Python 使用Boto3在RDS上与amazon Aurora交互

我已经使用AmazonAurora在AmazonRDS中建立了一个数据库，并希望使用Python与该数据库进行交互——显而易见的选择是使用Boto

但是，他们的文档很糟糕，没有涵盖我可以与数据库交互的方式，以便：

• 使用SQL语句运行查询
• 与数据库中的表交互
• 等

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是否有人有一些示例/教程的链接，或者知道如何执行这些任务？

当使用Amazon RDS产品（包括Aurora）时，您不会通过任何AWS API（包括Boto）连接到数据库。相反，您将使用所选数据库的本机客户端。对于Aurora，您可以使用MySQL命令行客户端进行连接。从那里，您可以像查询任何其他MySQL数据库一样查询它

“入门”文档中有一个简短的部分介绍了如何连接到Aurora数据库：

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这里有几个例子：

插入示例：

import boto3

sql = """
        INSERT INTO YOUR_TABLE_NAME_HERE
        (
            your_column_name_1
            ,your_column_name_2
            ,your_column_name_3)
        VALUES(
            :your_param_1_name
            ,:your_param_2_name)
            ,:your_param_3_name
        """

param1 = {'name':'your_param_1_name', 'value':{'longValue': 5}}
param2 = {'name':'your_param_2_name', 'value':{'longValue': 63}}
param3 = {'name':'your_param_3_name', 'value':{'stringValue': 'para bailar la bamba'}}

param_set = [param1, param2, param3]

db_clust_arn = 'your_db_cluster_arn_here'

db_secret_arn = 'your_db_secret_arn_here'

rds_data = boto3.client('rds-data')

response = rds_data.execute_statement(
    resourceArn = db_clust_arn, 
    secretArn = db_secret_arn, 
    database = 'your_database_name_here', 
    sql = sql,
    parameters = param_set)

print(str(response))

import boto3

rds_data = boto3.client('rds-data')

db_clust_arn = 'your_db_cluster_arn_here'

db_secret_arn = 'your_db_secret_arn_here'


employee_id = 35853

get_vacation_days_sql = f"""
    select vacation_days_remaining
    from employees_tbl
    where employee_id = {employee_id}    
        """


response1 = rds_data.execute_statement(
        resourceArn = db_clust_arn, 
        secretArn = db_secret_arn, 
        database = 'your_database_name_here', 
        sql = get_vacation_days_sql)

#recs is a list (of rows returned from Db)
recs = response1['records']

print(f"recs === {recs}")
#recs === [[{'longValue': 57}]]

#single_row is a list of dictionaries, where each dictionary represents a 
#column from that single row
for single_row in recs:
    print(f"single_row === {single_row}")
    #single_row === [{'longValue': 57}]
    
    #one_dict is a dictionary with one key value pair
    #where the key is the data type of the column and the 
    #value is the value of the column
    #each additional column is another dictionary
    for single_column_dict in single_row:
        print(f"one_dict === {single_column_dict}")
        # one_dict === {'longValue': 57}

        vacation_days_remaining = single_column_dict['longValue']
        
        print(f'vacation days remaining === {vacation_days_remaining}')

阅读示例：

import boto3

sql = """
        INSERT INTO YOUR_TABLE_NAME_HERE
        (
            your_column_name_1
            ,your_column_name_2
            ,your_column_name_3)
        VALUES(
            :your_param_1_name
            ,:your_param_2_name)
            ,:your_param_3_name
        """

param1 = {'name':'your_param_1_name', 'value':{'longValue': 5}}
param2 = {'name':'your_param_2_name', 'value':{'longValue': 63}}
param3 = {'name':'your_param_3_name', 'value':{'stringValue': 'para bailar la bamba'}}

param_set = [param1, param2, param3]

db_clust_arn = 'your_db_cluster_arn_here'

db_secret_arn = 'your_db_secret_arn_here'

rds_data = boto3.client('rds-data')

response = rds_data.execute_statement(
    resourceArn = db_clust_arn, 
    secretArn = db_secret_arn, 
    database = 'your_database_name_here', 
    sql = sql,
    parameters = param_set)

print(str(response))

import boto3

rds_data = boto3.client('rds-data')

db_clust_arn = 'your_db_cluster_arn_here'

db_secret_arn = 'your_db_secret_arn_here'


employee_id = 35853

get_vacation_days_sql = f"""
    select vacation_days_remaining
    from employees_tbl
    where employee_id = {employee_id}    
        """


response1 = rds_data.execute_statement(
        resourceArn = db_clust_arn, 
        secretArn = db_secret_arn, 
        database = 'your_database_name_here', 
        sql = get_vacation_days_sql)

#recs is a list (of rows returned from Db)
recs = response1['records']

print(f"recs === {recs}")
#recs === [[{'longValue': 57}]]

#single_row is a list of dictionaries, where each dictionary represents a 
#column from that single row
for single_row in recs:
    print(f"single_row === {single_row}")
    #single_row === [{'longValue': 57}]
    
    #one_dict is a dictionary with one key value pair
    #where the key is the data type of the column and the 
    #value is the value of the column
    #each additional column is another dictionary
    for single_column_dict in single_row:
        print(f"one_dict === {single_column_dict}")
        # one_dict === {'longValue': 57}

        vacation_days_remaining = single_column_dict['longValue']
        
        print(f'vacation days remaining === {vacation_days_remaining}')

源链接：

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谢谢。请原谅我的幼稚，但我该如何创建和使用API来通过查询获取数据，以便在web/移动应用程序中使用呢？例如，是否有一组服务或API？@user3024827-Nope。没有API。您只需像连接本地数据库一样连接到数据库。RDS只不过是一个托管数据库解决方案。那么这是否意味着它不能用作应用程序的数据库？再次道歉，如果这是一个愚蠢的问题，我是非常新的@user3024827-它绝对可以用作应用程序的数据库。我只是说，您对待它的方式与在本地运行数据库服务器的方式没有任何区别。我觉得这个答案可能会产生更多的歧义，并指导人们寻找使用Boto3连接到Aurora的方法。有一些API可以使用boto3连接到“rds数据”，然后运行查询。这在尝试使用secret manager而不是直接使用用户名密码进行连接时特别有用。在Glue上运行时，Boto3中没有rds数据客户端