def crawler_process(self, process_name, lock, timeout_flag, browser_list,
crawl_queue, data_manager, crawled_articles,
new_blacklists, export_to_queue):
# Function: work as an worker in multiprocessed crawling
# Input:
# timeout_flag: shared variable to check if timeout happen
# lock: to acquire and release shared data
# browser_list: a shared queue of browser to release when timeout
# crawl_queue: a shared queue of "crawl task"
# data_manager: an object that support method to crawl. Important: this object can't be shared by multiprocessing lib, so output data must be shared in another queue. But input data have cleared _data articles but initial _blacklists link
# blacklists: Queue that contain blacklist links
# crawled_articles: Queue that contain new crawled articles
# push_to_queue: push new crawled articles to rabbit queue
# Output:
# blacklists will contain new and old blacklisted links
# crawled_aritlces: contain new crawled articles
print("Crawler %s has been started" % process_name)
browser = BrowserWrapper()
lock.acquire()
browser_list.put(browser)
lock.release()
non_job_list = []
job_list = []
finish = False
a = True
browser_profile = None
try:
while True:
print("Crawler %s is running" % process_name)
# get a web config from crawl_queue
webconfig = None
# get current profile of current browser
# process browser can only crawl task that have the same profile
if browser.get_browser() is not None:
browser_profile = browser.get_profile()
lock.acquire()
# epdb.set_trace()
# this browser have more job (in job_list) or global queue have more job not timeout
if (not crawl_queue.empty() or
job_list) and not finish and (timeout_flag.value == 0):
if len(job_list) > 0: # has job
webconfig = job_list.pop()
else: # first job or ready to get more "default profile" job
if browser_profile is None: # first job. Use next webconfig to create browser
# _print_crawl_queue(crawl_queue)
webconfig = crawl_queue.get()
browser_profile = webconfig.get_browser_profile()
if browser_profile != '': # not default profile
while (
not crawl_queue.empty()
): # get all job for this browser profile
temp_webconfig = crawl_queue.get()
if temp_webconfig.get_browser_profile(
) == browser_profile:
job_list.append(temp_webconfig)
else:
non_job_list.append(temp_webconfig)
while len(non_job_list
) > 0: # push back non-job to queue
crawl_queue.put(non_job_list.pop())
# _print_crawl_queue(crawl_queue)
else:
pass # any other default browser can get job
# use webconfig as first job to crawl
elif browser_profile == '': # get more "default profile" job
webconfig = crawl_queue.get()
browser_profile = webconfig.get_browser_profile()
if browser_profile != '': # not default profile
non_job_list.append(webconfig)
found = False
#epdb.set_trace()
while (
not crawl_queue.empty()
): # get all job for this browser profile
temp_webconfig = crawl_queue.get()
if temp_webconfig.get_browser_profile(
) == '':
job_list.append(
temp_webconfig) # get one job only
found = True
break
else:
non_job_list.append(temp_webconfig)
while len(non_job_list
) > 0: # push back non-job to queue
crawl_queue.put(non_job_list.pop())
if not found:
finish = True # no more default profile job
lock.release()
continue # kill browser in the next while
else:
pass # use webconfig to crawl
else: # all job for this browser profile are done
# push back data
finish = True
lock.release()
continue # kill browser in the next while
# webconfig is first job or next job in job_list to crawl
lock.release()
# crawl data
# epdb.set_trace()
crawl_type = webconfig.get_crawl_type()
if crawl_type == "newspaper":
print("Crawler %s is crawling newspaper %s" %
(process_name, webconfig.get_webname()))
data_manager.add_articles_from_newspaper(
process_name, webconfig, browser)
elif 'facebook' in crawl_type: # facebook user, facebook fanpage/groups
print("Crawler %s is crawling FB %s" %
(process_name, webconfig.get_webname()))
data_manager.add_articles_from_facebook(
process_name, webconfig, browser)
elif 'kols smcc' in crawl_type: # facebook user, facebook fanpage/groups
print(
"Crawler %s is crawling Kols post by using smcc service"
% process_name)
data_manager.add_articles_from_facebook_by_smcc(
process_name, webconfig)
time.sleep(10)
else: # timeout or no more job left
if timeout_flag.value != 0:
print("Crawler %s: timeout is detected. Finish" %
process_name)
elif crawl_queue.empty() and (not job_list):
print(
"Crawler %s: no more job for this crawler. Finish"
% process_name)
lock.release()
if browser is not None:
print("Quit browser in Crawler %s" % process_name)
browser.quit()
# output data to shared data
# push crawled articles to Queue
print("Crawler %s is putting crawled data to main queues" %
process_name)
lock.acquire()
print("Number of articles: %s" %
str(len(data_manager._data)))
new_articles = []
for article_id, article in data_manager._new_article.items(
):
crawled_articles.put(article)
new_articles.append(article)
# push newly added blacklist to Queue
# push data
print(
"Crawler %s: Push new crawled articles to database " %
process_name)
if export_to_queue:
try:
# push to RabbitMQ # for Bangtin project only
rb = RabbitMQ_Client()
rb.connect()
rb.push_to_queue(
new_articles
) # put new newspaper article to RabbitMQ
rb.disconnect()
except:
print_exception()
for href, count in data_manager._new_blacklist.items():
new_blacklists.put((href, count))
lock.release()
print("Crawler %s has finished" % process_name)
return None
except:
print_exception()
print("There are some error in crawler %s" % process_name)
if browser is not None:
print("Quit browser in Crawler %s" % process_name)
browser.quit()
def multiprocess_crawl(self):
# Create Manager Proxy to host shared data for multiprocessed crawled
with multiprocessing.Manager() as manager:
data_manager = self._data_manager
config_manager = self._config_manager
keyword_manager = self._keyword_manager
time.sleep(1)
print("Create Manager Proxy")
time.sleep(1)
print("Create shared object")
crawl_queue = manager.Queue()
crawled_articles = manager.Queue()
new_blacklists = manager.Queue()
browser_list = manager.Queue(
) # keep all firefox browser to release when timeout
lock = manager.Lock()
timeout_flag = manager.Value(
'i',
0) # shared variable to inform processes if timeout happends
# Init crawl queue
time.sleep(1)
print("Init crawl queue")
config_list = config_manager.get_newspaper_list()
number_of_job = 0
for webconfig in config_list:
# check delay time between crawl
last_run = webconfig.get_last_run()
min_duration = webconfig.get_minimum_duration_between_crawls()
time_pass = int(
(get_utc_now_date() - last_run).total_seconds() / 60)
if time_pass > min_duration:
# print("Print crawl_queue:")
# print(webconfig.get_crawl_url()) # for debug
crawl_queue.put(webconfig)
number_of_job += 1
webconfig.set_last_run() # set last_run to now
else:
web_name = webconfig.get_webname()
print(
"Ignore crawling %s. Need more %d minutes more to crawl"
% (web_name, min_duration - time_pass))
# Start crawl process
max_crawler = config_manager.get_max_crawler()
time.sleep(1)
print("%s crawlers are set to be run in parallel" %
str(max_crawler))
supported_max_crawler = get_max_crawler_can_be_run()
if supported_max_crawler == 0:
supported_max_crawler = 1
if max_crawler > supported_max_crawler:
time.sleep(1)
print(
"Current system can support only %s crawlers to be run in parallel"
% str(supported_max_crawler))
time.sleep(1)
print("You should reduce max_crawler in config.yaml")
time.sleep(1)
print("max_crawler will be set to %s in this run" %
str(supported_max_crawler))
max_crawler = supported_max_crawler
elif max_crawler < supported_max_crawler:
time.sleep(1)
print(
"Current system can support up to %s crawlers to be run in parallel"
% str(supported_max_crawler))
time.sleep(1)
print("You should increase max_crawler in config.yaml")
if max_crawler > int(number_of_job / 2):
time.sleep(1)
print("There are only %s newspaper to crawl" %
str(number_of_job))
time.sleep(1)
print("max_crawler will be set to %s for efficience" %
str(int(number_of_job / 2) + 1))
max_crawler = int(number_of_job / 2) + 1
crawler_processes = []
time.sleep(1)
print("Can run max to %s crawlers" % str(max_crawler))
timeout = config_manager.get_timeout()
start = time.time()
alive_crawler = 0
running = True
start_timeout = 0
is_timeout = False
terminate_time = 120 # 2 min
crawler_iterator = 0
while running:
# count alive crawler
running_crawler = ''
alive_crawler = 0
running = False
for process in crawler_processes:
if process.is_alive():
alive_crawler += 1
running_crawler = running_crawler + " %s " % str(
alive_crawler)
running = True
if running:
print("Running crawler:")
print(running_crawler)
else: # not running process
lock.acquire()
if crawl_queue.empty():
lock.release()
break
running = True
lock.release()
# create new crawler if needed
lock.acquire()
if alive_crawler < max_crawler and not crawl_queue.empty(
) and not is_timeout: # have more jobs that current browser can't crawl. Maybe need another browser_profiles
#epdb.set_trace()
lock.release()
print("Can create more crawler")
crawler_iterator += 1
crawler = multiprocessing.Process(
target=self.crawler_process,
args=(str(crawler_iterator), lock, timeout_flag,
browser_list, crawl_queue, data_manager,
crawled_articles, new_blacklists,
self._export_to_queue))
crawler_processes.append(crawler)
crawler.start()
time.sleep(1)
print("Start crawler number %s (pid: %s)" %
(str(crawler_iterator), crawler.pid))
else:
lock.release()
# kill all process after timeout
if not is_timeout:
print("Remaining seconds to timeout %s" %
str(int(timeout - time.time() + start)))
else:
print(
"Remaining seconds to terminate %s" %
str(int(terminate_time - time.time() + start_timeout)))
if (time.time() - start > timeout) and (not is_timeout):
start_timeout = time.time()
print("Timeout")
print(
"Inform all processes about timeout. Terminate all after 2 min"
)
lock.acquire()
timeout_flag.value = 1
lock.release()
is_timeout = True
if (timeout_flag.value == 1) and (time.time() - start_timeout
>= terminate_time):
print("Kill unquited browser")
while not browser_list.empty():
lock.acquire()
browser = browser_list.get()
print("Found a running browser")
print(browser)
print("Close browser")
browser.quit()
lock.release()
print("Kill all processes")
for crawler in crawler_processes:
crawler.terminate()
# some processes may be not terminate. Don't know why
#crawler.join()
running = False
time.sleep(10)
# join process to wait for all crawler to finish
#for crawler in crawler_processes:
# crawler.join()
time.sleep(1)
print("Finish crawling")
time.sleep(1)
# Save all new crawled articles and push to ElasticSearch + RabbitMQ
print("New crawled articles")
rb = RabbitMQ_Client()
rb_articles = []
while not crawled_articles.empty():
article = crawled_articles.get()
if article.get_id() not in data_manager._data:
data_manager._data[article.get_id(
)] = article # merge new articles to data
rb_articles.append(article)
print("%s: %s" %
(article.get_newspaper(), article.get_topic()))
while not new_blacklists.empty():
href, count = new_blacklists.get()
data_manager._blacklist[href] = count
# analyze keyword
print("Analyze keywords")
keyword_manager.build_keyword_list()
print("Export data to json files")
# export data
trending_keywords = keyword_manager.write_trending_keyword_by_growing_speed_to_json_file(
)
if self._export_to_json:
data_manager.export_to_json()
keyword_manager.write_fast_growing_keyword_to_json_file()
keyword_manager.write_uncategorized_keyword_to_text_file()
keyword_manager.write_trending_article_to_json_file()
keyword_manager.write_hot_growing_article_to_json_file()
keyword_manager.write_keyword_dicts_to_json_file()
keyword_manager.write_keyword_freq_series_to_json_file()
keyword_manager.write_new_keyword_to_json_file()
trends = []
for topic in trending_keywords[:min(40, len(trending_keywords))]:
print('trending topic: %s' % topic)
articles = data_manager.get_latest_article_contain_keyword(
topic, number=6)
first_article = articles[0]
posts = []
print('relate article: ')
for article in articles:
posts.append(str(article.get_id()))
print(article.get_topic())
print(posts)
#trends.append({'topic': topic, 'posts': posts})
trends.append({
'topic': first_article.get_topic(),
'posts': posts
})
# push data
print("Push data to database and other services")
if self._export_to_queue:
try:
# push to RabbitMQ # for Bangtin project only
rb.connect()
rb.push_trends_to_queue(trends)
rb.disconnect()
except:
print_exception()
if self._export_to_wordpress:
try:
# push to wordpress
wp = Wordpress()
for article in rb_articles:
if article.get_post_type() == 0: # newspaper post
topic = article.get_topic().lower()
# trending = False
# if trending_keywords:
# for keyword in trending_keywords:
# if keyword in topic:
# trending = True
# break
post_id = wp.add_new_article(article, [])
if post_id:
article.set_wordpress_id(post_id)
#sleep(15) # avoid being banned by wordpress host
except:
print_exception()
if self._export_to_elasticsearch:
try:
# push to Elasticsearch
es = ElasticSearch_Client()
for article in rb_articles:
es.push_article(
article) # put new article to ElasticSearch
except:
print_exception()
# write log data
try:
with open_utf8_file_to_write(
get_independent_os_path(["export",
"log_data.json"])) as stream:
log_dict = dict()
update_time = get_date_string(
get_utc_now_date(),
date_format="%d/%m/%Y %H:%M",
timezone=config_manager.get_display_timezone())
log_dict['update_time'] = update_time
log_dict['newspaper_count'] = str(
config_manager.get_newspaper_count())
log_dict['database_count'] = str(
data_manager.count_database())
log_dict['hub_title'] = config_manager.get_hub_title()
log_dict['hub_href'] = config_manager.get_hub_href()
stream.write(jsonpickle.encode(log_dict))
stream.close()
except:
print_exception()
print("FINISH")
import os
from src.backend.lib.data import ArticleManager
from src.backend.lib.rabbitmq_client import RabbitMQ_Client
from src.backend.lib.utils import get_independent_os_path
base_dir = os.environ['DOCBAO_BASE_DIR']
rb = RabbitMQ_Client()
rb.connect()
data_manager = ArticleManager(None, get_independent_os_path([base_dir, 'src', 'backend', 'data', 'article.dat']),get_independent_os_path([base_dir, 'src', 'backend', "data","blacklist.dat"]) ) #article database object
data_manager.load_data()
print("PUSH ALL ARTICLES TO RABBITMQ")
rb.push_to_queue(data_manager._data.values())