country":"CN","country_from_server":"CN
时间: 2024-06-04 12:05:13 浏览: 95
根据提供的引用,该字符串的格式为JSON格式,其中包含了`country`和`country_from_server`两个字段,它们的取值都是`CN`。JSON是一种轻量级的数据交换格式,常用于前后端数据交互。在Python中,我们可以使用`json`模块来解析和构建JSON数据。
以下是一个解析JSON数据并输出`country`和`country_from_server`的例子[^1]:
```python
import json
json_str = '{"country":"CN","country_from_server":"CN"}'
json_obj = json.loads(json_str)
print("country:", json_obj["country"]) # 输出:country: CN
print("country_from_server:", json_obj["country_from_server"]) # 输出:country_from_server: CN
```
相关问题
select left(trans_date,7) as [month], country, count([state]) as trans_count, count(case [state] when 'approved' then 1 else null) as approved_count, sum(amount) as trans_total_amount, sum(case [state] when 'approved' then amount else 0) as approved_total_amount from Transactions group by country,[month] 报[42000] [Microsoft][ODBC Driver 17 for SQL Server][SQL Server]Incorrect syntax near ')'. (102) (SQLExecDirectW) 请修正
请将查询语句中的方括号([])替换为双引号(""),并在group by子句中使用别名替代列名。修正后的查询语句如下:
```sql
SELECT LEFT(trans_date, 7) AS "month",
country,
COUNT([state]) AS trans_count,
COUNT(CASE [state] WHEN 'approved' THEN 1 ELSE NULL END) AS approved_count,
SUM(amount) AS trans_total_amount,
SUM(CASE [state] WHEN 'approved' THEN amount ELSE 0 END) AS approved_total_amount
FROM Transactions
GROUP BY country, "month";
```
sql server 增删改查
SQL Server 是一种关系型数据库管理系统(RDBMS),它支持多种操作,包括增删改查等。以下是 SQL Server 的增删改查语句示例:
增加数据:
INSERT INTO table_name (column1, column2, column3, ...)
VALUES (value1, value2, value3, ...);
例如:
INSERT INTO customers (customer_name, contact_name, city, country)
VALUES ('John Smith', 'Peter Lee', 'New York', 'USA');
删除数据:
DELETE FROM table_name WHERE condition;
例如:
DELETE FROM customers WHERE customer_id = 100;
更新数据:
UPDATE table_name SET column1 = value1, column2 = value2, ... WHERE condition;
例如:
UPDATE customers SET city = 'Los Angeles', country = 'USA' WHERE customer_id = 100;
查询数据:
SELECT column1, column2, ... FROM table_name WHERE condition;
例如:
SELECT customer_name, city FROM customers WHERE country = 'USA';