python之cur.fetchall与cur.fetchone提取数据并统计处理操作

{'ys4ng35toofdviy9ce0pn1uxw2x7trjb':'娱乐',
        'vekgqjtw3ax20udsniycjv1hdsa7t4oz':'经济',
        'vjzy0fobzgxkcnlbrsduhp47f8pxcoaj':'军事',
        'uamwbfqlxo7bu0warx6vkhefigkhtoz3':'政治',
        'lyr1hbrnmg9qzvwuzlk5fas7v628jiqx':'文化',
        }

import string
import random
def get_code():
    return ''.join(random.sample(string.ascii_letters + string.digits + string.punctuation, 32))
print(get_code())
 
def get_code1():
    return ''.join(random.sample(string.ascii_letters + string.digits, 32))
testresult= get_code1()
print(testresult.lower())
print(type(testresult))

)@+t37/b|UQ[K;!spj<(>%r9"PokwTe=
igwle98kgqtcprke7byvq12xnhucmz4v
<class 'str'>

import pymysql
import pandas as pd 
conn = pymysql.Connect(host="127.0.0.1",port=3306,user="root",password="123456",charset="utf8",db="sql_prac")
cur = conn.cursor()

print("连接成功")
sql = "SELECT type_code,count(1) as num FROM test GROUP BY type_code ORDER BY num desc"
cur.execute(sql)
res = cur.fetchall()
print(res)

(('ys4ng35toofdviy9ce0pn1uxw2x7trjb', 8), ('vekgqjtw3ax20udsniycjv1hdsa7t4oz', 5), ('vjzy0fobzgxkcnlbrsduhp47f8pxcoaj', 3), ('uamwbfqlxo7bu0warx6vkhefigkhtoz3', 3), ('娱乐', 2), ('lyr1hbrnmg9qzvwuzlk5fas7v628jiqx', 1), ('政治', 1), ('经济', 1), ('军事', 1), ('文化', 1))
res = pd.DataFrame(list(res), columns=['name','value'])
print(res)

dicts = {'ys4ng35toofdviy9ce0pn1uxw2x7trjb':'娱乐',
        'vekgqjtw3ax20udsniycjv1hdsa7t4oz':'经济',
        'vjzy0fobzgxkcnlbrsduhp47f8pxcoaj':'军事',
        'uamwbfqlxo7bu0warx6vkhefigkhtoz3':'政治',
        'lyr1hbrnmg9qzvwuzlk5fas7v628jiqx':'文化',
        }
res['name'] = res['name'].map(lambda x:dicts[x] if x in dicts else x)
print(res)

  name  value
0   娱乐      8
1   经济      5
2   军事      3
3   政治      3
4   娱乐      2
5   文化      1
6   政治      1
7   经济      1
8   军事      1
9   文化      1

#分组统计
result = res.groupby(['name']).sum().reset_index()
print(result)
 name  value
0   军事      4
1   娱乐     10
2   政治      4
3   文化      2
4   经济      6

#排序
result = result.sort_values(['value'], ascending=False)
 name  value
1   娱乐     10
4   经济      6
0   军事      4
2   政治      4
3   文化      2

#输出为list，前端需要的数据格式
data_dict = result.to_dict(orient='records')
print(data_dict)
[{'name': '娱乐', 'value': 10}, {'name': '经济', 'value': 6}, {'name': '军事', 'value': 4}, {'name': '政治', 'value': 4}, {'name': '文化', 'value': 2}]

import pymysql
import pandas as pd
conn = pymysql.Connect(host="127.0.0.1",port=3306,user="root",password="123456",charset="utf8",db="sql_prac")
cur = conn.cursor()
print("连接成功")
sql = "select count(case when type_code in ('ys4ng35toofdviy9ce0pn1uxw2x7trjb','娱乐') then 1 end) 娱乐," \
      "count(case when type_code in ('vekgqjtw3ax20udsniycjv1hdsa7t4oz','经济') then 1 end) 经济," \
      "count(case when type_code in ('vjzy0fobzgxkcnlbrsduhp47f8pxcoaj','军事') then 1 end) 军事," \
      "count(case when type_code in ('uamwbfqlxo7bu0warx6vkhefigkhtoz3' ,'政治') then 1 end) 政治," \
      "count(case when type_code in ('lyr1hbrnmg9qzvwuzlk5fas7v628jiqx','文化') then 1 end) 文化 from test"
cur.execute(sql)
res = cur.fetchone()
print(res)

(10, 6, 4, 4, 2)
data = [
                {"name": "娱乐", "value": res[0]},
                {"name": "经济", "value": res[1]},
                {"name": "军事", "value": res[2]},
                {"name": "政治", "value": res[3]},
                {"name": "文化", "value": res[4]}
]
result = sorted(data, key=lambda x: x['value'], reverse=True)
print(result)

[{'name': '娱乐', 'value': 10}, {'name': '经济', 'value': 6}, {'name': '军事', 'value': 4}, {'name': '政治', 'value': 4}, {'name': '文化', 'value': 2}]

sql_str = 'select col_1 from table_1 where criteria = 1'
cursor = connection.cursor()
cursor.execute(sql_str)
fetchall = cursor.fetchall()

(('101',), ('102',), ('103',),('104',))

cursor.execute(select username,password,nickname from user where id='%s'  %(input)

cursor.execute(select * from user)

((username1,password1,nickname1),(username2,password2,nickname2),(username3,password3,nickname))