def get_company_overview():
company_df = query_from_db(
"""SELECT ent_text as company_name, cast(ADDTIME(news_published_date, '8:00:0') as DATE) as published_date, COUNT(*) as count
FROM news_db.news_kw_view
WHERE ent_text in (SELECT company_name FROM news_db.yahoo_stock_companies) and ent_type = 'ORG' and ADDTIME(news_published_date, '8:00:0') > '2021-01-19'
GROUP BY ent_text, cast(ADDTIME(news_published_date, '8:00:0') as DATE);""")
return company_df
def get_keywords_by_date():
kw_df = query_from_db(
"""SELECT ADDTIME(news_published_date, '8:00:0') published_date, news_keywords
FROM news_db.news_contents
WHERE news_keywords is not NULL and news_keywords != '' and ADDTIME(news_published_date, '8:00:0') > '2021-01-19';"""
)
kw_df['published_date'] = kw_df['published_date'].dt.date
return kw_df
def get_rss_data():
count_df = query_from_db("""
SELECT DATE(nrf.created_at) AS DATE, nc.category_name, COUNT(*) AS COUNT
FROM news_db.news_rss_feeds nrf
LEFT JOIN news_db.news_categories nc ON nc.rss_source = nrf.rss_source
GROUP BY DATE(nrf.created_at), nc.category_name ORDER BY DATE(nrf.created_at);"""
)
return count_df
def get_fail_parse_data():
fail_df = query_from_db("""
SELECT DATE(nrf.updated_at) AS DATE, nc.category_name, COUNT(*) AS COUNT
FROM news_db.news_rss_feeds nrf
LEFT JOIN news_db.news_categories nc ON nc.rss_source = nrf.rss_source
WHERE nrf.processed_status = 1 and nrf.processed_success = 0
GROUP BY DATE(nrf.updated_at), nc.category_name ORDER BY DATE(nrf.updated_at);"""
)
return fail_df
parent_dir = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
sys.path.append(parent_dir)
from db_func import query_from_db
start = time.time()
DIR_PATH = os.path.dirname(os.path.realpath(__file__))
FORMAT = '%(asctime)s %(levelname)s: %(message)s'
logging.basicConfig(level=logging.INFO,
filename=os.path.join(DIR_PATH, 'logs',
'sent_splitter.log'),
filemode='a',
format=FORMAT)
raw_df = query_from_db(
"SELECT news_id, news FROM news_contents WHERE processed_status = 0 LIMIT 300;"
)
with open(os.path.join(parent_dir, 'configs', 'server2server.config'),
'rb') as f:
configs = pickle.load(f)
author_header = r'^((（.+?）)|(\(.+?\))|(【.+?】)|(〔.+?〕)|(\[.+?\])|(［.+?］))\s*'
content_footer = r'^更多.*?報導：?$|^更多新聞推薦|^【更多新聞】|^延伸閱讀：|^【延伸閱讀】|^超人氣$|^看更多.*?文章|^更多匯流新聞網報導：|^原始連結|^更多\w+內容：|^《TVBS》提醒您：|^※|^（延伸閱讀：|^相關影音：|^責任編輯：|^☆|^更多\w+相關新聞|►'
mydb = mysql.connector.connect(host=configs['host'],
user=configs['user'],
passwd=configs['passwd'],
database=configs['database'])
spacy_start))
except Exception as e:
logging.error('NLP process Error: {}\n Content ID: {}'.format(
e, content_sent_id))
print('NLP process Error: {}\n Content ID: {}'.format(
e, content_sent_id))
print("Process record in {} seconds".format(time.time() -
process_start))
insert_start = time.time()
insert_sentlevel_info(word_sentence_list[0], pos_sentence_list[0],
content_sent_id, 'ckip-transformer')
insert_sentlevel_info(word_sent_list_spacy, word_pos_list_spacy,
content_sent_id, 'spacy-transformer',
word_dep_list_spacy)
insert_ner_info(entity_sentence_list[0], content_sent_id,
'ckip-transformer')
insert_ner_info(entity_sent_list_spacy, content_sent_id,
'spacy-transformer')
print("Insert record in {} seconds".format(time.time() - insert_start))
raw_df = query_from_db("SELECT * FROM news_db.financial_sent_view LIMIT 100;")
print("finish load the data in {} seconds".format(time.time() - start))
sent_level_analysis(raw_df)
mydb.close()
logging.error('Finish process {} examples in {} seconds'.format(
len(raw_df),
time.time() - start))
print('Finish process {} examples in {} seconds'.format(
len(raw_df),
time.time() - start))
DIR_PATH = dirname(abspath(__file__))
parent_dir = os.path.dirname(DIR_PATH)
sys.path.append(parent_dir)
FORMAT = '%(asctime)s %(levelname)s: %(message)s'
logging.basicConfig(level=logging.INFO,
filename=os.path.join(DIR_PATH, 'logs',
'yahoo_stock_companies.log'),
filemode='a',
format=FORMAT)
logger = logging.getLogger('yahoo_stock_logger')
from db_func import query_from_db, bulk_insert_to_db
start = time.time()
stock_df = query_from_db(
"""SELECT stock_category_id ,category_name, category_url FROM news_db.yahoo_stock_categories WHERE valid = 1"""
)
### Define the global header for requests
headers = {
'user-agent':
'Mozilla/5.0 (Macintosh Intel Mac OS X 10_13_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/66.0.3359.181 Safari/537.36',
'Connection': 'close'
}
res = []
for idx, (stock_category_id, _, category_url) in stock_df.iterrows():
# print(stock_category_id, category_url)
r = requests.get(category_url, headers=headers)
r.encoding = 'big5-hkscs'
web_content = r.text
def get_ner_by_date(selected_date):
ner_df = query_from_db(
"""SELECT CAST(nkv.news_published_date AS DATE) AS published_date, nkv.ent_text, nkv.ent_type
FROM news_db.news_kw_view nkv
WHERE CAST(nkv.news_published_date AS DATE) = '{}';""".format(selected_date))
return ner_df
else:
mydb.commit()
process_cursor.close()
def title_level_analysis(raw_df):
for index, (news_id, title) in raw_df.iterrows():
insert_process_flag(news_id, 'title-words')
process_start = time.time()
try:
word_title_list = ws_driver([title], use_delim=False)
entity_title_list = ner_driver([title], use_delim=False)
pos_title_list = pos_driver(word_title_list, use_delim=False)
print("Ckip process time {} seconds".format(time.time() - process_start))
except Exception as e:
logging.error('NLP process Error: {}\n News ID: {}'.format(e, news_id))
print('NLP process Error: {}\n News ID: {}'.format(e, news_id))
print("Process record in {} seconds".format(time.time() - process_start))
insert_start = time.time()
insert_title_level_info(word_title_list[0], pos_title_list[0], news_id, 'ckip-transformer')
insert_ner_info(entity_title_list[0], news_id, 'ckip-transformer')
print("Insert record in {} seconds".format(time.time() - insert_start))
raw_df = query_from_db("SELECT news_id, news_title FROM news_db.financial_title_view LIMIT 100;")
print("Finish load the data in {} seconds".format(time.time() - start))
title_level_analysis(raw_df)
mydb.close()
logging.error('Finish process {} examples in {} seconds'.format(len(raw_df), time.time() - start))
print('Finish process {} examples in {} seconds'.format(len(raw_df), time.time() - start))
DIR_PATH = dirname(abspath(__file__))
parent_dir = os.path.dirname(DIR_PATH)
sys.path.append(parent_dir)
FORMAT = '%(asctime)s %(levelname)s: %(message)s'
logging.basicConfig(level=logging.INFO,
filename=os.path.join(DIR_PATH, 'logs',
'stock_prices.log'),
filemode='a',
format=FORMAT)
logger = logging.getLogger('stock_price_logger')
from db_func import query_from_db, bulk_insert_to_db, insert_to_db
start = time.time()
ticker_df = query_from_db(
"SELECT stock_ticker FROM news_db.yahoo_stock_companies")
#ticker_df = ticker_df.iloc[ticker_df[ticker_df['stock_ticker'] == '2891B'].index.values[0]:]
def date_convertor(date_text):
temp_y, temp_m, temp_d = date_text.split('/')
temp_y = str(int(temp_y) + 1911)
temp = '/'.join([temp_y, temp_m, temp_d])
return datetime.strptime(temp, '%Y/%m/%d')
#日期', '成交股數', '成交金額', '開盤價', '最高價', '最低價', '收盤價', '漲跌價差', '成交筆數'
#'data': [['107/01/02', '13,698,944', '499,370,945', '36.45', '36.60', '36.05', '36.55', '+0.10', '3,932']
def format_convertor(stock_ticker, data):
cur_date, volumn, total_price, open_price, high_price, low_price, close_price, price_diff, transaction = data
transaction = int(transaction.replace(',', ''))
