def test_mentionize_text(self):
'''this test also test implicitly
test extract_first_matching_mentioned_author'''
text = "oh hai @user1 how are you? @UsEr1"
expected_output = 'oh hai <a href="%(user_url)s">@user1</a> how are you?'
expected_output += ' <a href="%(user_url)s">@user1</a>'
anticipated_authors = [self.u1,]
mentioned_authors, output = markup.mentionize_text(text, anticipated_authors)
self.assertTrue(self.u1 in mentioned_authors)
self.assertEquals(output, expected_output % {'user_url': self.u1.get_profile_url()})
def parse_post_text(post):
"""typically post has a field to store raw source text
in comment it is called .comment, in Question and Answer it is
called .text
also there is another field called .html (consistent across models)
so the goal of this function is to render raw text into .html
and extract any metadata given stored in source (currently
this metadata is limited by twitter style @mentions
but there may be more in the future
function returns a dictionary with the following keys
html
newly_mentioned_users - list of <User> objects
removed_mentions - list of mention <Activity> objects - for removed ones
"""
text = post.get_text()
if post._escape_html:
text = cgi.escape(text)
if post._urlize:
text = html.urlize(text)
if post._use_markdown:
text = sanitize_html(markup.get_parser().convert(text))
#todo, add markdown parser call conditional on
#post.use_markdown flag
post_html = text
mentioned_authors = list()
removed_mentions = list()
if '@' in text:
op = post.get_origin_post()
anticipated_authors = op.get_author_list(include_comments=True,
recursive=True)
extra_name_seeds = markup.extract_mentioned_name_seeds(text)
extra_authors = set()
for name_seed in extra_name_seeds:
extra_authors.update(
User.objects.filter(username__istartswith=name_seed))
#it is important to preserve order here so that authors of post
#get mentioned first
anticipated_authors += list(extra_authors)
mentioned_authors, post_html = markup.mentionize_text(
text, anticipated_authors)
#find mentions that were removed and identify any previously
#entered mentions so that we can send alerts on only new ones
from askbot.models.user import Activity
if post.pk is not None:
#only look for previous mentions if post was already saved before
prev_mention_qs = Activity.objects.get_mentions(mentioned_in=post)
new_set = set(mentioned_authors)
for prev_mention in prev_mention_qs:
user = prev_mention.get_mentioned_user()
if user is None:
continue
if user in new_set:
#don't report mention twice
new_set.remove(user)
else:
removed_mentions.append(prev_mention)
mentioned_authors = list(new_set)
data = {
'html': post_html,
'newly_mentioned_users': mentioned_authors,
'removed_mentions': removed_mentions,
}
return data
def parse_post_text(post):
"""typically post has a field to store raw source text
in comment it is called .comment, in Question and Answer it is
called .text
also there is another field called .html (consistent across models)
so the goal of this function is to render raw text into .html
and extract any metadata given stored in source (currently
this metadata is limited by twitter style @mentions
but there may be more in the future
function returns a dictionary with the following keys
html
newly_mentioned_users - list of <User> objects
removed_mentions - list of mention <Activity> objects - for removed ones
"""
text = post.get_text()
if post._escape_html:
text = cgi.escape(text)
if post._urlize:
text = html.urlize(text)
if post._use_markdown:
text = sanitize_html(markup.get_parser().convert(text))
#todo, add markdown parser call conditional on
#post.use_markdown flag
post_html = text
mentioned_authors = list()
removed_mentions = list()
if '@' in text:
op = post.get_origin_post()
anticipated_authors = op.get_author_list(
include_comments = True,
recursive = True
)
extra_name_seeds = markup.extract_mentioned_name_seeds(text)
extra_authors = set()
for name_seed in extra_name_seeds:
extra_authors.update(User.objects.filter(
username__startswith = name_seed
)
)
#it is important to preserve order here so that authors of post
#get mentioned first
anticipated_authors += list(extra_authors)
mentioned_authors, post_html = markup.mentionize_text(
text,
anticipated_authors
)
#find mentions that were removed and identify any previously
#entered mentions so that we can send alerts on only new ones
from askbot.models.user import Activity
if post.pk is not None:
#only look for previous mentions if post was already saved before
prev_mention_qs = Activity.objects.get_mentions(
mentioned_in = post
)
new_set = set(mentioned_authors)
for prev_mention in prev_mention_qs:
user = prev_mention.get_mentioned_user()
if user is None:
continue
if user in new_set:
#don't report mention twice
new_set.remove(user)
else:
removed_mentions.append(prev_mention)
mentioned_authors = list(new_set)
data = {
'html': post_html,
'newly_mentioned_users': mentioned_authors,
'removed_mentions': removed_mentions,
}
return data