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如何使用CDKTF在AWS EC上部署Springboot API？

Linda Hamilton

Jan 24, 2025 am 10:11 AM

> Java开发人员问我如何在AWS ECS上部署其Spring Boot API时，我认为这是潜入CDKTF（Terraform云开发套件）项目的最新更新的绝佳机会。在上一篇文章中，我介绍了CDKTF，该框架使您可以使用Python等通用编程语言将基础结构编写为代码（IAC）。从那时起，CDKTF达到了第一个GA版本，使其成为重新访问它的最佳时机。在本文中，我们将使用CDKTF在AWS EC上部署Spring Boot API。

在我的github repo上找到本文的代码。

体系结构概述

>进入实施之前，让我们回顾一下我们旨在部署的体系结构：>

在此图中，我们可以将体系结构分解为03层：>

如何使用CDKTF在AWS EC上部署Springboot API？网络

：

> vpc

公共和私人子网 Internet网关
- > nat网关
- ：
应用程序负载平衡器（ALB）
侦听器 ecs cluster
- ：
>目标组
> ECS服务任务定义

/ping

：返回字符串“ pong”。该端点对于测试API的响应能力很有用。它还可以增加Prometheus计数器指标以进行监视。

/HealthCheck

：返回“确定”，用作健康检查端点，以确保应用程序正确运行。喜欢 /ping，它更新了普罗米修斯计数器以进行可观察性。

/Hello：接受名称查询参数（默认为“世界”）并返回个性化的问候，例如，“ Hello，[name]！”。此终点也与Prometheus计数器集成在一起。
>让我们添加 dockerfile
>

步骤2：设置AWS CDKTF aws cdktf允许您使用Python定义和管理AWS资源。

1。

FROM maven:3.9-amazoncorretto-21 AS builder

WORKDIR /app

COPY pom.xml .

COPY src src

RUN mvn clean package

# amazon java distribution
FROM amazoncorretto:21-alpine

COPY --from=builder /app/target/*.jar /app/java-api.jar

EXPOSE 8080

ENTRYPOINT ["java","-jar","/app/java-api.jar"]

>先决条件

2。

安装CDKTF和依赖项

>确保您通过安装CDKTF及其依赖项具有必要的工具：>

- [**python (3.13)**](https://www.python.org/)
- [**pipenv**](https://pipenv.pypa.io/en/latest/)
- [**npm**](https://nodejs.org/en/)

这安装了CDKTF CLI，该CLI允许为各种语言旋转新项目。

3。初始化您的CDKTF应用程序

>我们可以通过运行：>

FROM maven:3.9-amazoncorretto-21 AS builder

WORKDIR /app

COPY pom.xml .

COPY src src

RUN mvn clean package

# amazon java distribution
FROM amazoncorretto:21-alpine

COPY --from=builder /app/target/*.jar /app/java-api.jar

EXPOSE 8080

ENTRYPOINT ["java","-jar","/app/java-api.jar"]

默认创建了很多文件，并且安装了所有依赖项。

下面是初始的 main.py 文件：

- [**python (3.13)**](https://www.python.org/)
- [**pipenv**](https://pipenv.pypa.io/en/latest/)
- [**npm**](https://nodejs.org/en/)

第 3 步：构建图层

堆栈表示 CDK for Terraform (CDKTF) 编译成不同 Terraform 配置的一组基础设施资源。堆栈为应用程序中的不同环境提供单独的状态管理。为了跨层共享资源，我们将利用跨堆栈引用。

1. 网络层

将 network_stack.py 文件添加到您的项目

$ npm install -g cdktf-cli@latest

添加以下代码来创建所有网络资源：

# init the project using aws provider
$ mkdir samples-fargate

$ cd samples-fargate && cdktf init --template=python --providers=aws

然后，编辑main.py文件：

#!/usr/bin/env python
from constructs import Construct
from cdktf import App, TerraformStack

class MyStack(TerraformStack):
    def __init__(self, scope: Construct, id: str):
        super().__init__(scope, id)

        # define resources here

app = App()
MyStack(app, "aws-cdktf-samples-fargate")

app.synth()

通过运行以下命令生成 terraform 配置文件：

$ mkdir infra

$ cd infra && touch network_stack.py

使用以下命令部署网络堆栈：

from constructs import Construct
from cdktf import S3Backend, TerraformStack
from cdktf_cdktf_provider_aws.provider import AwsProvider
from cdktf_cdktf_provider_aws.vpc import Vpc
from cdktf_cdktf_provider_aws.subnet import Subnet
from cdktf_cdktf_provider_aws.eip import Eip
from cdktf_cdktf_provider_aws.nat_gateway import NatGateway
from cdktf_cdktf_provider_aws.route import Route
from cdktf_cdktf_provider_aws.route_table import RouteTable
from cdktf_cdktf_provider_aws.route_table_association import RouteTableAssociation
from cdktf_cdktf_provider_aws.internet_gateway import InternetGateway

class NetworkStack(TerraformStack):
    def __init__(self, scope: Construct, ns: str, params: dict):
        super().__init__(scope, ns)

        self.region = params["region"]

        # configure the AWS provider to use the us-east-1 region
        AwsProvider(self, "AWS", region=self.region)

        # use S3 as backend
        S3Backend(
            self,
            bucket=params["backend_bucket"],
            key=params["backend_key_prefix"] + "/network.tfstate",
            region=self.region,
        )

        # create the vpc
        vpc_demo = Vpc(self, "vpc-demo", cidr_block="192.168.0.0/16")

        # create two public subnets
        public_subnet1 = Subnet(
            self,
            "public-subnet-1",
            vpc_id=vpc_demo.id,
            availability_zone=f"{self.region}a",
            cidr_block="192.168.1.0/24",
        )

        public_subnet2 = Subnet(
            self,
            "public-subnet-2",
            vpc_id=vpc_demo.id,
            availability_zone=f"{self.region}b",
            cidr_block="192.168.2.0/24",
        )

        # create. the internet gateway
        igw = InternetGateway(self, "igw", vpc_id=vpc_demo.id)

        # create the public route table
        public_rt = Route(
            self,
            "public-rt",
            route_table_id=vpc_demo.main_route_table_id,
            destination_cidr_block="0.0.0.0/0",
            gateway_id=igw.id,
        )

        # create the private subnets
        private_subnet1 = Subnet(
            self,
            "private-subnet-1",
            vpc_id=vpc_demo.id,
            availability_zone=f"{self.region}a",
            cidr_block="192.168.10.0/24",
        )

        private_subnet2 = Subnet(
            self,
            "private-subnet-2",
            vpc_id=vpc_demo.id,
            availability_zone=f"{self.region}b",
            cidr_block="192.168.20.0/24",
        )

        # create the Elastic IPs
        eip1 = Eip(self, "nat-eip-1", depends_on=[igw])
        eip2 = Eip(self, "nat-eip-2", depends_on=[igw])

        # create the NAT Gateways
        private_nat_gw1 = NatGateway(
            self,
            "private-nat-1",
            subnet_id=public_subnet1.id,
            allocation_id=eip1.id,
        )

        private_nat_gw2 = NatGateway(
            self,
            "private-nat-2",
            subnet_id=public_subnet2.id,
            allocation_id=eip2.id,
        )

        # create Route Tables
        private_rt1 = RouteTable(self, "private-rt1", vpc_id=vpc_demo.id)
        private_rt2 = RouteTable(self, "private-rt2", vpc_id=vpc_demo.id)

        # add default routes to tables
        Route(
            self,
            "private-rt1-default-route",
            route_table_id=private_rt1.id,
            destination_cidr_block="0.0.0.0/0",
            nat_gateway_id=private_nat_gw1.id,
        )

        Route(
            self,
            "private-rt2-default-route",
            route_table_id=private_rt2.id,
            destination_cidr_block="0.0.0.0/0",
            nat_gateway_id=private_nat_gw2.id,
        )

        # associate routes with subnets
        RouteTableAssociation(
            self,
            "public-rt-association",
            subnet_id=private_subnet2.id,
            route_table_id=private_rt2.id,
        )

        RouteTableAssociation(
            self,
            "private-rt1-association",
            subnet_id=private_subnet1.id,
            route_table_id=private_rt1.id,
        )

        RouteTableAssociation(
            self,
            "private-rt2-association",
            subnet_id=private_subnet2.id,
            route_table_id=private_rt2.id,
        )

        # terraform outputs
        self.vpc_id = vpc_demo.id
        self.public_subnets = [public_subnet1.id, public_subnet2.id]
        self.private_subnets = [private_subnet1.id, private_subnet2.id]

Network Deployment

我们的 VPC 已准备就绪，如下图所示：

Network Map

2. 基础设施层

将 infra_stack.py 文件添加到您的项目

#!/usr/bin/env python
from constructs import Construct
from cdktf import App, TerraformStack
from infra.network_stack import NetworkStack

ENV = "dev"
AWS_REGION = "us-east-1"
BACKEND_S3_BUCKET = "blog.abdelfare.me"
BACKEND_S3_KEY = f"{ENV}/cdktf-samples"

class MyStack(TerraformStack):
    def __init__(self, scope: Construct, id: str):
        super().__init__(scope, id)

        # define resources here

app = App()
MyStack(app, "aws-cdktf-samples-fargate")

network = NetworkStack(
    app,
    "network",
    {
        "region": AWS_REGION,
        "backend_bucket": BACKEND_S3_BUCKET,
        "backend_key_prefix": BACKEND_S3_KEY,
    },
)

app.synth()

添加以下代码来创建所有基础设施资源：

$ cdktf synth

编辑main.py文件：

$ cdktf deploy network

使用以下命令部署基础设施堆栈：

$ cd infra && touch infra_stack.py

记下 ALB 的 DNS 名称，我们稍后会用到它。

ALB DNS

3. 服务层

将 service_stack.py 文件添加到您的项目

from constructs import Construct
from cdktf import S3Backend, TerraformStack
from cdktf_cdktf_provider_aws.provider import AwsProvider
from cdktf_cdktf_provider_aws.ecs_cluster import EcsCluster
from cdktf_cdktf_provider_aws.lb import Lb
from cdktf_cdktf_provider_aws.lb_listener import (
    LbListener,
    LbListenerDefaultAction,
    LbListenerDefaultActionFixedResponse,
)
from cdktf_cdktf_provider_aws.security_group import (
    SecurityGroup,
    SecurityGroupIngress,
    SecurityGroupEgress,
)

class InfraStack(TerraformStack):
    def __init__(self, scope: Construct, ns: str, network: dict, params: dict):
        super().__init__(scope, ns)

        self.region = params["region"]

        # Configure the AWS provider to use the us-east-1 region
        AwsProvider(self, "AWS", region=self.region)

        # use S3 as backend
        S3Backend(
            self,
            bucket=params["backend_bucket"],
            key=params["backend_key_prefix"] + "/load_balancer.tfstate",
            region=self.region,
        )

        # create the ALB security group
        alb_sg = SecurityGroup(
            self,
            "alb-sg",
            vpc_id=network["vpc_id"],
            ingress=[
                SecurityGroupIngress(
                    protocol="tcp", from_port=80, to_port=80, cidr_blocks=["0.0.0.0/0"]
                )
            ],
            egress=[
                SecurityGroupEgress(
                    protocol="-1", from_port=0, to_port=0, cidr_blocks=["0.0.0.0/0"]
                )
            ],
        )

        # create the ALB
        alb = Lb(
            self,
            "alb",
            internal=False,
            load_balancer_type="application",
            security_groups=[alb_sg.id],
            subnets=network["public_subnets"],
        )

        # create the LB Listener
        alb_listener = LbListener(
            self,
            "alb-listener",
            load_balancer_arn=alb.arn,
            port=80,
            protocol="HTTP",
            default_action=[
                LbListenerDefaultAction(
                    type="fixed-response",
                    fixed_response=LbListenerDefaultActionFixedResponse(
                        content_type="text/plain",
                        status_code="404",
                        message_body="Could not find the resource you are looking for",
                    ),
                )
            ],
        )

        # create the ECS cluster
        cluster = EcsCluster(self, "cluster", name=params["cluster_name"])

        self.alb_arn = alb.arn
        self.alb_listener = alb_listener.arn
        self.alb_sg = alb_sg.id
        self.cluster_id = cluster.id

添加以下代码来创建所有 ECS 服务资源：

...

CLUSTER_NAME = "cdktf-samples"
...

infra = InfraStack(
    app,
    "infra",
    {
        "vpc_id": network.vpc_id,
        "public_subnets": network.public_subnets,
    },
    {
        "region": AWS_REGION,
        "backend_bucket": BACKEND_S3_BUCKET,
        "backend_key_prefix": BACKEND_S3_KEY,
        "cluster_name": CLUSTER_NAME,
    },
)
...

更新main.py（最后一次？）：

$ cdktf deploy network infra

使用以下命令部署服务堆栈：

$ mkdir apps

$ cd apps && touch service_stack.py

我们来了！

我们成功创建了在 AWS ECS Fargate 上部署新服务的所有资源。

运行以下命令来获取您的堆栈列表

from constructs import Construct
import json
from cdktf import S3Backend, TerraformStack, Token, TerraformOutput
from cdktf_cdktf_provider_aws.provider import AwsProvider
from cdktf_cdktf_provider_aws.ecs_service import (
    EcsService,
    EcsServiceLoadBalancer,
    EcsServiceNetworkConfiguration,
)
from cdktf_cdktf_provider_aws.ecr_repository import (
    EcrRepository,
    EcrRepositoryImageScanningConfiguration,
)
from cdktf_cdktf_provider_aws.ecr_lifecycle_policy import EcrLifecyclePolicy
from cdktf_cdktf_provider_aws.ecs_task_definition import (
    EcsTaskDefinition,
)
from cdktf_cdktf_provider_aws.lb_listener_rule import (
    LbListenerRule,
    LbListenerRuleAction,
    LbListenerRuleCondition,
    LbListenerRuleConditionPathPattern,
)
from cdktf_cdktf_provider_aws.lb_target_group import (
    LbTargetGroup,
    LbTargetGroupHealthCheck,
)
from cdktf_cdktf_provider_aws.security_group import (
    SecurityGroup,
    SecurityGroupIngress,
    SecurityGroupEgress,
)
from cdktf_cdktf_provider_aws.cloudwatch_log_group import CloudwatchLogGroup
from cdktf_cdktf_provider_aws.data_aws_iam_policy_document import (
    DataAwsIamPolicyDocument,
)
from cdktf_cdktf_provider_aws.iam_role import IamRole
from cdktf_cdktf_provider_aws.iam_role_policy_attachment import IamRolePolicyAttachment

class ServiceStack(TerraformStack):
    def __init__(
        self, scope: Construct, ns: str, network: dict, infra: dict, params: dict
    ):
        super().__init__(scope, ns)

        self.region = params["region"]

        # Configure the AWS provider to use the us-east-1 region
        AwsProvider(self, "AWS", region=self.region)

        # use S3 as backend
        S3Backend(
            self,
            bucket=params["backend_bucket"],
            key=params["backend_key_prefix"] + "/" + params["app_name"] + ".tfstate",
            region=self.region,
        )

        # create the service security group
        svc_sg = SecurityGroup(
            self,
            "svc-sg",
            vpc_id=network["vpc_id"],
            ingress=[
                SecurityGroupIngress(
                    protocol="tcp",
                    from_port=params["app_port"],
                    to_port=params["app_port"],
                    security_groups=[infra["alb_sg"]],
                )
            ],
            egress=[
                SecurityGroupEgress(
                    protocol="-1", from_port=0, to_port=0, cidr_blocks=["0.0.0.0/0"]
                )
            ],
        )

        # create the service target group
        svc_tg = LbTargetGroup(
            self,
            "svc-target-group",
            name="svc-tg",
            port=params["app_port"],
            protocol="HTTP",
            vpc_id=network["vpc_id"],
            target_type="ip",
            health_check=LbTargetGroupHealthCheck(path="/ping", matcher="200"),
        )

        # create the service listener rule
        LbListenerRule(
            self,
            "alb-rule",
            listener_arn=infra["alb_listener"],
            action=[LbListenerRuleAction(type="forward", target_group_arn=svc_tg.arn)],
            condition=[
                LbListenerRuleCondition(
                    path_pattern=LbListenerRuleConditionPathPattern(values=["/*"])
                )
            ],
        )

        # create the ECR repository
        repo = EcrRepository(
            self,
            params["app_name"],
            image_scanning_configuration=EcrRepositoryImageScanningConfiguration(
                scan_on_push=True
            ),
            image_tag_mutability="MUTABLE",
            name=params["app_name"],
        )

        EcrLifecyclePolicy(
            self,
            "this",
            repository=repo.name,
            policy=json.dumps(
                {
                    "rules": [
                        {
                            "rulePriority": 1,
                            "description": "Keep last 10 images",
                            "selection": {
                                "tagStatus": "tagged",
                                "tagPrefixList": ["v"],
                                "countType": "imageCountMoreThan",
                                "countNumber": 10,
                            },
                            "action": {"type": "expire"},
                        },
                        {
                            "rulePriority": 2,
                            "description": "Expire images older than 3 days",
                            "selection": {
                                "tagStatus": "untagged",
                                "countType": "sinceImagePushed",
                                "countUnit": "days",
                                "countNumber": 3,
                            },
                            "action": {"type": "expire"},
                        },
                    ]
                }
            ),
        )

        # create the service log group
        service_log_group = CloudwatchLogGroup(
            self,
            "svc_log_group",
            name=params["app_name"],
            retention_in_days=1,
        )

        ecs_assume_role = DataAwsIamPolicyDocument(
            self,
            "assume_role",
            statement=[
                {
                    "actions": ["sts:AssumeRole"],
                    "principals": [
                        {
                            "identifiers": ["ecs-tasks.amazonaws.com"],
                            "type": "Service",
                        },
                    ],
                },
            ],
        )

        # create the service execution role
        service_execution_role = IamRole(
            self,
            "service_execution_role",
            assume_role_policy=ecs_assume_role.json,
            name=params["app_name"] + "-exec-role",
        )

        IamRolePolicyAttachment(
            self,
            "ecs_role_policy",
            policy_arn="arn:aws:iam::aws:policy/service-role/AmazonECSTaskExecutionRolePolicy",
            role=service_execution_role.name,
        )

        # create the service task role
        service_task_role = IamRole(
            self,
            "service_task_role",
            assume_role_policy=ecs_assume_role.json,
            name=params["app_name"] + "-task-role",
        )

        # create the service task definition
        task = EcsTaskDefinition(
            self,
            "svc-task",
            family="service",
            network_mode="awsvpc",
            requires_compatibilities=["FARGATE"],
            cpu="256",
            memory="512",
            task_role_arn=service_task_role.arn,
            execution_role_arn=service_execution_role.arn,
            container_definitions=json.dumps(
                [
                    {
                        "name": "svc",
                        "image": f"{repo.repository_url}:latest",
                        "networkMode": "awsvpc",
                        "healthCheck": {
                            "Command": ["CMD-SHELL", "echo hello"],
                            "Interval": 5,
                            "Timeout": 2,
                            "Retries": 3,
                        },
                        "portMappings": [
                            {
                                "containerPort": params["app_port"],
                                "hostPort": params["app_port"],
                            }
                        ],
                        "logConfiguration": {
                            "logDriver": "awslogs",
                            "options": {
                                "awslogs-group": service_log_group.name,
                                "awslogs-region": params["region"],
                                "awslogs-stream-prefix": params["app_name"],
                            },
                        },
                    }
                ]
            ),
        )

        # create the ECS service
        EcsService(
            self,
            "ecs_service",
            name=params["app_name"] + "-service",
            cluster=infra["cluster_id"],
            task_definition=task.arn,
            desired_count=params["desired_count"],
            launch_type="FARGATE",
            force_new_deployment=True,
            network_configuration=EcsServiceNetworkConfiguration(
                subnets=network["private_subnets"],
                security_groups=[svc_sg.id],
            ),
            load_balancer=[
                EcsServiceLoadBalancer(
                    target_group_arn=svc_tg.id,
                    container_name="svc",
                    container_port=params["app_port"],
                )
            ],
        )

        TerraformOutput(
            self,
            "ecr_repository_url",
            description="url of the ecr repo",
            value=repo.repository_url,
        )

Stack List

步骤4：github动作工作流程

为了使部署自动化，让我们将一个github操作集成到我们的 java-api

。启用GITHUB操作后，为您的存储库设置秘密和变量，创建.github/workflows/deploy.yml文件，然后添加以下内容：
我们的工作流程正常：

FROM maven:3.9-amazoncorretto-21 AS builder

WORKDIR /app

COPY pom.xml .

COPY src src

RUN mvn clean package

# amazon java distribution
FROM amazoncorretto:21-alpine

COPY --from=builder /app/target/*.jar /app/java-api.jar

EXPOSE 8080

ENTRYPOINT ["java","-jar","/app/java-api.jar"]

该服务已成功部署，如下图所示：> Github Actions

步骤5：验证部署

ECS Service >使用以下脚本测试您的部署（

用您的

替换ALB URL）：>

ALB现在准备为流量服务！

- [**python (3.13)**](https://www.python.org/)
- [**pipenv**](https://pipenv.pypa.io/en/latest/)
- [**npm**](https://nodejs.org/en/)

最终想法

通过利用AWS CDKTF，我们可以使用Python编写干净，可维护的IAC代码。这种方法简化了部署容器化的应用程序，例如AWS ECS Fargate上的Spring Boot API。 CDKTF的灵活性，再加上Terraform的强大功能，使其成为现代云部署的绝佳选择。

> CDKTF项目为基础架构管理提供了许多有趣的功能，但我必须承认，我有时发现它有些冗长。

> 您对CDKTF有任何经验吗？您是否在生产中使用过？随时与我们分享您的经验。

以上是如何使用CDKTF在AWS EC上部署Springboot API？的详细内容。更多信息请关注PHP中文网其他相关文章！

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Python是否列表动态阵列或引擎盖下的链接列表？May 07, 2025 am 12:16 AM

pythonlistsareimplementedasdynamicarrays，notlinkedlists.1）他们areStoredIncoNtiguulMemoryBlocks，mayrequireRealLealLocationWhenAppendingItems，EmpactingPerformance.2）LinkesedlistSwoldOfferefeRefeRefeRefeRefficeInsertions/DeletionsButslowerIndexeDexedAccess，Lestpypytypypytypypytypy

如何从python列表中删除元素？May 07, 2025 am 12:15 AM

pythonoffersFourmainMethodStoreMoveElement Fromalist：1）删除（值）emovesthefirstoccurrenceofavalue，2）pop（index）emovesanderturnsanelementataSpecifiedIndex，3）delstatementremoveselemsbybybyselementbybyindexorslicebybyindexorslice，and 4）

试图运行脚本时，应该检查是否会遇到'权限拒绝”错误？May 07, 2025 am 12:12 AM

toresolvea“ dermissionded”错误Whenrunningascript，跟随台词：1）CheckAndAdjustTheScript'Spermissions ofchmod xmyscript.shtomakeitexecutable.2）nesureThEseRethEserethescriptistriptocriptibationalocatiforecationAdirectorywherewhereyOuhaveWritePerMissionsyOuhaveWritePermissionsyYouHaveWritePermissions，susteSyAsyOURHomeRecretectory。

与Python的图像处理中如何使用阵列？May 07, 2025 am 12:04 AM

ArraysarecrucialinPythonimageprocessingastheyenableefficientmanipulationandanalysisofimagedata.1)ImagesareconvertedtoNumPyarrays,withgrayscaleimagesas2Darraysandcolorimagesas3Darrays.2)Arraysallowforvectorizedoperations,enablingfastadjustmentslikebri

对于哪些类型的操作，阵列比列表要快得多？May 07, 2025 am 12:01 AM

ArraySaresificatificallyfasterthanlistsForoperationsBenefiting fromDirectMemoryAcccccccCesandFixed-Sizestructures.1）conscessingElements：arraysprovideconstant-timeaccessduetocontoconcotigunmorystorage.2）iteration：araysleveragececacelocality.3）

说明列表和数组之间元素操作的性能差异。May 06, 2025 am 12:15 AM

ArraySareBetterForlement-WiseOperationsDuetofasterAccessCessCessCessCessCessAndOptimizedImplementations.1）ArrayshaveContiguucuulmemoryfordirectAccesscess.2）列出sareflexible butslible dueTopotentEnallymideNamicizing.3）forlarargedAtaTasetsetsetsetsetsetsetsetsetsetsetlib

如何有效地对整个Numpy阵列进行数学操作？May 06, 2025 am 12:15 AM

在NumPy中进行整个数组的数学运算可以通过向量化操作高效实现。 1)使用简单运算符如加法（arr 2）可对数组进行运算。 2)NumPy使用C语言底层库，提升了运算速度。 3)可以进行乘法、除法、指数等复杂运算。 4)需注意广播操作，确保数组形状兼容。 5)使用NumPy函数如np.sum()能显着提高性能。

您如何将元素插入python数组中？May 06, 2025 am 12:14 AM

在Python中，向列表插入元素有两种主要方法：1)使用insert(index,value)方法，可以在指定索引处插入元素，但在大列表开头插入效率低；2)使用append(value)方法，在列表末尾添加元素，效率高。对于大列表，建议使用append()或考虑使用deque或NumPy数组来优化性能。

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