Microsoft Azure Data Tables Client Library for Python
90
Pending
Does it follow best practices?
Impact
90%
0.96xAverage score across 10 eval scenarios
Pending
The risk profile of this skill
{
"context": "This criteria evaluates how effectively the engineer uses the azure-data-tables package's property projection capabilities to retrieve only specified fields from Azure Table Storage entities. The focus is on proper usage of the select parameter in query and list operations to minimize bandwidth and improve performance.",
"type": "weighted_checklist",
"checklist": [
{
"name": "TableClient initialization",
"description": "Uses TableClient.from_connection_string() to create a table client from the connection string obtained from the AZURE_TABLES_CONNECTION_STRING environment variable",
"max_score": 15
},
{
"name": "select parameter usage",
"description": "Uses the select parameter in list_entities() or query_entities() method calls to specify which fields to retrieve, passing a list of field names",
"max_score": 30
},
{
"name": "list_entities projection",
"description": "Implements list_entities() with select parameter to retrieve all entities with only specified fields (e.g., table_client.list_entities(select=['Name', 'Email']))",
"max_score": 25
},
{
"name": "query_entities projection",
"description": "Implements query_entities() with both query_filter and select parameters to filter and project fields simultaneously (e.g., table_client.query_entities(query_filter='Age gt 25', select=['Name', 'City']))",
"max_score": 25
},
{
"name": "Iterator handling",
"description": "Properly returns or iterates over the ItemPaged object returned by list_entities() or query_entities() to yield entity results",
"max_score": 5
}
]
}docs
evals
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