Microsoft Azure File DataLake Storage Client Library for Python
92
Pending
Does it follow best practices?
Impact
92%
0.98xAverage score across 10 eval scenarios
Pending
The risk profile of this skill
{
"context": "This criteria evaluates how well the engineer uses the azure-storage-file-datalake package to implement metadata management for files in Azure Data Lake Storage Gen2. The focus is on proper client initialization, correct method usage for getting and setting metadata, and appropriate handling of metadata operations.",
"type": "weighted_checklist",
"checklist": [
{
"name": "Client Initialization",
"description": "Correctly initializes DataLakeServiceClient or FileSystemClient using the account_url and credential parameters. Uses get_file_system_client() or get_file_client() to obtain the appropriate client for operations.",
"max_score": 20
},
{
"name": "File Client Creation",
"description": "Properly creates DataLakeFileClient instances for each file operation using get_file_client() method with the file_path parameter.",
"max_score": 15
},
{
"name": "Set Metadata Method",
"description": "Uses the set_metadata() method on DataLakeFileClient to add or update metadata. Passes metadata as a dictionary parameter to the method.",
"max_score": 25
},
{
"name": "Get Metadata Method",
"description": "Uses get_file_properties() method on DataLakeFileClient and accesses the metadata attribute from the returned properties object to retrieve metadata.",
"max_score": 25
},
{
"name": "Metadata Key Check",
"description": "Implements has_metadata_key() by retrieving metadata using get_file_properties() and checking if the key exists in the metadata dictionary using Python's 'in' operator or .get() method.",
"max_score": 15
}
]
}docs
evals
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