Navidog

Python连接Hive，Mysql，Presto数据库，集成pandas。让数据分析更便捷，轻松。

连接数据源

• 连接mysql

---

from Navidog.api import *
mysql = Mysql(host='127.0.0.1', username='root', password='root', database='oozie')

• 连接hive

---

from Navidog.api import *
hive = Hive('127.0.0.1', database='all_users_db', port=10001, username='admin')

• 连接presto

---

from Navidog.api import *
prestos = Presto(host='127.0.0.1',
                 port=8081,
                 catalog='hive',
                 username='admin',
                 schema='table') 

增删改查

以mysql为例

• 增

---

from Navidog.api import *
mysql = Mysql(host='127.0.0.1', username='root', password='root', database='oozie')
items={'name': "dddd"}
lastid = mysql.insert('tables', items=items)
#lastid = mysql.insert('tables', name="dddd") #返回自增id

• 删

---

from Navidog.api import *
mysql = Mysql(host='127.0.0.1', username='root', password='root', database='oozie')
rows = mysql.delete("tables", where="id=1") #返回影响行数

• 改

---

from Navidog.api import *
mysql = Mysql(host='127.0.0.1', username='root', password='root', database='oozie')
rows = mysql.update('tables', where='id=2', name="sssss") #返回影响行数

• 查

---

from Navidog.api import *
mysql = Mysql(host='127.0.0.1', username='root', password='root', database='oozie')
data = mysql.select("tables", limit=10, use_pandas=1)

print(type(data))
<class 'pandas.core.frame.DataFrame'>

print(data)
   id   name
0   2  sssss
1   3   dddd
2   5   dddd
3   6   dddd
4   7   dddd