def main():
g = Graph()
g.set_directed(False)
db = DBModel.get()
g.vertex_properties["subscribers"] = g.new_vertex_property("int")
g.vertex_properties["name"] = g.new_vertex_property("string")
vertices = dict()
# add all vertices to the graph
for subreddit in db.get_subreddits():
v = g.add_vertex()
g.vertex_properties["name"][v] = subreddit[0]
g.vertex_properties["subscribers"][v] = subreddit[1]
vertices[subreddit[0]] = v
# add all the edges
for link in db.get_all_links():
v1, v2 = link
source = vertices[v1]
target = vertices[v2]
g.add_edge(source, target)
db.close()
g.save("data/reddit.gml")
def retry():
global choice_bodies, candidates, top
top += 1
if top + 1 >= len(candidates):
r = HTTPResponse(status=500)
r.set_header('Content-Type', 'application/json')
r.set_header('Access-Control-Allow-Origin', '*')
return r
restaurant_db = DBModel('gourmet', 'localhost', 'foo', 'bar')
name_result = restaurant_db.select('SELECT name FROM restaurants WHERE id={}'.format(
choice_bodies[top]['_source']['restaurant_id']
))
address_result = restaurant_db.select(
'SELECT address FROM restaurants WHERE id={}'.format(
choice_bodies[top]['_source']['restaurant_id']
)
)
restaurant = 'こちらのお店はいかがでしょうか？\n\n店名 : {}'.format(name_result[0])
if address_result[0] != 'nan':
restaurant += '\n住所 : {}'.format(address_result[0])
if len(candidates[top]) == 0 or candidates[top] is None:
recommend = 'このお店に行ったことがある人は，残念ながら見つかりませんでした．'
else:
recommend = 'このお店に行ったことがある人は次のような感想を述べています :'
for candidate in candidates[top]:
recommend += '\n\n・{}'.format(candidate)
dicts = [
{'restaurant': restaurant, 'recommend': recommend}
]
r = HTTPResponse(status=200, body=json.dumps(dicts, ensure_ascii=False))
r.set_header('Content-Type', 'application/json')
r.set_header('Access-Control-Allow-Origin', '*')
return r
def main():
model = DBModel.get()
print "[ ] Connecting.."
r = praw.Reddit(user_agent="/u/benediktkr/")
print "[ ] Logging in.."
r.login(username="******", password="******")
print "[ ] Starting.."
try:
while True:
# praw follows the guidelines on ratelimits
print " [ ] Fetching comments.."
comments = list(r.get_comments("all", limit=None))
print " [+] Fetched: {0} comments.".format(len(comments))
print " [ ] Processing"
for comment in comments:
username = str(comment.author)
subreddit = "/r/" + str(comment.subreddit).lower() + "/"
model.save_comment(username, subreddit)
print " [+] Done"
except KeyboardInterrupt:
model.close()
print "\n[!]Exiting"
def bfs(start_node):
f = open('data/reddit.txt', 'w')
db = DBModel.get()
todo = deque()
visited = set()
todo.append(start)
while len(todo) > 0:
here = todo.popleft()
if here in visited:
continue
visited.add(here)
this_subreddit = parse_sidebar(here)
db.save_subreddit(this_subreddit)
# Handle stuff about this node.
for subreddit in this_subreddit['links']:
if subreddit not in visited:
todo.append(subreddit)
link = (here, subreddit)
print link
db.save_link(link)
db.close()
f.close()
def get_reply(query):
global candidates, choice_bodies, top
candidates = []
choice_bodies = []
top = 0
parser.drop_morph(query)
word_pairs = word2vec_model.similar_words(parser.words)
word_pairs = word2vec_model.most_significant_word_pairs(word_pairs)
terms = [word for word, _ in word_pairs]
elastic_results = elastic_model.search_terms(terms)
bodies = elastic_results[0]
analyst = Analyst(word2vec_model, specific_parts=['普通名詞', '地名', '固有名詞', '組織名'])
all_sum_scores = []
all_scores = []
all_candidates = []
for body in elastic_results[0]:
analyst.parse(body['_source']['body'])
candidate_scores = np.array(analyst.calc_candidate_score())
query_base_scores = np.array(analyst.calc_query_base_score(parser.words))
scores = list(candidate_scores + query_base_scores)
all_sum_scores.append(sum(scores) / (len(scores) if len(scores) != 0 else 1))
all_scores.append(scores)
all_candidates.append(analyst.candidates)
indices = np.argsort(all_sum_scores)[::-1]
for index in indices:
choice_bodies.append(bodies[index])
candidates_ = analyst.most_significant_candidates(
all_scores[index],
all_candidates[index]
)
candidates.append(candidates_)
restaurant_db = DBModel('gourmet', 'localhost', 'foo', 'bar')
name_result = restaurant_db.select('SELECT name FROM restaurants WHERE id={};'.format(
choice_bodies[top]['_source']['restaurant_id']
))
address_result = restaurant_db.select(
'SELECT address FROM restaurants WHERE id={}'.format(
choice_bodies[top]['_source']['restaurant_id']
)
)
restaurant = 'こちらのお店はいかがでしょうか？\n\n店名 : {}'.format(name_result[0])
if address_result[0] != 'nan':
restaurant += '\n住所 : {}'.format(address_result[0])
if len(candidates[top]) == 0 or candidates[top] is None:
recommend = 'このお店に行ったことがある人は，残念ながら見つかりませんでした．'
else:
recommend = 'このお店に行った人は次のような感想を述べています :'
for candidate in candidates[top]:
recommend += '\n\n・{}'.format(candidate)
dicts = [
{'restaurant': restaurant, 'recommend': recommend}
]
return json.dumps(dicts, ensure_ascii=False)
