Python client library for Google Cloud Platform services including Datastore, Storage, and Pub/Sub
93
Pending
Does it follow best practices?
Impact
93%
1.19xAverage score across 10 eval scenarios
Pending
The risk profile of this skill
{
"context": "This criteria evaluates the engineer's ability to use gcloud's datastore batch context manager functionality. The focus is on proper usage of client.batch() context manager, entity creation with datastore.Key and datastore.Entity, and batch operations like put() and delete().",
"type": "weighted_checklist",
"checklist": [
{
"name": "Batch context manager",
"description": "Uses client.batch() as a context manager (with statement) to group multiple datastore operations together",
"max_score": 30
},
{
"name": "Entity and Key creation",
"description": "Correctly creates datastore.Entity objects with datastore.Key for storing product data",
"max_score": 20
},
{
"name": "Batch put operations",
"description": "Uses batch.put() or client.put() within batch context to add or update entities",
"max_score": 20
},
{
"name": "Batch delete operations",
"description": "Uses batch.delete() or client.delete() within batch context to remove entities by their keys",
"max_score": 15
},
{
"name": "Automatic commit",
"description": "Relies on the batch context manager's automatic commit on successful exit (no explicit commit() call needed)",
"max_score": 10
},
{
"name": "Exception safety",
"description": "Demonstrates understanding that exceptions prevent batch commit, ensuring atomicity",
"max_score": 5
}
]
}evals
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