Récupérer les entrées de job

Récupérez les valeurs d'entrée fournies lors de l'exécution d'un job. Utilisez pour déboguer, reproduire des résultats ou auditer des soumissions de jobs.

Spar Skills Guide Bot
DevOpsIntermédiaire
2020/08/2026
Claude Code
#job-inputs#weaver#api#debugging#auditing

Recommandé pour


name: job-inputs description: | Retrieve the input specifications and values that were provided when a job was executed. Shows what parameters were used to run the process. Use for debugging, reproducing results, or auditing job submissions. license: Apache-2.0 compatibility: Requires Weaver API access. metadata: author: fmigneault

Get Job Inputs

Retrieve the input values that were provided when a job was executed.

When to Use

  • Reviewing parameters used for a job
  • Reproducing job execution with same inputs
  • Debugging parameter-related issues
  • Auditing job submissions
  • Documenting workflow configurations
  • Comparing inputs across multiple job runs

Parameters

Required

  • job_id (string): Job identifier

CLI Usage

# Get job inputs
weaver inputs -u $WEAVER_URL -j a1b2c3d4-e5f6-7890-abcd-ef1234567890

# Save inputs for reuse
weaver inputs -u $WEAVER_URL -j a1b2c3d4-e5f6-7890-abcd-ef1234567890 > inputs-to-reuse.json

# Resubmit with same inputs
weaver execute -u $WEAVER_URL -p my-process -I inputs-to-reuse.json

Python Usage

from weaver.cli import WeaverClient

client = WeaverClient(url="https://weaver.example.com")

# Get inputs
inputs = client.inputs(job_id="a1b2c3d4-e5f6-7890-abcd-ef1234567890")

for input_name, input_value in inputs.body.items():
    print(f"{input_name}: {input_value}")

# Reuse inputs for another job
new_job = client.execute(
    process_id="my-process",
    inputs=inputs.body
)

API Request

curl -X GET \
  "${WEAVER_URL}/jobs/a1b2c3d4-e5f6-7890-abcd-ef1234567890/inputs"

Returns

{
  "input1": "value1",
  "input2": {
    "href": "https://example.com/input-file.nc",
    "type": "application/netcdf"
  },
  "threshold": 0.5,
  "enabled": true
}

Note: Response may include additional fields. See API documentation for complete response schemas.

Input Types

Literal Values

{
  "parameter": "string value",
  "count": 42,
  "enabled": true
}

File References

{
  "input_file": {
    "href": "https://example.com/data.tif",
    "type": "image/tiff"
  }
}

Arrays

{
  "files": [
    {"href": "https://example.com/file1.nc"},
    {"href": "https://example.com/file2.nc"}
  ]
}

Vault References

{
  "credentials": {
    "href": "vault://secret-token"
  }
}

Use Cases

Reproduce Results

# Get inputs from successful job
weaver inputs -u $WEAVER_URL -j c3d4e5f6-a7b8-9012-cdef-123456789012 > good-inputs.json

# Run again with same parameters
weaver execute -u $WEAVER_URL -p my-process -I good-inputs.json

Debug Failed Jobs

# Compare inputs between successful and failed jobs
success_inputs = client.inputs(job_id="success-job-id")
failed_inputs = client.inputs(job_id="d4e5f6a7-b8c9-0123-def1-234567890123")

# Find differences
for key in success_inputs.body:
    if success_inputs.body[key] != failed_inputs.body.get(key):
        print(f"Different value for {key}")

Audit Trail

# Document what inputs were used
weaver inputs -u $WEAVER_URL -j $JOB_ID | tee audit/job-$JOB_ID-inputs.json

Related Skills

Documentation

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