Python client library for Modal, a serverless cloud computing platform that enables developers to run Python code in the cloud with on-demand access to compute resources.
85
{
"context": "This evaluation assesses how well the engineer uses Modal's output control features to build a distributed log processing system. The focus is on using enable_output() to stream remote worker logs locally, proper Modal app structure with decorators, and parallel execution patterns.",
"type": "weighted_checklist",
"checklist": [
{
"name": "Output Control Usage",
"description": "Uses modal.enable_output() or app.run() context manager to stream output from remote workers to the local terminal. This is the core capability being tested - ensuring logs from distributed workers are visible locally.",
"max_score": 40
},
{
"name": "Modal App Setup",
"description": "Creates a modal.App instance and uses @app.function() decorator to define remote functions. The app should be properly initialized and functions should be correctly decorated for remote execution.",
"max_score": 15
},
{
"name": "Local Entrypoint",
"description": "Uses @app.local_entrypoint() decorator to define the CLI entry point that runs locally and orchestrates remote execution. This ensures proper separation between local orchestration and remote execution.",
"max_score": 10
},
{
"name": "Parallel Execution",
"description": "Uses function.map() or function.starmap() to process multiple log files in parallel across remote workers. This demonstrates understanding of Modal's distributed execution patterns.",
"max_score": 20
},
{
"name": "Function Implementation",
"description": "Implements process_log_file() as a remote Modal function that processes individual files and returns structured results. The function should handle file reading and log analysis correctly.",
"max_score": 10
},
{
"name": "Print Statements",
"description": "Includes print statements within remote functions to demonstrate that output is being captured and streamed. Without enable_output(), these prints would not be visible locally.",
"max_score": 5
}
]
}Install with Tessl CLI
npx tessl i tessl/pypi-modaldocs
evals
scenario-1
scenario-2
scenario-3
scenario-4
scenario-5
scenario-6
scenario-7
scenario-8
scenario-9
scenario-10