Hacktoberfest 2026 : les issues que les mainteneurs ont marquées pour octobre, ouvertes et accessibles aux débutants. Parcourir les issues Hacktoberfest

mypy typing errors for batch enum's

Ouverte
  • Quelque chose ne va pas ?
#13,302 1 commentaire 0 réactions 0 personnes assignées Voir sur GitHub

Les mainteneurs répondent en général sous 5 jours

Personne n'a encore pris cette issue.

Évaluation

Difficulté
2/5
Temps estimé
1-3 heures
Accessibilité débutants
35/100
Type d'issue
Bug
Clarté
Clairement spécifiée
Activité
À l'abandon
Stack technique
google-cloud, python
Domaine
cloud

Piste de recherche

Commencez par copier l’exemple officiel de Batch dans batch_example.py et par exécuter mypy 1.11.2. Inspectez l’affectation à logs_policy.destination à la ligne signalée ; le travail est terminé lorsque l’exemple ne produit aucune erreur mypy tout en préservant le comportement documenté de Batch.

Rédigé par le modèle d'indexation à partir du texte de l'issue.

Description

priority: p2 samples triage me type: bug
Determine this is the right repository
  • I determined this is the correct repository in which to report this bug.
Summary of the issue

Context
Running mypy on this official code sample (copy and paste into a file batch_example.py and running mypy batch_example.py)

Expected Behavior:
No mypy errors

Actual Behavior:
mypy errors:

batch_example.py:66: error: Incompatible types in assignment (expression has type "int", variable has type "Destination")  [assignment]
Found 1 error in 1 file (checked 1 source file)
API client name and version

google-cloud-batch v0.17.28

Reproduction steps: code
from google.cloud import batch_v1


def create_container_job(project_id: str, region: str, job_name: str) -> batch_v1.Job:
    """
    This method shows how to create a sample Batch Job that will run
    a simple command inside a container on Cloud Compute instances.

    Args:
        project_id: project ID or project number of the Cloud project you want to use.
        region: name of the region you want to use to run the job. Regions that are
            available for Batch are listed on: https://cloud.google.com/batch/docs/get-started#locations
        job_name: the name of the job that will be created.
            It needs to be unique for each project and region pair.

    Returns:
        A job object representing the job created.
    """
    client = batch_v1.BatchServiceClient()

    # Define what will be done as part of the job.
    runnable = batch_v1.Runnable()
    runnable.container = batch_v1.Runnable.Container()
    runnable.container.image_uri = "gcr.io/google-containers/busybox"
    runnable.container.entrypoint = "/bin/sh"
    runnable.container.commands = [
        "-c",
        "echo Hello world! This is task ${BATCH_TASK_INDEX}. This job has a total of ${BATCH_TASK_COUNT} tasks.",
    ]

    # Jobs can be divided into tasks. In this case, we have only one task.
    task = batch_v1.TaskSpec()
    task.runnables = [runnable]

    # We can specify what resources are requested by each task.
    resources = batch_v1.ComputeResource()
    resources.cpu_milli = 2000  # in milliseconds per cpu-second. This means the task requires 2 whole CPUs.
    resources.memory_mib = 16  # in MiB
    task.compute_resource = resources

    task.max_retry_count = 2
    task.max_run_duration = "3600s"

    # Tasks are grouped inside a job using TaskGroups.
    # Currently, it's possible to have only one task group.
    group = batch_v1.TaskGroup()
    group.task_count = 4
    group.task_spec = task

    # Policies are used to define on what kind of virtual machines the tasks will run on.
    # In this case, we tell the system to use "e2-standard-4" machine type.
    # Read more about machine types here: https://cloud.google.com/compute/docs/machine-types
    policy = batch_v1.AllocationPolicy.InstancePolicy()
    policy.machine_type = "e2-standard-4"
    instances = batch_v1.AllocationPolicy.InstancePolicyOrTemplate()
    instances.policy = policy
    allocation_policy = batch_v1.AllocationPolicy()
    allocation_policy.instances = [instances]

    job = batch_v1.Job()
    job.task_groups = [group]
    job.allocation_policy = allocation_policy
    job.labels = {"env": "testing", "type": "container"}
    # We use Cloud Logging as it's an out of the box available option
    job.logs_policy = batch_v1.LogsPolicy()
    job.logs_policy.destination = batch_v1.LogsPolicy.Destination.CLOUD_LOGGING

    create_request = batch_v1.CreateJobRequest()
    create_request.job = job
    create_request.job_id = job_name
    # The job's parent is the region in which the job will run
    create_request.parent = f"projects/{project_id}/locations/{region}"

    return client.create_job(create_request)
Reproduction steps: supporting files

No response

Reproduction steps: actual results
batch_example.py:66: error: Incompatible types in assignment (expression has type "int", variable has type "Destination")  [assignment]
Found 1 error in 1 file (checked 1 source file)
Reproduction steps: expected results
Success: no issues found in 1 source file
OS & version + platform

macOS 15.0.1

Python environment

Python 3.11.10

Python dependencies
Package                  Version
------------------------ ---------
cachetools               5.5.0
certifi                  2024.8.30
charset-normalizer       3.3.2
google-api-core          2.20.0
google-auth              2.35.0
google-cloud-batch       0.17.28
googleapis-common-protos 1.65.0
grpcio                   1.66.2
grpcio-status            1.66.2
idna                     3.10
mypy                     1.11.2
mypy-extensions          1.0.0
pip                      24.2
proto-plus               1.24.0
protobuf                 5.28.2
pyasn1                   0.6.1
pyasn1_modules           0.4.1
requests                 2.32.3
rsa                      4.9
setuptools               75.1.0
typing_extensions        4.12.2
urllib3                  2.2.3
Langage dominant
Jupyter Notebook
Étoiles
8.1k
Forks
6.7k
Merge moyen
4 j 12 h
PR mergées (30 j)
9

Préparer son environnement

Par où commencer

  1. Lisez l'issue en entier, puis le guide de contribution du projet.
  2. Signalez en commentaire que vous la prenez — cela évite que deux personnes fassent le même travail.
  3. Forkez le dépôt et travaillez sur une branche.
  4. Ouvrez une pull request qui référence le numéro de l'issue.

Autres issues de GoogleCloudPlatform/python-docs-samples

Toutes les issues de GoogleCloudPlatform/python-docs-samples

Issues similaires

Plus d'issues Cloud

Recevez les nouvelles issues par e-mail

Un résumé court des issues GitHub adaptées aux débutants.