def search():
with ScopedSession() as session:
q = flask.request.args.get('query')
query = session.query(Comment, User, Post, func.ts_headline('russian', Comment.text, func.plainto_tsquery('russian', q), 'HighlightAll=true').label('highlighted')).filter(Comment.user_id == User.user_id).filter(Comment.post_id == Post.post_id)
query = query.filter(func.to_tsvector('russian', Comment.text).op('@@')(func.plainto_tsquery('russian', q)))
comments = []
for comment, user, post, highlighted in query.order_by(func.ts_rank_cd(func.to_tsvector('russian', Comment.text), func.plainto_tsquery('russian', q)).desc(), Comment.posted.desc()).limit(100).all():
comments.append({
"id": comment.comment_id,
"parent_id": comment.parent_id,
"post_id": comment.post_id,
"text": normalize_text(highlighted),
"posted": comment.posted.strftime(DATE_FORMAT),
"user_id": user.user_id,
"user_name": user.name,
"user_avatar": user.avatar_hash,
"comment_list_id": post.comment_list_id
})
resp = app.make_response(json.dumps(comments, ensure_ascii=False))
resp.mimetype = 'application/json; charset=utf-8'
resp.headers['Access-Control-Allow-Origin'] = '*'
return resp
def fetch_content(query_text, column, text_column, page, sources=None):
session = g.session
tsq = build_tsquery(query_text)
search = None
if column == db.WebPages.title:
query = session \
.query(db.WebPages, func.ts_rank_cd(func.to_tsvector("english", column), func.to_tsquery(tsq))) \
.filter( \
func.to_tsvector("english", column).match(tsq, postgresql_regconfig='english') \
) \
.order_by(func.ts_rank_cd(func.to_tsvector("english", column), func.to_tsquery(tsq)).desc())
elif column == db.WebPages.tsv_content:
query = session \
.query(db.WebPages, func.ts_rank_cd(column, func.to_tsquery(tsq))) \
.filter( column.match(tsq) )
if "'" in query_text or '"' in query_text:
search = query_text.replace("!", " ").replace("?", " ").replace(
"'", " ").replace('"', " ").replace(',',
" ").replace('.',
" ").strip()
while " " in search:
search = search.replace(" ", " ")
search = search.strip()
search = '%{}%'.format(search.lower())
query = query.filter(func.lower(text_column).like(search))
query = query.order_by(
func.ts_rank_cd(column, func.to_tsquery(tsq)).desc())
if sources:
query = query.filter(db.WebPages.netloc.in_(sources))
else:
raise ValueError("Wat?")
print(str(query.statement.compile(dialect=postgresql.dialect())))
print("param: '%s', '%s', '%s'" % (tsq, sources, search))
try:
entries = paginate(query, page, per_page=50)
except sqlalchemy.exc.ProgrammingError:
traceback.print_exc()
print("ProgrammingError - Rolling back!")
g.session.rollback()
raise
except sqlalchemy.exc.InternalError:
traceback.print_exc()
print("InternalError - Rolling back!")
g.session.rollback()
raise
except sqlalchemy.exc.OperationalError:
traceback.print_exc()
print("InternalError - Rolling back!")
g.session.rollback()
raise
return entries
def fetch_content(query_text, column, text_column, page, sources=None):
session = g.session
tsq = build_tsquery(query_text)
search = None
if column == db.WebPages.title:
query = session \
.query(db.WebPages, func.ts_rank_cd(func.to_tsvector("english", column), func.to_tsquery(tsq))) \
.filter( \
func.to_tsvector("english", column).match(tsq, postgresql_regconfig='english') \
) \
.order_by(func.ts_rank_cd(func.to_tsvector("english", column), func.to_tsquery(tsq)).desc())
elif column == db.WebPages.tsv_content:
query = session \
.query(db.WebPages, func.ts_rank_cd(column, func.to_tsquery(tsq))) \
.filter( column.match(tsq) )
if "'" in query_text or '"' in query_text:
search = query_text.replace("!", " ").replace("?", " ").replace("'", " ").replace('"', " ").replace(',', " ").replace('.', " ").strip()
while " " in search:
search = search.replace(" ", " ")
search = search.strip()
search = '%{}%'.format(search.lower())
query = query.filter( func.lower(text_column).like(search) )
query = query.order_by(func.ts_rank_cd(column, func.to_tsquery(tsq)).desc())
if sources:
query = query.filter(db.WebPages.netloc.in_(sources))
else:
raise ValueError("Wat?")
print(str(query.statement.compile(dialect=postgresql.dialect())))
print("param: '%s', '%s', '%s'" % (tsq, sources, search))
try:
entries = paginate(query, page, per_page=50)
except sqlalchemy.exc.ProgrammingError:
traceback.print_exc()
print("ProgrammingError - Rolling back!")
g.session.rollback()
raise
except sqlalchemy.exc.InternalError:
traceback.print_exc()
print("InternalError - Rolling back!")
g.session.rollback()
raise
except sqlalchemy.exc.OperationalError:
traceback.print_exc()
print("InternalError - Rolling back!")
g.session.rollback()
raise
return entries
def fetch_content(query_text, column, page, sources=None):
session = db.get_session()
tsq = build_tsquery(query_text)
if column == db.WebPages.title:
query = session \
.query(db.WebPages, func.ts_rank_cd(func.to_tsvector("english", column), func.to_tsquery(tsq))) \
.filter( \
func.to_tsvector("english", column).match(tsq, postgresql_regconfig='english') \
) \
.order_by(func.ts_rank_cd(func.to_tsvector("english", column), func.to_tsquery(tsq)).desc())
elif column == db.WebPages.tsv_content:
query = session \
.query(db.WebPages, func.ts_rank_cd(column, func.to_tsquery(tsq))) \
.filter( column.match(tsq) ) \
.order_by(func.ts_rank_cd(column, func.to_tsquery(tsq)).desc())
if sources:
query = query.filter(db.WebPages.netloc.in_(sources))
else:
raise ValueError("Wat?")
# print(str(query.statement.compile(dialect=postgresql.dialect())))
# print("param: '%s'" % tsq)
try:
entries = paginate(query, page, per_page=50)
except sqlalchemy.exc.ProgrammingError:
traceback.print_exc()
print("ProgrammingError - Rolling back!")
db.get_session().rollback()
raise
except sqlalchemy.exc.InternalError:
traceback.print_exc()
print("InternalError - Rolling back!")
db.get_session().rollback()
raise
except sqlalchemy.exc.OperationalError:
traceback.print_exc()
print("InternalError - Rolling back!")
db.get_session().rollback()
raise
return entries
def fetch_all_by_tsquery(self, tsquery, *expr, **kwargs):
"""
Returns all structures whose abstract matches the keywords given in the
keyword string.
Parameters
----------
tsquery : str
A string containing the lexme that will be used for searching. The
string will be automatically casted into a tsquery through the to_tsquery()
function.
weights : list, default=[0.1, 0.2, 0.4, 1.0]
The weights specify how heavily to weigh each category of word, in the
order [D-weight, C-weight, B-weight, A-weight].
normalization : int, default=32
Option that specifies whether and how a document's length should impact
its rank. The integer option controls several behaviors, so it is a
bit mask: you can specify one or more behaviors using | (for example, 2|4).
- 0 ignores the document length
- 1 divides the rank by 1 + the logarithm of the document length
- 2 divides the rank by the document length
- 4 divides the rank by the mean harmonic distance between extents
(this is implemented only by ts_rank_cd)
- 8 divides the rank by the number of unique words in document
- 16 divides the rank by 1 + the logarithm of the number of unique
words in document
- 32 divides the rank by itself + 1
min_words : int, default=10
max_words : int, default=25
Returns
-------
resultset : list
List containing tuples in the form (Structure, snippet, rank).
The snippet is the part of the abstract that matches the query.
Ordered by rank.
Notes
-----
- http://www.postgresql.org/docs/current/interactive/datatype-textsearch.html
Examples
--------
>>> StructureAdaptor().fetch_all_by_tsquery('imatinib')
[(<Structure(3FW1)>, u'[Imatinib] represents the first in a class', 0.54545500000000002),
(<Structure(2GQG)>, u'[imatinib], an inhibitor of BCR-ABL. Although', 0.375),
(<Structure(3CS9)>, u'[imatinib] against [imatinib]-resistant Bcr-Abl. Consistent', 0.33333299999999999),
(<Structure(2HYY)>, u'[imatinib] as first-line therapy', 0.230769),
(<Structure(3G0F)>, u'[imatinib] mesylate and sunitinib malate', 0.230769),
(<Structure(3G0E)>, u'[imatinib] mesylate and sunitinib malate', 0.230769),
(<Structure(1T46)>, u'[Imatinib] or Gleevec) demonstrates that', 0.090909100000000007)]
"""
weights = kwargs.get('weights', [0.1, 0.2, 0.4, 1.0])
normalization = kwargs.get('normalization', 32)
min_words, max_words = kwargs.get('min_words',
10), kwargs.get('max_words', 25)
if kwargs.get('plain'):
tsquery = func.plainto_tsquery('english', tsquery)
else:
tsquery = func.to_tsquery('english', tsquery)
# basic query construct
query = self.query.join('XRefs').filter(and_(*expr))
query = query.join(
citations,
and_(citations.c.pubmed_id == cast(XRef.xref, Integer),
XRef.source == 'PubMed'))
# GIST index that is used for searching
index = func.to_tsvector('english',
citations.c.abstract).op('@@')(tsquery)
query = query.filter(index).order_by("rank DESC")
# calculated rank of the hit
rank = func.ts_rank_cd(
weights, func.to_tsvector('english', citations.c.abstract),
tsquery, normalization).label('rank')
query = query.add_column(rank)
if kwargs.get('snippet'):
# configuration of the preview snippet
headline_conf = 'StartSel=[, StopSel=], MaxWords={0}, MinWords={1}'.format(
max_words, min_words)
# function to create a preview snippet of the matched area
snippet = func.ts_headline('english', citations.c.abstract,
tsquery, headline_conf).label('snippet')
# add snippet column to query
query = query.add_column(snippet)
return query
def filter_field(self, field, op, value):
"""
Applies a filter on a field.
Notes on 'ne' op:
Example data: [None, 'john', 'roger']
ne:john would return only roger (i.e. nulls excluded)
ne: would return john and roger
Notes on 'search' op:
For some reason, SQLAlchemy uses to_tsquery rather than
plainto_tsquery for the match operator
to_tsquery uses operators (&, |, ! etc.) while
plainto_tsquery tokenises the input string and uses AND between
tokens, hence plainto_tsquery is what we want here
For other database back ends, the behaviour of the match
operator is completely different - see:
http://docs.sqlalchemy.org/en/rel_1_0/core/sqlelement.html
:param field: field name
:param op: 'eq', 'ne', 'gt', 'lt', 'ge', 'le' or 'search'
:param value: comparison value, string or list/tuple
:return:
"""
app = self.app
odm = app.odm()
query = self.sql_query
if field.model:
field_model = self.app.models.get(field.model)
if not field_model:
return
db_model = field_model.db_model()
field = getattr(db_model, field.name, None)
if field is None:
field = getattr(db_model, field_model.id_field, None)
if not field:
return
if field_model.identifier not in self.joins:
self.joins.add(field_model.identifier)
query = query.join(db_model)
elif isinstance(field.field, str):
field = getattr(self.model.db_model(), field.name, None)
else:
field = None
if not field:
return
multiple = isinstance(value, (list, tuple))
if value == '':
value = None
if multiple and op in ('eq', 'ne'):
if op == 'eq':
query = query.filter(field.in_(value))
elif op == 'ne':
query = query.filter(~field.in_(value))
else:
if multiple:
assert len(value) > 0
value = value[0]
if op == 'eq':
query = query.filter(field == value)
elif op == 'ne':
query = query.filter(field != value)
elif op == 'search':
dialect_name = odm.binds[odm[self.name].__table__].dialect.name
if dialect_name == 'postgresql':
ts_config = field.info.get(
'text_search_config',
app.config['DEFAULT_TEXT_SEARCH_CONFIG'])
query = query.filter(
func.to_tsvector(ts_config,
cast(field, String)).op('@@')(
func.plainto_tsquery(value)))
else:
query = query.filter(field.match(value))
elif op == 'gt':
query = query.filter(field > value)
elif op == 'ge':
query = query.filter(field >= value)
elif op == 'lt':
query = query.filter(field < value)
elif op == 'le':
query = query.filter(field <= value)
self.sql_query = query
return self
def filter_field(self, field, op, value):
"""
Applies a filter on a field.
Notes on 'ne' op:
Example data: [None, 'john', 'roger']
ne:john would return only roger (i.e. nulls excluded)
ne: would return john and roger
Notes on 'search' op:
For some reason, SQLAlchemy uses to_tsquery rather than
plainto_tsquery for the match operator
to_tsquery uses operators (&, |, ! etc.) while
plainto_tsquery tokenises the input string and uses AND between
tokens, hence plainto_tsquery is what we want here
For other database back ends, the behaviour of the match
operator is completely different - see:
http://docs.sqlalchemy.org/en/rel_1_0/core/sqlelement.html
:param field: field name
:param op: 'eq', 'ne', 'gt', 'lt', 'ge', 'le' or 'search'
:param value: comparison value, string or list/tuple
:return:
"""
app = self.app
odm = app.odm()
query = self.sql_query
if field.model:
field_model = self.app.models.get(field.model)
if not field_model:
return
db_model = field_model.db_model()
field = getattr(db_model, field.name, None)
if field is None:
field = getattr(db_model, field_model.id_field, None)
if not field:
return
if field_model.identifier not in self.joins:
self.joins.add(field_model.identifier)
query = query.join(db_model)
elif isinstance(field.field, str):
field = getattr(self.model.db_model(), field.name, None)
else:
field = None
if not field:
return
multiple = isinstance(value, (list, tuple))
if value == '':
value = None
if multiple and op in ('eq', 'ne'):
if op == 'eq':
query = query.filter(field.in_(value))
elif op == 'ne':
query = query.filter(~field.in_(value))
else:
if multiple:
assert len(value) > 0
value = value[0]
if op == 'eq':
query = query.filter(field == value)
elif op == 'ne':
query = query.filter(field != value)
elif op == 'search':
dialect_name = odm.binds[odm[self.name].__table__].dialect.name
if dialect_name == 'postgresql':
ts_config = field.info.get(
'text_search_config',
app.config['DEFAULT_TEXT_SEARCH_CONFIG']
)
query = query.filter(
func.to_tsvector(ts_config, cast(field, String)).op(
'@@')(func.plainto_tsquery(value))
)
else:
query = query.filter(field.match(value))
elif op == 'gt':
query = query.filter(field > value)
elif op == 'ge':
query = query.filter(field >= value)
elif op == 'lt':
query = query.filter(field < value)
elif op == 'le':
query = query.filter(field <= value)
self.sql_query = query
return self