Sono disponibili altri esempi per SDK AWS nel repository GitHub della documentazione degli esempi per SDK AWS
Esempi per Aurora con SDK per Python (Boto3)
Gli esempi di codice seguenti mostrano come eseguire operazioni e implementare scenari comuni utilizzando AWS SDK per Python (Boto3) con Aurora.
Nozioni di base: esempi di codice che mostrano come eseguire le operazioni essenziali all’interno di un servizio.
Le azioni sono estratti di codice da programmi più grandi e devono essere eseguite nel contesto. Sebbene le operazioni mostrino come richiamare le singole funzioni del servizio, è possibile visualizzarle contestualizzate negli scenari correlati.
Scenari: esempi di codice che mostrano come eseguire un’attività specifica chiamando più funzioni all’interno dello stesso servizio o combinate con altri Servizi AWS.
Ogni esempio include un link al codice sorgente completo, in cui vengono fornite le istruzioni su come configurare ed eseguire il codice nel contesto.
Nozioni di base
Gli esempi di codice seguenti mostrano come iniziare a utilizzare Aurora.
- SDK per Python (Boto3)
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Nota
Ulteriori informazioni su GitHub. Trova l’esempio completo e scopri di più sulla configurazione e l’esecuzione nel Repository di esempi di codice AWS
. import boto3 # Create an RDS client rds = boto3.client("rds") # Create a paginator for the describe_db_clusters operation paginator = rds.get_paginator("describe_db_clusters") # Use the paginator to get a list of DB clusters response_iterator = paginator.paginate( PaginationConfig={ "PageSize": 50, # Adjust PageSize as needed "StartingToken": None, } ) # Iterate through the pages of the response clusters_found = False for page in response_iterator: if "DBClusters" in page and page["DBClusters"]: clusters_found = True print("Here are your RDS Aurora clusters:") for cluster in page["DBClusters"]: print( f"Cluster ID: {cluster['DBClusterIdentifier']}, Engine: {cluster['Engine']}" ) if not clusters_found: print("No clusters found!")-
Per informazioni dettagliate sull’API, consulta DescribeDBClusters nella documentazione di riferimento dell’API AWS SDK per Python (Boto3).
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Argomenti
Nozioni di base
L’esempio di codice seguente mostra come:
Crea un gruppo di parametri del cluster di database Aurora personalizzati e imposta i relativi valori.
Crea un cluster di database che utilizza il gruppo di parametri.
Crea un’istanza database che contiene un database.
Acquisisci uno snapshot del cluster di database, quindi elimina le risorse.
- SDK per Python (Boto3)
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Nota
Ulteriori informazioni su GitHub. Trova l’esempio completo e scopri di più sulla configurazione e l’esecuzione nel Repository di esempi di codice AWS
. Esegui uno scenario interattivo al prompt dei comandi.
class AuroraClusterScenario: """Runs a scenario that shows how to get started using Aurora DB clusters.""" def __init__(self, aurora_wrapper): """ :param aurora_wrapper: An object that wraps Aurora DB cluster actions. """ self.aurora_wrapper = aurora_wrapper def create_parameter_group(self, db_engine, parameter_group_name): """ Shows how to get available engine versions for a specified database engine and create a DB cluster parameter group that is compatible with a selected engine family. :param db_engine: The database engine to use as a basis. :param parameter_group_name: The name given to the newly created parameter group. :return: The newly created parameter group. """ print( f"Checking for an existing DB cluster parameter group named {parameter_group_name}." ) parameter_group = self.aurora_wrapper.get_parameter_group(parameter_group_name) if parameter_group is None: print(f"Getting available database engine versions for {db_engine}.") engine_versions = self.aurora_wrapper.get_engine_versions(db_engine) families = list({ver["DBParameterGroupFamily"] for ver in engine_versions}) family_index = q.choose("Which family do you want to use? ", families) print(f"Creating a DB cluster parameter group.") self.aurora_wrapper.create_parameter_group( parameter_group_name, families[family_index], "Example parameter group." ) parameter_group = self.aurora_wrapper.get_parameter_group( parameter_group_name ) print(f"Parameter group {parameter_group['DBClusterParameterGroupName']}:") pp(parameter_group) print("-" * 88) return parameter_group def set_user_parameters(self, parameter_group_name): """ Shows how to get the parameters contained in a custom parameter group and update some of the parameter values in the group. :param parameter_group_name: The name of the parameter group to query and modify. """ print("Let's set some parameter values in your parameter group.") auto_inc_parameters = self.aurora_wrapper.get_parameters( parameter_group_name, name_prefix="auto_increment" ) update_params = [] for auto_inc in auto_inc_parameters: if auto_inc["IsModifiable"] and auto_inc["DataType"] == "integer": print(f"The {auto_inc['ParameterName']} parameter is described as:") print(f"\t{auto_inc['Description']}") param_range = auto_inc["AllowedValues"].split("-") auto_inc["ParameterValue"] = str( q.ask( f"Enter a value between {param_range[0]} and {param_range[1]}: ", q.is_int, q.in_range(int(param_range[0]), int(param_range[1])), ) ) update_params.append(auto_inc) self.aurora_wrapper.update_parameters(parameter_group_name, update_params) print( "You can get a list of parameters you've set by specifying a source of 'user'." ) user_parameters = self.aurora_wrapper.get_parameters( parameter_group_name, source="user" ) pp(user_parameters) print("-" * 88) def create_cluster(self, cluster_name, db_engine, db_name, parameter_group): """ Shows how to create an Aurora DB cluster that contains a database of a specified type. The database is also configured to use a custom DB cluster parameter group. :param cluster_name: The name given to the newly created DB cluster. :param db_engine: The engine of the created database. :param db_name: The name given to the created database. :param parameter_group: The parameter group that is associated with the DB cluster. :return: The newly created DB cluster. """ print("Checking for an existing DB cluster.") cluster = self.aurora_wrapper.get_db_cluster(cluster_name) if cluster is None: admin_username = q.ask( "Enter an administrator user name for the database: ", q.non_empty ) admin_password = q.ask( "Enter a password for the administrator (at least 8 characters): ", q.non_empty, ) engine_versions = self.aurora_wrapper.get_engine_versions( db_engine, parameter_group["DBParameterGroupFamily"] ) engine_choices = [ ver["EngineVersionDescription"] for ver in engine_versions ] print("The available engines for your parameter group are:") engine_index = q.choose("Which engine do you want to use? ", engine_choices) print( f"Creating DB cluster {cluster_name} and database {db_name}.\n" f"The DB cluster is configured to use\n" f"your custom parameter group {parameter_group['DBClusterParameterGroupName']}\n" f"and selected engine {engine_choices[engine_index]}.\n" f"This typically takes several minutes." ) cluster = self.aurora_wrapper.create_db_cluster( cluster_name, parameter_group["DBClusterParameterGroupName"], db_name, db_engine, engine_versions[engine_index]["EngineVersion"], admin_username, admin_password, ) while cluster.get("Status") != "available": wait(30) cluster = self.aurora_wrapper.get_db_cluster(cluster_name) print("Cluster created and available.\n") print("Cluster data:") pp(cluster) print("-" * 88) return cluster def create_instance(self, cluster): """ Shows how to create a DB instance in an existing Aurora DB cluster. A new DB cluster contains no DB instances, so you must add one. The first DB instance that is added to a DB cluster defaults to a read-write DB instance. :param cluster: The DB cluster where the DB instance is added. :return: The newly created DB instance. """ print("Checking for an existing database instance.") cluster_name = cluster["DBClusterIdentifier"] db_inst = self.aurora_wrapper.get_db_instance(cluster_name) if db_inst is None: print("Let's create a database instance in your DB cluster.") print("First, choose a DB instance type:") inst_opts = self.aurora_wrapper.get_orderable_instances( cluster["Engine"], cluster["EngineVersion"] ) inst_choices = list( { opt["DBInstanceClass"] + ", storage type: " + opt["StorageType"] for opt in inst_opts } ) inst_index = q.choose( "Which DB instance class do you want to use? ", inst_choices ) print( f"Creating a database instance. This typically takes several minutes." ) db_inst = self.aurora_wrapper.create_instance_in_cluster( cluster_name, cluster_name, cluster["Engine"], inst_opts[inst_index]["DBInstanceClass"], ) while db_inst.get("DBInstanceStatus") != "available": wait(30) db_inst = self.aurora_wrapper.get_db_instance(cluster_name) print("Instance data:") pp(db_inst) print("-" * 88) return db_inst @staticmethod def display_connection(cluster): """ Displays connection information about an Aurora DB cluster and tips on how to connect to it. :param cluster: The DB cluster to display. """ print( "You can now connect to your database using your favorite MySql client.\n" "One way to connect is by using the 'mysql' shell on an Amazon EC2 instance\n" "that is running in the same VPC as your database cluster. Pass the endpoint,\n" "port, and administrator user name to 'mysql' and enter your password\n" "when prompted:\n" ) print( f"\n\tmysql -h {cluster['Endpoint']} -P {cluster['Port']} -u {cluster['MasterUsername']} -p\n" ) print( "For more information, see the User Guide for Aurora:\n" "\thttp://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_GettingStartedAurora.CreatingConnecting.Aurora.html#CHAP_GettingStartedAurora.Aurora.Connect" ) print("-" * 88) def create_snapshot(self, cluster_name): """ Shows how to create a DB cluster snapshot and wait until it's available. :param cluster_name: The name of a DB cluster to snapshot. """ if q.ask( "Do you want to create a snapshot of your DB cluster (y/n)? ", q.is_yesno ): snapshot_id = f"{cluster_name}-{uuid.uuid4()}" print( f"Creating a snapshot named {snapshot_id}. This typically takes a few minutes." ) snapshot = self.aurora_wrapper.create_cluster_snapshot( snapshot_id, cluster_name ) while snapshot.get("Status") != "available": wait(30) snapshot = self.aurora_wrapper.get_cluster_snapshot(snapshot_id) pp(snapshot) print("-" * 88) def cleanup(self, db_inst, cluster, parameter_group): """ Shows how to clean up a DB instance, DB cluster, and DB cluster parameter group. Before the DB cluster parameter group can be deleted, all associated DB instances and DB clusters must first be deleted. :param db_inst: The DB instance to delete. :param cluster: The DB cluster to delete. :param parameter_group: The DB cluster parameter group to delete. """ cluster_name = cluster["DBClusterIdentifier"] parameter_group_name = parameter_group["DBClusterParameterGroupName"] if q.ask( "\nDo you want to delete the database instance, DB cluster, and parameter " "group (y/n)? ", q.is_yesno, ): print(f"Deleting database instance {db_inst['DBInstanceIdentifier']}.") self.aurora_wrapper.delete_db_instance(db_inst["DBInstanceIdentifier"]) print(f"Deleting database cluster {cluster_name}.") self.aurora_wrapper.delete_db_cluster(cluster_name) print( "Waiting for the DB instance and DB cluster to delete.\n" "This typically takes several minutes." ) while db_inst is not None or cluster is not None: wait(30) if db_inst is not None: db_inst = self.aurora_wrapper.get_db_instance( db_inst["DBInstanceIdentifier"] ) if cluster is not None: cluster = self.aurora_wrapper.get_db_cluster( cluster["DBClusterIdentifier"] ) print(f"Deleting parameter group {parameter_group_name}.") self.aurora_wrapper.delete_parameter_group(parameter_group_name) def run_scenario(self, db_engine, parameter_group_name, cluster_name, db_name): print("-" * 88) print( "Welcome to the Amazon Relational Database Service (Amazon RDS) get started\n" "with Aurora DB clusters demo." ) print("-" * 88) parameter_group = self.create_parameter_group(db_engine, parameter_group_name) self.set_user_parameters(parameter_group_name) cluster = self.create_cluster(cluster_name, db_engine, db_name, parameter_group) wait(5) db_inst = self.create_instance(cluster) self.display_connection(cluster) self.create_snapshot(cluster_name) self.cleanup(db_inst, cluster, parameter_group) print("\nThanks for watching!") print("-" * 88) if __name__ == "__main__": logging.basicConfig(level=logging.INFO, format="%(levelname)s: %(message)s") try: scenario = AuroraClusterScenario(AuroraWrapper.from_client()) scenario.run_scenario( "aurora-mysql", "doc-example-cluster-parameter-group", "doc-example-aurora", "docexampledb", ) except Exception: logging.exception("Something went wrong with the demo.")Definisci le funzioni richiamate dallo scenario per gestire le operazioni Aurora.
class AuroraWrapper: """Encapsulates Aurora DB cluster actions.""" def __init__(self, rds_client): """ :param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client. """ self.rds_client = rds_client @classmethod def from_client(cls): """ Instantiates this class from a Boto3 client. """ rds_client = boto3.client("rds") return cls(rds_client) def get_parameter_group(self, parameter_group_name): """ Gets a DB cluster parameter group. :param parameter_group_name: The name of the parameter group to retrieve. :return: The requested parameter group. """ try: response = self.rds_client.describe_db_cluster_parameter_groups( DBClusterParameterGroupName=parameter_group_name ) parameter_group = response["DBClusterParameterGroups"][0] except ClientError as err: if err.response["Error"]["Code"] == "DBParameterGroupNotFound": logger.info("Parameter group %s does not exist.", parameter_group_name) else: logger.error( "Couldn't get parameter group %s. Here's why: %s: %s", parameter_group_name, err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return parameter_group def create_parameter_group( self, parameter_group_name, parameter_group_family, description ): """ Creates a DB cluster parameter group that is based on the specified parameter group family. :param parameter_group_name: The name of the newly created parameter group. :param parameter_group_family: The family that is used as the basis of the new parameter group. :param description: A description given to the parameter group. :return: Data about the newly created parameter group. """ try: response = self.rds_client.create_db_cluster_parameter_group( DBClusterParameterGroupName=parameter_group_name, DBParameterGroupFamily=parameter_group_family, Description=description, ) except ClientError as err: logger.error( "Couldn't create parameter group %s. Here's why: %s: %s", parameter_group_name, err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return response def delete_parameter_group(self, parameter_group_name): """ Deletes a DB cluster parameter group. :param parameter_group_name: The name of the parameter group to delete. :return: Data about the parameter group. """ try: response = self.rds_client.delete_db_cluster_parameter_group( DBClusterParameterGroupName=parameter_group_name ) except ClientError as err: logger.error( "Couldn't delete parameter group %s. Here's why: %s: %s", parameter_group_name, err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return response def get_parameters(self, parameter_group_name, name_prefix="", source=None): """ Gets the parameters that are contained in a DB cluster parameter group. :param parameter_group_name: The name of the parameter group to query. :param name_prefix: When specified, the retrieved list of parameters is filtered to contain only parameters that start with this prefix. :param source: When specified, only parameters from this source are retrieved. For example, a source of 'user' retrieves only parameters that were set by a user. :return: The list of requested parameters. """ try: kwargs = {"DBClusterParameterGroupName": parameter_group_name} if source is not None: kwargs["Source"] = source parameters = [] paginator = self.rds_client.get_paginator("describe_db_cluster_parameters") for page in paginator.paginate(**kwargs): parameters += [ p for p in page["Parameters"] if p["ParameterName"].startswith(name_prefix) ] except ClientError as err: logger.error( "Couldn't get parameters for %s. Here's why: %s: %s", parameter_group_name, err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return parameters def update_parameters(self, parameter_group_name, update_parameters): """ Updates parameters in a custom DB cluster parameter group. :param parameter_group_name: The name of the parameter group to update. :param update_parameters: The parameters to update in the group. :return: Data about the modified parameter group. """ try: response = self.rds_client.modify_db_cluster_parameter_group( DBClusterParameterGroupName=parameter_group_name, Parameters=update_parameters, ) except ClientError as err: logger.error( "Couldn't update parameters in %s. Here's why: %s: %s", parameter_group_name, err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return response def get_db_cluster(self, cluster_name): """ Gets data about an Aurora DB cluster. :param cluster_name: The name of the DB cluster to retrieve. :return: The retrieved DB cluster. """ try: response = self.rds_client.describe_db_clusters( DBClusterIdentifier=cluster_name ) cluster = response["DBClusters"][0] except ClientError as err: if err.response["Error"]["Code"] == "DBClusterNotFoundFault": logger.info("Cluster %s does not exist.", cluster_name) else: logger.error( "Couldn't verify the existence of DB cluster %s. Here's why: %s: %s", cluster_name, err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return cluster def create_db_cluster( self, cluster_name, parameter_group_name, db_name, db_engine, db_engine_version, admin_name, admin_password, ): """ Creates a DB cluster that is configured to use the specified parameter group. The newly created DB cluster contains a database that uses the specified engine and engine version. :param cluster_name: The name of the DB cluster to create. :param parameter_group_name: The name of the parameter group to associate with the DB cluster. :param db_name: The name of the database to create. :param db_engine: The database engine of the database that is created, such as MySql. :param db_engine_version: The version of the database engine. :param admin_name: The user name of the database administrator. :param admin_password: The password of the database administrator. :return: The newly created DB cluster. """ try: response = self.rds_client.create_db_cluster( DatabaseName=db_name, DBClusterIdentifier=cluster_name, DBClusterParameterGroupName=parameter_group_name, Engine=db_engine, EngineVersion=db_engine_version, MasterUsername=admin_name, MasterUserPassword=admin_password, ) cluster = response["DBCluster"] except ClientError as err: logger.error( "Couldn't create database %s. Here's why: %s: %s", db_name, err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return cluster def delete_db_cluster(self, cluster_name): """ Deletes a DB cluster. :param cluster_name: The name of the DB cluster to delete. """ try: self.rds_client.delete_db_cluster( DBClusterIdentifier=cluster_name, SkipFinalSnapshot=True ) logger.info("Deleted DB cluster %s.", cluster_name) except ClientError: logger.exception("Couldn't delete DB cluster %s.", cluster_name) raise def create_cluster_snapshot(self, snapshot_id, cluster_id): """ Creates a snapshot of a DB cluster. :param snapshot_id: The ID to give the created snapshot. :param cluster_id: The DB cluster to snapshot. :return: Data about the newly created snapshot. """ try: response = self.rds_client.create_db_cluster_snapshot( DBClusterSnapshotIdentifier=snapshot_id, DBClusterIdentifier=cluster_id ) snapshot = response["DBClusterSnapshot"] except ClientError as err: logger.error( "Couldn't create snapshot of %s. Here's why: %s: %s", cluster_id, err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return snapshot def get_cluster_snapshot(self, snapshot_id): """ Gets a DB cluster snapshot. :param snapshot_id: The ID of the snapshot to retrieve. :return: The retrieved snapshot. """ try: response = self.rds_client.describe_db_cluster_snapshots( DBClusterSnapshotIdentifier=snapshot_id ) snapshot = response["DBClusterSnapshots"][0] except ClientError as err: logger.error( "Couldn't get DB cluster snapshot %s. Here's why: %s: %s", snapshot_id, err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return snapshot def create_instance_in_cluster( self, instance_id, cluster_id, db_engine, instance_class ): """ Creates a database instance in an existing DB cluster. The first database that is created defaults to a read-write DB instance. :param instance_id: The ID to give the newly created DB instance. :param cluster_id: The ID of the DB cluster where the DB instance is created. :param db_engine: The database engine of a database to create in the DB instance. This must be compatible with the configured parameter group of the DB cluster. :param instance_class: The DB instance class for the newly created DB instance. :return: Data about the newly created DB instance. """ try: response = self.rds_client.create_db_instance( DBInstanceIdentifier=instance_id, DBClusterIdentifier=cluster_id, Engine=db_engine, DBInstanceClass=instance_class, ) db_inst = response["DBInstance"] except ClientError as err: logger.error( "Couldn't create DB instance %s. Here's why: %s: %s", instance_id, err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return db_inst def get_engine_versions(self, engine, parameter_group_family=None): """ Gets database engine versions that are available for the specified engine and parameter group family. :param engine: The database engine to look up. :param parameter_group_family: When specified, restricts the returned list of engine versions to those that are compatible with this parameter group family. :return: The list of database engine versions. """ try: kwargs = {"Engine": engine} if parameter_group_family is not None: kwargs["DBParameterGroupFamily"] = parameter_group_family response = self.rds_client.describe_db_engine_versions(**kwargs) versions = response["DBEngineVersions"] except ClientError as err: logger.error( "Couldn't get engine versions for %s. Here's why: %s: %s", engine, err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return versions def get_orderable_instances(self, db_engine, db_engine_version): """ Gets DB instance options that can be used to create DB instances that are compatible with a set of specifications. :param db_engine: The database engine that must be supported by the DB instance. :param db_engine_version: The engine version that must be supported by the DB instance. :return: The list of DB instance options that can be used to create a compatible DB instance. """ try: inst_opts = [] paginator = self.rds_client.get_paginator( "describe_orderable_db_instance_options" ) for page in paginator.paginate( Engine=db_engine, EngineVersion=db_engine_version ): inst_opts += page["OrderableDBInstanceOptions"] except ClientError as err: logger.error( "Couldn't get orderable DB instances. Here's why: %s: %s", err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return inst_opts def get_db_instance(self, instance_id): """ Gets data about a DB instance. :param instance_id: The ID of the DB instance to retrieve. :return: The retrieved DB instance. """ try: response = self.rds_client.describe_db_instances( DBInstanceIdentifier=instance_id ) db_inst = response["DBInstances"][0] except ClientError as err: if err.response["Error"]["Code"] == "DBInstanceNotFound": logger.info("Instance %s does not exist.", instance_id) else: logger.error( "Couldn't get DB instance %s. Here's why: %s: %s", instance_id, err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return db_inst def delete_db_instance(self, instance_id): """ Deletes a DB instance. :param instance_id: The ID of the DB instance to delete. :return: Data about the deleted DB instance. """ try: response = self.rds_client.delete_db_instance( DBInstanceIdentifier=instance_id, SkipFinalSnapshot=True, DeleteAutomatedBackups=True, ) db_inst = response["DBInstance"] except ClientError as err: logger.error( "Couldn't delete DB instance %s. Here's why: %s: %s", instance_id, err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return db_inst-
Per informazioni dettagliate sull’API, consulta i seguenti argomenti nella documentazione di riferimento dell’API AWS SDK per Python (Boto3).
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Azioni
L’esempio di codice seguente mostra come utilizzare CreateDBCluster.
- SDK per Python (Boto3)
-
Nota
Ulteriori informazioni su GitHub. Trova l’esempio completo e scopri di più sulla configurazione e l’esecuzione nel Repository di esempi di codice AWS
. class AuroraWrapper: """Encapsulates Aurora DB cluster actions.""" def __init__(self, rds_client): """ :param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client. """ self.rds_client = rds_client @classmethod def from_client(cls): """ Instantiates this class from a Boto3 client. """ rds_client = boto3.client("rds") return cls(rds_client) def create_db_cluster( self, cluster_name, parameter_group_name, db_name, db_engine, db_engine_version, admin_name, admin_password, ): """ Creates a DB cluster that is configured to use the specified parameter group. The newly created DB cluster contains a database that uses the specified engine and engine version. :param cluster_name: The name of the DB cluster to create. :param parameter_group_name: The name of the parameter group to associate with the DB cluster. :param db_name: The name of the database to create. :param db_engine: The database engine of the database that is created, such as MySql. :param db_engine_version: The version of the database engine. :param admin_name: The user name of the database administrator. :param admin_password: The password of the database administrator. :return: The newly created DB cluster. """ try: response = self.rds_client.create_db_cluster( DatabaseName=db_name, DBClusterIdentifier=cluster_name, DBClusterParameterGroupName=parameter_group_name, Engine=db_engine, EngineVersion=db_engine_version, MasterUsername=admin_name, MasterUserPassword=admin_password, ) cluster = response["DBCluster"] except ClientError as err: logger.error( "Couldn't create database %s. Here's why: %s: %s", db_name, err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return cluster-
Per informazioni dettagliate sull’API, consulta CreateDBCluster nella documentazione di riferimento dell’API AWS SDK per Python (Boto3).
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L’esempio di codice seguente mostra come utilizzare CreateDBClusterParameterGroup.
- SDK per Python (Boto3)
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Nota
Ulteriori informazioni su GitHub. Trova l’esempio completo e scopri di più sulla configurazione e l’esecuzione nel Repository di esempi di codice AWS
. class AuroraWrapper: """Encapsulates Aurora DB cluster actions.""" def __init__(self, rds_client): """ :param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client. """ self.rds_client = rds_client @classmethod def from_client(cls): """ Instantiates this class from a Boto3 client. """ rds_client = boto3.client("rds") return cls(rds_client) def create_parameter_group( self, parameter_group_name, parameter_group_family, description ): """ Creates a DB cluster parameter group that is based on the specified parameter group family. :param parameter_group_name: The name of the newly created parameter group. :param parameter_group_family: The family that is used as the basis of the new parameter group. :param description: A description given to the parameter group. :return: Data about the newly created parameter group. """ try: response = self.rds_client.create_db_cluster_parameter_group( DBClusterParameterGroupName=parameter_group_name, DBParameterGroupFamily=parameter_group_family, Description=description, ) except ClientError as err: logger.error( "Couldn't create parameter group %s. Here's why: %s: %s", parameter_group_name, err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return response-
Per informazioni dettagliate sull’API, consulta CreateDBClusterParameterGroup nella documentazione di riferimento dell’API AWS SDK per Python (Boto3).
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L’esempio di codice seguente mostra come utilizzare CreateDBClusterSnapshot.
- SDK per Python (Boto3)
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Nota
Ulteriori informazioni su GitHub. Trova l’esempio completo e scopri di più sulla configurazione e l’esecuzione nel Repository di esempi di codice AWS
. class AuroraWrapper: """Encapsulates Aurora DB cluster actions.""" def __init__(self, rds_client): """ :param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client. """ self.rds_client = rds_client @classmethod def from_client(cls): """ Instantiates this class from a Boto3 client. """ rds_client = boto3.client("rds") return cls(rds_client) def create_cluster_snapshot(self, snapshot_id, cluster_id): """ Creates a snapshot of a DB cluster. :param snapshot_id: The ID to give the created snapshot. :param cluster_id: The DB cluster to snapshot. :return: Data about the newly created snapshot. """ try: response = self.rds_client.create_db_cluster_snapshot( DBClusterSnapshotIdentifier=snapshot_id, DBClusterIdentifier=cluster_id ) snapshot = response["DBClusterSnapshot"] except ClientError as err: logger.error( "Couldn't create snapshot of %s. Here's why: %s: %s", cluster_id, err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return snapshot-
Per informazioni dettagliate sull’API, consulta CreateDBClusterSnapshot nella documentazione di riferimento dell’API AWS SDK per Python (Boto3).
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L’esempio di codice seguente mostra come utilizzare CreateDBInstance.
- SDK per Python (Boto3)
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Nota
Ulteriori informazioni su GitHub. Trova l’esempio completo e scopri di più sulla configurazione e l’esecuzione nel Repository di esempi di codice AWS
. class AuroraWrapper: """Encapsulates Aurora DB cluster actions.""" def __init__(self, rds_client): """ :param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client. """ self.rds_client = rds_client @classmethod def from_client(cls): """ Instantiates this class from a Boto3 client. """ rds_client = boto3.client("rds") return cls(rds_client) def create_instance_in_cluster( self, instance_id, cluster_id, db_engine, instance_class ): """ Creates a database instance in an existing DB cluster. The first database that is created defaults to a read-write DB instance. :param instance_id: The ID to give the newly created DB instance. :param cluster_id: The ID of the DB cluster where the DB instance is created. :param db_engine: The database engine of a database to create in the DB instance. This must be compatible with the configured parameter group of the DB cluster. :param instance_class: The DB instance class for the newly created DB instance. :return: Data about the newly created DB instance. """ try: response = self.rds_client.create_db_instance( DBInstanceIdentifier=instance_id, DBClusterIdentifier=cluster_id, Engine=db_engine, DBInstanceClass=instance_class, ) db_inst = response["DBInstance"] except ClientError as err: logger.error( "Couldn't create DB instance %s. Here's why: %s: %s", instance_id, err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return db_inst-
Per informazioni dettagliate sull’API, consulta CreateDBInstance nella documentazione di riferimento dell’API AWS SDK per Python (Boto3).
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L’esempio di codice seguente mostra come utilizzare DeleteDBCluster.
- SDK per Python (Boto3)
-
Nota
Ulteriori informazioni su GitHub. Trova l’esempio completo e scopri di più sulla configurazione e l’esecuzione nel Repository di esempi di codice AWS
. class AuroraWrapper: """Encapsulates Aurora DB cluster actions.""" def __init__(self, rds_client): """ :param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client. """ self.rds_client = rds_client @classmethod def from_client(cls): """ Instantiates this class from a Boto3 client. """ rds_client = boto3.client("rds") return cls(rds_client) def delete_db_cluster(self, cluster_name): """ Deletes a DB cluster. :param cluster_name: The name of the DB cluster to delete. """ try: self.rds_client.delete_db_cluster( DBClusterIdentifier=cluster_name, SkipFinalSnapshot=True ) logger.info("Deleted DB cluster %s.", cluster_name) except ClientError: logger.exception("Couldn't delete DB cluster %s.", cluster_name) raise-
Per informazioni dettagliate sull’API, consulta DeleteDBCluster nella documentazione di riferimento dell’API AWS SDK per Python (Boto3).
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L’esempio di codice seguente mostra come utilizzare DeleteDBClusterParameterGroup.
- SDK per Python (Boto3)
-
Nota
Ulteriori informazioni su GitHub. Trova l’esempio completo e scopri di più sulla configurazione e l’esecuzione nel Repository di esempi di codice AWS
. class AuroraWrapper: """Encapsulates Aurora DB cluster actions.""" def __init__(self, rds_client): """ :param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client. """ self.rds_client = rds_client @classmethod def from_client(cls): """ Instantiates this class from a Boto3 client. """ rds_client = boto3.client("rds") return cls(rds_client) def delete_parameter_group(self, parameter_group_name): """ Deletes a DB cluster parameter group. :param parameter_group_name: The name of the parameter group to delete. :return: Data about the parameter group. """ try: response = self.rds_client.delete_db_cluster_parameter_group( DBClusterParameterGroupName=parameter_group_name ) except ClientError as err: logger.error( "Couldn't delete parameter group %s. Here's why: %s: %s", parameter_group_name, err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return response-
Per informazioni dettagliate sull’API, consulta DeleteDBClusterParameterGroup nella documentazione di riferimento dell’API AWS SDK per Python (Boto3).
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L’esempio di codice seguente mostra come utilizzare DeleteDBInstance.
- SDK per Python (Boto3)
-
Nota
Ulteriori informazioni su GitHub. Trova l’esempio completo e scopri di più sulla configurazione e l’esecuzione nel Repository di esempi di codice AWS
. class AuroraWrapper: """Encapsulates Aurora DB cluster actions.""" def __init__(self, rds_client): """ :param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client. """ self.rds_client = rds_client @classmethod def from_client(cls): """ Instantiates this class from a Boto3 client. """ rds_client = boto3.client("rds") return cls(rds_client) def delete_db_instance(self, instance_id): """ Deletes a DB instance. :param instance_id: The ID of the DB instance to delete. :return: Data about the deleted DB instance. """ try: response = self.rds_client.delete_db_instance( DBInstanceIdentifier=instance_id, SkipFinalSnapshot=True, DeleteAutomatedBackups=True, ) db_inst = response["DBInstance"] except ClientError as err: logger.error( "Couldn't delete DB instance %s. Here's why: %s: %s", instance_id, err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return db_inst-
Per informazioni dettagliate sull’API, consulta DeleteDBInstance nella documentazione di riferimento dell’API AWS SDK per Python (Boto3).
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L’esempio di codice seguente mostra come utilizzare DescribeDBClusterParameterGroups.
- SDK per Python (Boto3)
-
Nota
Ulteriori informazioni su GitHub. Trova l’esempio completo e scopri di più sulla configurazione e l’esecuzione nel Repository di esempi di codice AWS
. class AuroraWrapper: """Encapsulates Aurora DB cluster actions.""" def __init__(self, rds_client): """ :param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client. """ self.rds_client = rds_client @classmethod def from_client(cls): """ Instantiates this class from a Boto3 client. """ rds_client = boto3.client("rds") return cls(rds_client) def get_parameter_group(self, parameter_group_name): """ Gets a DB cluster parameter group. :param parameter_group_name: The name of the parameter group to retrieve. :return: The requested parameter group. """ try: response = self.rds_client.describe_db_cluster_parameter_groups( DBClusterParameterGroupName=parameter_group_name ) parameter_group = response["DBClusterParameterGroups"][0] except ClientError as err: if err.response["Error"]["Code"] == "DBParameterGroupNotFound": logger.info("Parameter group %s does not exist.", parameter_group_name) else: logger.error( "Couldn't get parameter group %s. Here's why: %s: %s", parameter_group_name, err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return parameter_group-
Per informazioni dettagliate sull’API, consulta DescribeDBClusterParameterGroups nella documentazione di riferimento dell’API AWS SDK per Python (Boto3).
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L’esempio di codice seguente mostra come utilizzare DescribeDBClusterParameters.
- SDK per Python (Boto3)
-
Nota
Ulteriori informazioni su GitHub. Trova l’esempio completo e scopri di più sulla configurazione e l’esecuzione nel Repository di esempi di codice AWS
. class AuroraWrapper: """Encapsulates Aurora DB cluster actions.""" def __init__(self, rds_client): """ :param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client. """ self.rds_client = rds_client @classmethod def from_client(cls): """ Instantiates this class from a Boto3 client. """ rds_client = boto3.client("rds") return cls(rds_client) def get_parameters(self, parameter_group_name, name_prefix="", source=None): """ Gets the parameters that are contained in a DB cluster parameter group. :param parameter_group_name: The name of the parameter group to query. :param name_prefix: When specified, the retrieved list of parameters is filtered to contain only parameters that start with this prefix. :param source: When specified, only parameters from this source are retrieved. For example, a source of 'user' retrieves only parameters that were set by a user. :return: The list of requested parameters. """ try: kwargs = {"DBClusterParameterGroupName": parameter_group_name} if source is not None: kwargs["Source"] = source parameters = [] paginator = self.rds_client.get_paginator("describe_db_cluster_parameters") for page in paginator.paginate(**kwargs): parameters += [ p for p in page["Parameters"] if p["ParameterName"].startswith(name_prefix) ] except ClientError as err: logger.error( "Couldn't get parameters for %s. Here's why: %s: %s", parameter_group_name, err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return parameters-
Per informazioni dettagliate sull’API, consulta DescribeDBClusterParameters nella documentazione di riferimento dell’API AWS SDK per Python (Boto3).
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L’esempio di codice seguente mostra come utilizzare DescribeDBClusterSnapshots.
- SDK per Python (Boto3)
-
Nota
Ulteriori informazioni su GitHub. Trova l’esempio completo e scopri di più sulla configurazione e l’esecuzione nel Repository di esempi di codice AWS
. class AuroraWrapper: """Encapsulates Aurora DB cluster actions.""" def __init__(self, rds_client): """ :param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client. """ self.rds_client = rds_client @classmethod def from_client(cls): """ Instantiates this class from a Boto3 client. """ rds_client = boto3.client("rds") return cls(rds_client) def get_cluster_snapshot(self, snapshot_id): """ Gets a DB cluster snapshot. :param snapshot_id: The ID of the snapshot to retrieve. :return: The retrieved snapshot. """ try: response = self.rds_client.describe_db_cluster_snapshots( DBClusterSnapshotIdentifier=snapshot_id ) snapshot = response["DBClusterSnapshots"][0] except ClientError as err: logger.error( "Couldn't get DB cluster snapshot %s. Here's why: %s: %s", snapshot_id, err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return snapshot-
Per informazioni dettagliate sull’API, consulta DescribeDBClusterSnapshots nella documentazione di riferimento dell’API AWS SDK per Python (Boto3).
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L’esempio di codice seguente mostra come utilizzare DescribeDBClusters.
- SDK per Python (Boto3)
-
Nota
Ulteriori informazioni su GitHub. Trova l’esempio completo e scopri di più sulla configurazione e l’esecuzione nel Repository di esempi di codice AWS
. class AuroraWrapper: """Encapsulates Aurora DB cluster actions.""" def __init__(self, rds_client): """ :param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client. """ self.rds_client = rds_client @classmethod def from_client(cls): """ Instantiates this class from a Boto3 client. """ rds_client = boto3.client("rds") return cls(rds_client) def get_db_cluster(self, cluster_name): """ Gets data about an Aurora DB cluster. :param cluster_name: The name of the DB cluster to retrieve. :return: The retrieved DB cluster. """ try: response = self.rds_client.describe_db_clusters( DBClusterIdentifier=cluster_name ) cluster = response["DBClusters"][0] except ClientError as err: if err.response["Error"]["Code"] == "DBClusterNotFoundFault": logger.info("Cluster %s does not exist.", cluster_name) else: logger.error( "Couldn't verify the existence of DB cluster %s. Here's why: %s: %s", cluster_name, err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return cluster-
Per informazioni dettagliate sull’API, consulta DescribeDBClusters nella documentazione di riferimento dell’API AWS SDK per Python (Boto3).
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L’esempio di codice seguente mostra come utilizzare DescribeDBEngineVersions.
- SDK per Python (Boto3)
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Nota
Ulteriori informazioni su GitHub. Trova l’esempio completo e scopri di più sulla configurazione e l’esecuzione nel Repository di esempi di codice AWS
. class AuroraWrapper: """Encapsulates Aurora DB cluster actions.""" def __init__(self, rds_client): """ :param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client. """ self.rds_client = rds_client @classmethod def from_client(cls): """ Instantiates this class from a Boto3 client. """ rds_client = boto3.client("rds") return cls(rds_client) def get_engine_versions(self, engine, parameter_group_family=None): """ Gets database engine versions that are available for the specified engine and parameter group family. :param engine: The database engine to look up. :param parameter_group_family: When specified, restricts the returned list of engine versions to those that are compatible with this parameter group family. :return: The list of database engine versions. """ try: kwargs = {"Engine": engine} if parameter_group_family is not None: kwargs["DBParameterGroupFamily"] = parameter_group_family response = self.rds_client.describe_db_engine_versions(**kwargs) versions = response["DBEngineVersions"] except ClientError as err: logger.error( "Couldn't get engine versions for %s. Here's why: %s: %s", engine, err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return versions-
Per informazioni dettagliate sull’API, consulta DescribeDBEngineVersions nella documentazione di riferimento dell’API AWS SDK per Python (Boto3).
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L’esempio di codice seguente mostra come utilizzare DescribeDBInstances.
- SDK per Python (Boto3)
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Nota
Ulteriori informazioni su GitHub. Trova l’esempio completo e scopri di più sulla configurazione e l’esecuzione nel Repository di esempi di codice AWS
. class AuroraWrapper: """Encapsulates Aurora DB cluster actions.""" def __init__(self, rds_client): """ :param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client. """ self.rds_client = rds_client @classmethod def from_client(cls): """ Instantiates this class from a Boto3 client. """ rds_client = boto3.client("rds") return cls(rds_client) def get_db_instance(self, instance_id): """ Gets data about a DB instance. :param instance_id: The ID of the DB instance to retrieve. :return: The retrieved DB instance. """ try: response = self.rds_client.describe_db_instances( DBInstanceIdentifier=instance_id ) db_inst = response["DBInstances"][0] except ClientError as err: if err.response["Error"]["Code"] == "DBInstanceNotFound": logger.info("Instance %s does not exist.", instance_id) else: logger.error( "Couldn't get DB instance %s. Here's why: %s: %s", instance_id, err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return db_inst-
Per informazioni dettagliate sull’API, consulta DescribeDBInstances nella documentazione di riferimento dell’API AWS SDK per Python (Boto3).
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L’esempio di codice seguente mostra come utilizzare DescribeOrderableDBInstanceOptions.
- SDK per Python (Boto3)
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Nota
Ulteriori informazioni su GitHub. Trova l’esempio completo e scopri di più sulla configurazione e l’esecuzione nel Repository di esempi di codice AWS
. class AuroraWrapper: """Encapsulates Aurora DB cluster actions.""" def __init__(self, rds_client): """ :param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client. """ self.rds_client = rds_client @classmethod def from_client(cls): """ Instantiates this class from a Boto3 client. """ rds_client = boto3.client("rds") return cls(rds_client) def get_orderable_instances(self, db_engine, db_engine_version): """ Gets DB instance options that can be used to create DB instances that are compatible with a set of specifications. :param db_engine: The database engine that must be supported by the DB instance. :param db_engine_version: The engine version that must be supported by the DB instance. :return: The list of DB instance options that can be used to create a compatible DB instance. """ try: inst_opts = [] paginator = self.rds_client.get_paginator( "describe_orderable_db_instance_options" ) for page in paginator.paginate( Engine=db_engine, EngineVersion=db_engine_version ): inst_opts += page["OrderableDBInstanceOptions"] except ClientError as err: logger.error( "Couldn't get orderable DB instances. Here's why: %s: %s", err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return inst_opts-
Per informazioni dettagliate sull’API, consulta DescribeOrderableDBInstanceOptions nella documentazione di riferimento dell’API AWS SDK per Python (Boto3).
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L’esempio di codice seguente mostra come utilizzare ModifyDBClusterParameterGroup.
- SDK per Python (Boto3)
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Nota
Ulteriori informazioni su GitHub. Trova l’esempio completo e scopri di più sulla configurazione e l’esecuzione nel Repository di esempi di codice AWS
. class AuroraWrapper: """Encapsulates Aurora DB cluster actions.""" def __init__(self, rds_client): """ :param rds_client: A Boto3 Amazon Relational Database Service (Amazon RDS) client. """ self.rds_client = rds_client @classmethod def from_client(cls): """ Instantiates this class from a Boto3 client. """ rds_client = boto3.client("rds") return cls(rds_client) def update_parameters(self, parameter_group_name, update_parameters): """ Updates parameters in a custom DB cluster parameter group. :param parameter_group_name: The name of the parameter group to update. :param update_parameters: The parameters to update in the group. :return: Data about the modified parameter group. """ try: response = self.rds_client.modify_db_cluster_parameter_group( DBClusterParameterGroupName=parameter_group_name, Parameters=update_parameters, ) except ClientError as err: logger.error( "Couldn't update parameters in %s. Here's why: %s: %s", parameter_group_name, err.response["Error"]["Code"], err.response["Error"]["Message"], ) raise else: return response-
Per informazioni dettagliate sull’API, consulta ModifyDBClusterParameterGroup nella documentazione di riferimento delle API SDK AWS per Python (Boto3).
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Scenari
L’esempio di codice seguente mostra come creare una libreria di prestiti in cui gli utenti possono prendere in prestito e restituire libri tramite una REST API supportata da un database Amazon Aurora.
- SDK per Python (Boto3)
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Mostra come usare AWS SDK per Python (Boto3) con l’API Amazon Relational Database Service (Amazon RDS) e AWS Chalice per creare una REST API supportata da un database Amazon Aurora. Il servizio Web è completamente serverless e rappresenta una semplice libreria di prestiti in cui gli utenti possono prendere in prestito e restituire libri. Scopri come:
Creare e gestire un cluster di database Aurora serverless.
Utilizzare Gestione dei segreti AWS per gestire le credenziali del database.
Implementare un livello di archiviazione di dati che utilizza Amazon RDS per spostare i dati dentro e fuori dal database.
Utilizzare AWS Chalice per distribuire una REST API serverless su Gateway Amazon API e AWS Lambda.
Utilizza il pacchetto Richieste per inviare le richieste al servizio Web.
Per il codice sorgente completo e le istruzioni su come configurare ed eseguire, consulta l’esempio completo su GitHub
. Servizi utilizzati in questo esempio
Gateway API
Aurora
Lambda
Secrets Manager
L’esempio di codice seguente mostra come creare un’applicazione web che traccia gli elementi di lavoro in database Amazon Aurora serverless e utilizza Amazon Simple Email Service (Amazon SES) per inviare report.
- SDK per Python (Boto3)
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Mostra come utilizzare AWS SDK per Python (Boto3) per creare un’applicazione web che traccia gli elementi di lavoro in database Amazon Aurora serverless e li segnala per e-mail tramite Amazon Simple Email Service (Amazon SES). Questo esempio utilizza il framework Web Flask per gestire il routing HTTP e si integra con una pagina web React per presentare un’applicazione web completamente funzionale.
Creazione di un servizio REST Flask che si integra con i Servizi AWS.
Lettura, scrittura e aggiornamento degli elementi di lavoro archiviati in un database Aurora serverless.
Creazione di un segreto Gestione dei segreti AWS che contenga le credenziali del database, da utilizzare per autenticare le chiamate al database.
Utilizzo di Amazon SES per inviare report via e-mail sugli elementi di lavoro.
Per il codice sorgente completo e le istruzioni su come configurare ed eseguire, consulta l’esempio completo su GitHub
. Servizi utilizzati in questo esempio
Aurora
Amazon RDS
Servizi di dati di Amazon RDS
Amazon SES