import pandas as pd
from sqlalchemy import create_engine
import matplotlib.pyplot as plt
import re
import nltk
from rake_nltk import Rake
from rake_nltk import Metric
Mysql_arguments = {
'user': 'adv_yswg',
'password': 'HCL1zcUgQesaaXNLbL37O5KhpSAy0c',
'host': 'rm-wz9yg9bsb2zf01ea4yo.mysql.rds.aliyuncs.com',
'port': 3306,
'database': 'selection',
'charset': 'utf8mb4',
}
def get_country_engine(site_name="us"):
if site_name == 'us':
db_ = 'mysql+pymysql://{}:{}@{}:{}/{}?charset={}'.format(*Mysql_arguments.values())
else:
Mysql_arguments["database"] = f"selection_{site_name}"
db_ = 'mysql+pymysql://{}:{}@{}:{}/{}?charset={}'.format(*Mysql_arguments.values())
engine = create_engine(db_) # , pool_recycle=3600
return engine
engine = get_country_engine()
# sql = f"select asin, content, rating from us_asin_comment order by asin limit 10000;"
sql = f"select asin, content, rating from us_asin_comment where asin='B00B0RD2RA';"
df_asin_comment = pd.read_sql(sql, con=engine)
print(df_asin_comment.head())