Question

我在本地运行minikube的python-kubernetes中使用python，例如没有云问题。

我正在尝试创建一个作业，并为其提供要运行的数据。我想为它提供一个包含本地计算机数据的目录。

我正在使用this示例，并尝试添加装载卷这是添加关键字volume_mounts后的代码（我尝试了多个位置，使用了多个关键字，但无济于事）

from os import path

import yaml

from kubernetes import client, config

JOB_NAME = "pi"


def create_job_object():
    # Configureate Pod template container
    container = client.V1Container(
        name="pi",
        image="perl",
        volume_mounts=["/home/user/data"],
        command=["perl", "-Mbignum=bpi", "-wle", "print bpi(2000)"])
    # Create and configurate a spec section
    template = client.V1PodTemplateSpec(
        metadata=client.V1ObjectMeta(labels={
            "app": "pi"}),
        spec=client.V1PodSpec(restart_policy="Never",
                              containers=[container]))
    # Create the specification of deployment
    spec = client.V1JobSpec(
        template=template,
        backoff_limit=0)
    # Instantiate the job object
    job = client.V1Job(
        api_version="batch/v1",
        kind="Job",
        metadata=client.V1ObjectMeta(name=JOB_NAME),
        spec=spec)

    return job


def create_job(api_instance, job):
    # Create job
    api_response = api_instance.create_namespaced_job(
        body=job,
        namespace="default")
    print("Job created. status='%s'" % str(api_response.status))


def update_job(api_instance, job):
    # Update container image
    job.spec.template.spec.containers[0].image = "perl"
    # Update the job
    api_response = api_instance.patch_namespaced_job(
        name=JOB_NAME,
        namespace="default",
        body=job)
    print("Job updated. status='%s'" % str(api_response.status))


def delete_job(api_instance):
    # Delete job
    api_response = api_instance.delete_namespaced_job(
        name=JOB_NAME,
        namespace="default",
        body=client.V1DeleteOptions(
            propagation_policy='Foreground',
            grace_period_seconds=5))
    print("Job deleted. status='%s'" % str(api_response.status))


def main():
    # Configs can be set in Configuration class directly or using helper
    # utility. If no argument provided, the config will be loaded from
    # default location.
    config.load_kube_config()
    batch_v1 = client.BatchV1Api()
    # Create a job object with client-python API. The job we
    # created is same as the `pi-job.yaml` in the /examples folder.


    job = create_job_object()

    create_job(batch_v1, job)

    update_job(batch_v1, job)

    delete_job(batch_v1)


if __name__ == '__main__':
    main()

我收到此错误

HTTP响应正文： {“种类”：“状态”，“ apiVersion”：“ v1”，“元数据”：{}，“状态”：“故障”，“消息”：“作业版本“ v1”中的版本不能作为Job：v1.Job.Spec： v1.JobSpec.Template：v1.PodTemplateSpec.Spec：v1.PodSpec。容器： [] v1.Container：v1.Container.VolumeMounts：[] v1.VolumeMount： readObjectStart：期望{或n，但找到\“，在＃10字节中发现错误 of || ounts \“：[\” / home / user | ...，更大的上下文... | \“图片\”： \“ perl \”，\“名称\”：\“ pi \”，\“ volumeMounts \”：[\“ / home / user / data \”]}]]， \“ restartPolicy \”：\“从不”，“}}}} | ...”，“原因”：“ BadRequest”，“代码”：400

我在这里想念什么？

还有另一种向工作公开数据的方法吗？

编辑：尝试使用client.V1Volumemount 我试图添加此代码，并在不同的init函数中添加安装对象，例如。

mount = client.V1VolumeMount(mount_path="/data", name="shai")

client.V1Container
client.V1PodTemplateSpec
client.V1JobSpec
client.V1Job

在多个关键字下都会导致错误，这是使用正确的对象吗？我如何使用它的外壳？

编辑：尝试将volume_mounts作为列表传递，答案中建议使用以下代码：

def create_job_object():
    # Configureate Pod template container
    container = client.V1Container(
        name="pi",
        image="perl",
        volume_mounts=["/home/user/data"],
        command=["perl", "-Mbignum=bpi", "-wle", "print bpi(2000)"])
    # Create and configurate a spec section
    template = client.V1PodTemplateSpec(
        metadata=client.V1ObjectMeta(labels={
            "app": "pi"}),
        spec=client.V1PodSpec(restart_policy="Never",
                              containers=[container]))
    # Create the specification of deployment
    spec = client.V1JobSpec(
        template=template,
        backoff_limit=0)
    # Instantiate the job object
    job = client.V1Job(
        api_version="batch/v1",
        kind="Job",
        metadata=client.V1ObjectMeta(name=JOB_NAME),
        spec=spec)

    return job

仍然出现类似错误

kubernetes.client.rest.ApiException：（422）原因：无法处理实体HTTP响应标头：HTTPHeaderDict（{'Content-Type'： 'application / json'，'Date'：'Tue，06 Aug 2019 06:19:13 GMT'， 'Content-Length'：'401'}）HTTP响应正文： {“种类”：“状态”，“ apiVersion”：“ v1”，“元数据”：{}，“状态”：“故障”，“消息”：“ Job.batch \“ pi \”无效： spec.template.spec.containers [0] .volumeMounts [0] .name：找不到： \“ d \”“，”原因“：”无效“，”详细信息“：{”名称“：” pi“，”组“：”批处理“，”种类“：”工作“，”原因“：[{ “原因”：“ FieldValueNotFound”，“消息”：“不发现： \“ d \”“，” field“：” spec.template.spec.containers [0] .volumeMounts [0] .name“}]}，” code“：422}

Answer 1

V1Container调用需要一个用于volume_mounts参数的V1VolumeMount对象列表，但是您传入了一个字符串列表：

代码：

def create_job_object():
    volume_mount = client.V1VolumeMount(
        mount_path="/home/user/data"
        # other optional arguments, see the volume mount doc link below
    )
    # Configureate Pod template container
    container = client.V1Container(
name="pi",
        image="perl",
        volume_mounts=[volume_mount],
        command=["perl", "-Mbignum=bpi", "-wle", "print bpi(2000)"])
    # Create and configurate a spec section
    template = client.V1PodTemplateSpec(
        metadata=client.V1ObjectMeta(labels={
            "app": "pi"}),
        spec=client.V1PodSpec(restart_policy="Never",
                              containers=[container]))
    ....

参考：

尝试挂载卷时出现python kubernetes API错误

1 个答案: