def show(req, search = None):
urlexpander = lambda url: _html_url(req, url)
qsearch = req.REQUEST.get('q', '')
if not search:
search = qsearch
dict = {}
dict['alltags'] = _alltags()
dict['alldocs'] = Doc
dict['menuitems'] = [
('/kb/', 'Knowledgebase'),
]
doc = Doc.try_get(id=atoi(search))
if doc: search = qsearch # the old search was really a docid
tag,tagdocs = _tagdocs(search)
print 'tds: %r %r %r' % (search, tag, tagdocs)
if search:
dict['urlappend'] = '?q=%s' % search
want_words = search.lower().split()
if search:
if tag:
dict['menuitems'].append(('/kb/%s' % search, tag))
else:
dict['menuitems'].append(('/kb/%s' % search, '"%s"' % search))
if tag:
h = HtmlHighlighter([], '')
else:
h = HtmlHighlighter(want_words, 'u')
dict['search'] = search
if doc:
# View the specific article they requested.
doc.use_latest()
pagebase = doc.get_url()
page = pagebase + dict.get('urlappend', '')
if req.path != pagebase and req.path != urllib.unquote(pagebase):
return HttpResponsePermanentRedirect(page)
dict['page'] = page
if not tag and not search and doc.tags:
t = doc.tags[0]
dict['menuitems'].append(('/kb/%s' % t, t))
dict['menuitems'].append((page, 'KB%d' % doc.id))
dict['title'] = doc.title
dict['when'] = nicedate(doc.mtime)
dict['tags'] = doc.tags
dict['editurl'] = doc.get_edit_url()
dict['pdfurl'] = doc.get_pdf_url()
dict['text'] = h.highlight(doc.expanded_text(urlexpander,
headerdepth=3,
expandbooks=0),
markdown.markdown)
dict['reference_parents'] = list(doc.reference_parents())
dict['similar'] = doc.similar(max=4)
dict['dissimilar'] = doc.dissimilar(max=4)
if tag:
dict['search'] = ''
return render_to_response('ekb/view.html', dict)
else:
# Search for matching articles
page = '/kb/%s' % search
dict['page'] = page
if tag:
# the search term is actually the name of a tag
f = tagdocs
dict['skip_tags'] = 1
dict['title'] = 'Category: %s' % tag
dict['search'] = ''
elif search:
# the search term is just a search term
dict['title'] = 'Search: "%s"' % search
words = []
docids = list(db.selectcol('select docid from WordWeights '
' where word=?', want_words[0]))
for word in want_words[1:]:
if not docids:
# no remaining matches
break
docids = list(db.selectcol('select docid from WordWeights '
' where word=? and docid in (%s)'
% _marks(docids),
word, *docids))
l = want_words + docids
docweights = db.select('select avg(weight)*count(weight), docid '
' from WordWeights '
' where word in (%s) and docid in (%s) '
' group by docid '
% (_marks(want_words), _marks(docids)),
*l)
f = []
for weight,docid in sorted(docweights):
if weight > 0.0:
f.append(docid)
else:
# there is no search term; toplevel index
dict['title'] = 'Knowledgebase'
return render_to_response('ekb/kb.html', dict)
dict['docs'] = []
for docid in f:
d = Doc(docid)
d.autosummary = autosummarize(d.expanded_text(urlexpander,
headerdepth=1,
expandbooks=1),
want_words, h.highlight)
dict['docs'].append(d)
return render_to_response('ekb/search.html', dict)
def _alltags():
return db.select('select tag,count(tag) '
' from Tags '
' group by tag '
' order by tag ')
