def __queue_smart_crawl_start(workspace_id, job_id, page_limit, broadness,
urls, page_model):
'''
{
"workspace_id": "workspace id",
"id": "crawl id",
"page_limit": 100
"broadness": "BROAD" # Valid codes are["N10", "N100", "N1000", "N10000", "BROAD"],
"urls": ["http://example.com", "http://example.com/2"],
"page_model": "b64-encoded page classifier",
}
'''
message = {
'workspace_id':
workspace_id, #Singleton.getInstance().mongo_instance.get_current_workspace_name(),
'id': job_id,
'page_limit': page_limit,
'broadness': broadness,
'urls': urls,
'page_model': page_model,
}
logging.info(message)
Singleton.getInstance().broker_service.add_message_to_dd_crawler_input(
message)
def queue_broad_crawl(workspace_id, job_id, num_to_fetch,
broad_crawler_provider, broad_crawler_sources):
# keywords = dao_get_keywords()
keywords = dao_get_keywords_by_relevance(workspace_id)
categorized_urls = get_seeds_urls_categorized(workspace_id)
existent_url = get_relevant_or_neutral_seeds_urls_url(workspace_id)
# jobId = str(uuid.uuid1())
logging.info("sending broad crawl message for %s urls with keywords %s" %
(str(num_to_fetch), str(keywords)))
message = {
'included': keywords['included'],
'excluded': keywords['excluded'],
'relevantUrl': categorized_urls['relevant'],
'irrelevantUrl': categorized_urls['irrelevant'],
'nResults': int(num_to_fetch),
'existentUrl': existent_url, #get_seeds_urls_url(),
# 'appInstance': Singleton.getInstance().app_instance,
'workspace':
workspace_id, #Singleton.getInstance().mongo_instance.get_current_workspace_name(),
'jobId': job_id,
'crawlProvider': broad_crawler_provider,
'crawlSources': broad_crawler_sources
}
logging.info(message)
Singleton.getInstance().broker_service.add_message_to_broadcrawler(
message, broad_crawler_provider)
def get_screenshot(crawl_type, id):
if crawl_type == "broadcrawl":
collection = Singleton.getInstance(
).mongo_instance.get_broad_crawler_collection()
elif crawl_type == "deepcrawl":
collection = Singleton.getInstance(
).mongo_instance.get_deep_crawler_collection()
elif crawl_type == "deepcrawl-domains":
collection = Singleton.getInstance(
).mongo_instance.get_deep_crawler_domains_collection()
elif crawl_type == "keywords":
collection = Singleton.getInstance(
).mongo_instance.get_seed_urls_collection()
else:
logging.info("invalid crawl type: " + crawl_type)
res = collection.find({"_id": ObjectId(id)})
docs = list(res)
screenshot = ""
if len(docs) > 0:
url = docs[0]["url"]
bytes = Singleton.getInstance().es_client.get_screenshoot(url)
if bytes:
screenshot = base64.b64decode(bytes)
return screenshot
def queue_deep_crawl_stop(workspace_id, job_id):
logging.info("preparing stop deep-crawler")
message = {
'id': job_id,
# 'workspace_id': workspace_id,
'stop': True
}
logging.info(message)
Singleton.getInstance().broker_service.add_message_to_deepcrawler(message)
def queue_login(workspace_id, job_id, credentials):
message = {
'workspace_id': workspace_id,
'job_id': job_id,
'id': credentials["_id"],
'domain': credentials["domain"],
'url': credentials["url"],
'key_values': credentials["keyValues"]
}
Singleton.getInstance().broker_service.add_message_to_login(message)
def queue_deep_crawl_start(workspace_id, job_id, num_to_fetch, urls,
login_credentials):
logging.info("preparing deep crawl message")
message = {
'id': job_id,
'workspace_id': workspace_id,
'page_limit': int(num_to_fetch),
'urls': urls,
'login_credentials': login_credentials
}
logging.info(message)
Singleton.getInstance().broker_service.add_message_to_deepcrawler(message)
def register_scraping_subscriber():
# Callback
def action1(args):
logging.info("read_topic_from_scraping run with: " + str(args))
# def save_urls(obj):
# url = obj['url']
# print("save_url with: " + url)
# print("save_url object with: " + str(obj))
# dao_update_url(url=url, obj=obj)
# Singleton.getInstance().broker_service.read_topic_from_broadcrawler(callback=save_urls)
Singleton.getInstance().broker_service.read_topic_from_scraping(callback=action1)
def get_screenshot(crawl_type, id):
if crawl_type == "broadcrawl":
collection = Singleton.getInstance(
).mongo_instance.get_broad_crawler_collection()
elif crawl_type == "keywords":
collection = Singleton.getInstance(
).mongo_instance.get_seed_urls_collection()
else:
logging.info("invalid crawl type: " + crawl_type)
res = collection.find({"_id": ObjectId(id)})
url = res[0]["url"]
base64 = Singleton.getInstance().es_client.get_screenshoot(url)
return base64
def get_deep_crawl_domains_by_domain_name(workspace_id, job_id, domain_name,
limit, last_id):
collection = Singleton.getInstance(
).mongo_instance.get_deep_crawler_collection()
and_source_conditions = []
workspace_search_object = {'workspaceId': workspace_id}
and_source_conditions.append(workspace_search_object)
job_search_object = {'jobId': job_id}
and_source_conditions.append(job_search_object)
domain_name_search_object = {'domain': domain_name}
and_source_conditions.append(domain_name_search_object)
page_search_object = {}
if last_id is not None:
page_search_object = {"_id": {"$gt": ObjectId(last_id)}}
and_source_conditions.append(page_search_object)
query = {'$and': and_source_conditions}
cursor = collection.find(query) \
.sort('_id', pymongo.ASCENDING) \
.limit(limit)
docs = list(cursor)
return docs
def get_logins(workspace_id, domains):
collection = Singleton.getInstance().mongo_instance.get_login_collection()
and_source_conditions = []
workspace_search_object = {'workspaceId': workspace_id}
and_source_conditions.append(workspace_search_object)
domains_search_object = {'domain': {'$in': domains}}
and_source_conditions.append(domains_search_object)
key_values_search_object = {'keyValues': {"$exists": True}}
and_source_conditions.append(key_values_search_object)
query = {'$and': and_source_conditions}
fields = {
'url': 1,
'domain': 1,
'keysOrder': 1,
'keyValues': 1,
'result': 1,
'_id': 1
}
cursor = collection.find(query, fields)
docs = list(cursor)
for doc in docs:
doc["_id"] = str(doc["_id"])
return docs
def save_login(credentials):
collection = Singleton.getInstance().mongo_instance.get_login_collection()
login_search_object = {'_id': ObjectId(credentials["_id"])}
operation = {'$set': {"keyValues": credentials["keyValues"]}}
collection.update(login_search_object, operation)
def get_max_id(workspace_id, job_id):
ws_object = {}
ws_object["workspaceId"] = workspace_id
search_object = {}
if job_id:
search_object = {"jobId": job_id}
# res = Singleton.getInstance().mongo_instance.get_broad_crawler_output_collection() \
# collection = Singleton.getInstance().mongo_instance.get_broad_crawler_output_collection_by_workspace_id(workspace_id)
collection = Singleton.getInstance(
).mongo_instance.get_broad_crawler_collection()
res = collection \
.find({'$and': [ws_object, search_object]}, ['_id']) \
.sort('_id', pymongo.DESCENDING) \
.limit(1)
res_list = list(res)
if len(res_list) > 0:
max_id = str(res_list[0]["_id"])
else:
max_id = None
return max_id
def create_account(username):
password = request.json['password']
encrypted_password = utils.encrypt_password(password)
try:
Singleton.getInstance().user_datastore.create_user(
email=username,
password=encrypted_password,
roles=[],
active=True,
login_count=0)
except NotUniqueError as ex:
raise InvalidUsage('An username with that email already exists',
status_code=409)
return Response("{}", mimetype="application/json")
def __init__(self):
self.counter = 0
self.sample_size = 50
def action1(args):
print("callback run with: " + str(args))
print("current counter:" + str(self.counter))
self.counter = self.counter + 1
kafka_host_port = "9092"
kafka_host_name = "localhost"
# topic_group = "test-group"
# topic = 'splash'
# topic_input = topic + '-input'
# topic_output = topic + '-input'#+ '-output'
app_instance = str(uuid.uuid1())
app_instance = 'app-instance' #str(uuid.uuid1())
instance = Singleton.getInstance()
instance.app_instance = app_instance
instance.mongo_instance = MongoInstance()
kafka_connector = KafkaConnector(kafka_host_name, kafka_host_port)
# kafka_connector.create_topic(topic_input)
broker_service = BrokerService(app_instance, kafka_host_name,
kafka_host_port)
#subscribe
# broker_service.read_from_queue(action1, topic_group, topic_output)
broker_service.read_topic_from_splash(action1)
time.sleep(1)
#produce
message = {}
i = 0
while i < self.sample_size:
message['index'] = i
message['text'] = 'test'
# message['date'] = strftime("%Y-%m-%d %H:%M:%S", gmtime())
message[
'splash_url_path'] = "/render.json?png=1&html=1&url=http://www.hyperiongray.com"
#"splash_url_path" : "/render.json?png=1&html=1&url=http://www.hyperiongray.com",
# broker_service.post_to_queue(message, topic_input, topic_output)
broker_service.add_message_to_splash(message)
print 'sending: ' + str(i)
i = i + 1
time.sleep(5)
print "Finish all"
print('Samples produced: ' + str(self.sample_size))
print('Samples consumed: ' + str(self.counter))
if self.sample_size == self.counter:
print 'Test passed'
else:
print 'test failed!!!'
time.sleep(1000000)
def get_metadata(self, workspace_id):
metadata = {}
metadata['workspace'] = workspace_id
metadata['source'] = Singleton.getInstance().app_instance
metadata['callbackQueue'] = "callback_queue_not_used"
metadata['timestamp'] = time.time()
metadata['strTimestamp'] = strftime("%Y-%m-%d %H:%M:%S", gmtime())
return metadata
def get_existing_categories_service(workspace_id):
collection = Singleton.getInstance(
).mongo_instance.get_broad_crawler_collection()
search_object = {}
search_object["workspaceId"] = workspace_id
categories = list(collection.find(search_object).distinct("categories"))
languages = list(collection.find(search_object).distinct("language"))
return categories, languages
def scraping_publication(url):
def register_scraping_subscriber():
logging.info('registering register_scraping_subscriber')
# Callback
def action1(args):
logging.info("action1 callback run with: " + str(args))
logging.info('publishing for scraping: ' + url)
message = {
'url': url,
'nResults': 2,
'workspace': Singleton.getInstance().mongo_instance.get_current_workspace_name()
}
Singleton.getInstance().broker_service.add_message_to_scraping(message)
return 282828
def post_to_queue(self, message, input_queue, callback_queue):
# add more headers to the message
message['source'] = Singleton.getInstance().app_instance#self.app_instance
message['callbackQueue'] = callback_queue
message['timestamp'] = time.time()
message['strTimestamp'] = strftime("%Y-%m-%d %H:%M:%S", gmtime())
json_message = json.dumps(message)
self.kafka_connector.send_message(input_queue, json_message)
def pin_service(workspace_id, id, is_pinned):
logging.info("PINNING: %s" % id + " as " + str(is_pinned))
collection = Singleton.getInstance(
).mongo_instance.get_broad_crawler_collection()
update_object = {"pinned": is_pinned}
collection.update({"_id": ObjectId(id)}, {'$set': update_object}, True)
publish_to_events_queue(workspace_id, "bookmark", "changed", {
"id": id,
"pinned": is_pinned
})
def get_job_by_id(job_id):
collection = Singleton.getInstance(
).mongo_instance.get_crawl_job_collection()
and_source_conditions = []
job_search_object = {'_id': ObjectId(job_id)}
and_source_conditions.append(job_search_object)
query = {'$and': and_source_conditions}
cursor = collection.find(query)
docs = list(cursor)
return docs[0]
def get_domains_by_job_id(workspace_id, job_id):
collection = Singleton.getInstance(
).mongo_instance.get_deep_crawler_domains_collection()
and_source_conditions = []
workspace_search_object = {'workspaceId': workspace_id}
and_source_conditions.append(workspace_search_object)
job_search_object = {'jobId': job_id}
and_source_conditions.append(job_search_object)
query = {'$and': and_source_conditions}
cursor = collection.find(query)
docs = list(cursor)
return docs
def get_relevant_or_neutral_seeds_urls_url(workspace_id):
# res = Singleton.getInstance().mongo_instance.get_broad_crawler_output_collection()\
# collection = Singleton.getInstance().mongo_instance.get_broad_crawler_output_collection_by_workspace_id(workspace_id)
collection = Singleton.getInstance(
).mongo_instance.get_seed_urls_collection()
res = collection.find(
{
'relevant': {
'$ne': False
},
"workspaceId": workspace_id
}, {'url': 1})
docs = list(res)
urls = []
for doc in docs:
# urls.append({"id": str(doc["_id"]), "url": doc["url"]})
urls.append(doc["url"])
return urls
def __get_urls(workspace_id):
collection = Singleton.getInstance(
).mongo_instance.get_seed_urls_collection()
relevant_urls_result = collection.find(
{
'workspaceId': workspace_id,
'relevant': True,
'deleted': {
'$exists': False
}
}, {
'_id': 0,
'url': 1
})
relevant_urls = []
for url_doc in relevant_urls_result:
if 'url' in url_doc:
relevant_urls.append(url_doc['url'])
return relevant_urls
def get_smart_crawler_results(workspace_id, page_size, input_search_query):
and_conditions = []
and_conditions.append({'workspaceId': workspace_id})
and_conditions.append({'deleted': {'$exists': False}})
and_conditions.append({'crawlEntityType': 'DD'})
# and_conditions.append({'crawlType': 'SMARTCRAWL'})
if 'job_id' in input_search_query and input_search_query[
'job_id'] is not None:
job_search_object = {'jobId': input_search_query["job_id"]}
and_conditions.append(job_search_object)
''' max_id restricts the results to the current set of returned results and not screw the pagination by score '''
if 'last_id' in input_search_query and input_search_query[
'last_id'] is not None:
last_id_search_object = {
"_id": {
"$gt": ObjectId(input_search_query['last_id'])
}
}
and_conditions.append(last_id_search_object)
if "search_text" in input_search_query:
search_text = input_search_query['search_text']
url_search_condition = {'url': {'$regex': search_text}}
host_search_condition = {'host': {'$regex': search_text}}
and_conditions.append(
{'$or': [url_search_condition, host_search_condition]})
# and_source_conditions = {'$and': and_conditions}
collection = Singleton.getInstance(
).mongo_instance.get_broad_crawler_collection()
query = {'$and': and_conditions}
cursor = collection.find(query) \
.sort('_id', pymongo.ASCENDING) \
.limit(page_size)
docs = list(cursor)
return docs
def dao_aggregate_broadcrawl_results(workspace_id):
source_search_conditions = []
workspace_search_object = {'workspaceId': workspace_id}
source_search_conditions.append(workspace_search_object)
delete_search_object = {'deleted': {'$exists': False}}
source_search_conditions.append(delete_search_object)
source_search_object = {'$and': source_search_conditions}
collection = Singleton.getInstance(
).mongo_instance.get_broad_crawler_collection()
try:
res = collection.aggregate([
# '$group': {'_id': '$crawlEntityType', "count": {"$sum": 1}}
{
'$match': source_search_object
},
{
'$group': {
'_id': {
'crawlEntityType': '$crawlEntityType'
},
"count": {
"$sum": 1
}
}
}
])
except Exception as e:
print e
return res["result"]
def __init__(self):
app_instance = str(uuid.uuid1())
app_instance = 'app-instance' #str(uuid.uuid1())
instance = Singleton.getInstance()
instance.app_instance = app_instance
instance.mongo_instance = MongoInstance()
search_query = {}
search_text = 'abellan'
print ''
print 'searching: ' + search_text
search_query['search_text'] = search_text
search_results = get_search_results(search_query)
print(search_results)
print 'searching complete for: ' + search_text
# in host
print ''
search_text = 'Guingueta'
print 'searching: ' + search_text
search_query['search_text'] = search_text
search_results = get_search_results(search_query)
print(search_results)
print 'searching complete for: ' + search_text
# in words
print ''
search_text = 'restaurantes'
print 'searching: ' + search_text
search_query['search_text'] = search_text
search_results = get_search_results(search_query)
print(search_results)
print 'searching complete for: ' + search_text
print 'done!'
def __get_page_model(workspace_id):
base64 = Singleton.getInstance().es_client.get_modeler_model(workspace_id)
return base64
def __queue_smart_crawler_stop(workspace_id, job_id):
message = {'id': job_id, 'stop': True}
logging.info(message)
Singleton.getInstance().broker_service.add_message_to_dd_crawler_input(
message)
def count_service(workspace_id):
collection = Singleton.getInstance(
).mongo_instance.get_broad_crawler_collection()
return collection.find({"workspaceId": workspace_id}).count()
def pin_service(workspace_id, id, is_pinned):
logging.info("PINNING: %s" % id + " as " + str(is_pinned))
collection = Singleton.getInstance(
).mongo_instance.get_broad_crawler_collection()
update_object = {"pinned": is_pinned}
collection.update({"_id": ObjectId(id)}, {'$set': update_object}, True)
