlist"
if not os.path.isfile(search_file):
return Query.query(self,
qs,
corpus_file,
self.width,
method,
method_arg,
limit,
filename=search_file)
else:
parsed = QuerySyntax.parse_query(qs)
grouped = QuerySyntax.group_terms(parsed)
split = Query.split_terms(grouped)
words_per_hit = len(split)
# parsed = QuerySyntax.parse_query(qs)
# parsed_split = []
# for label,token in parsed:
# l,t = label,token
# if l == "QUOTE":
# subtokens = t[1:-1].split(" ")
# parsed_split += [("QUOTE_S",sub_t) for sub_t in subtokens if sub_t]
# else:
# parsed_split += [(l,t)]
# command = Query.format_parsed_query(parsed_split,self)
# words_per_hit = len(command.split("\n\n"))
return HitList.HitList(search_file, words_per_hit, self)
else:
if corpus:
return corpus
else:
return self.get_all("doc")
