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API Reference

Welcome to the RHAPSODY API Reference. This section provides detailed documentation for all public APIs, classes, and functions in RHAPSODY.

Core Modules

rhapsody.backends

Backend implementations for different execution environments.

Backends API

rhapsody.session

Session management for workflow orchestration.

Session API

rhapsody.tasks

Task definition and specification utilities.

Tasks API

rhapsody.config

Configuration management and utilities.

Configuration API

rhapsody.utils

Utility functions and helpers.

Utilities API

Quick Reference

Basic Usage

import rhapsody
from rhapsody.backends import Session

# Create session and get backend
session = Session()
backend = rhapsody.get_backend("dask")

# Define tasks
tasks = [
    {
        "uid": "example_task",
        "executable": "echo",
        "arguments": ["Hello, World!"]
    }
]

# Submit and execute
backend = rhapsody.get_backend("dask")
await backend.submit_tasks(tasks)

### Common Patterns

#### Task Dependencies

```python
tasks = [
    {"uid": "task_1", "executable": "echo", "arguments": ["step 1"]},
    {"uid": "task_2", "executable": "echo", "arguments": ["step 2"],
     "dependencies": ["task_1"]}
]

Error Handling

try:
    await backend.submit_tasks(tasks)
    await backend.wait()
except Exception as e:
    print(f"Workflow failed: {e}")

Callbacks

def monitor_progress(task, state):
    print(f"Task {task['uid']}: {state}")

backend.register_callback(monitor_progress)

API Index

Functions

Classes

Exceptions

Type Definitions

RHAPSODY uses type hints throughout. Key type definitions:

from typing import Dict, List, Any, Optional, Callable

TaskDict = Dict[str, Any]
TaskList = List[TaskDict]
CallbackFunction = Callable[[TaskDict, str], None]

Configuration Schema

Task definition schema:

task:
  uid: string               # Required: Unique identifier
  executable: string        # Required: Command to execute
  arguments: list           # Optional: Command arguments
  dependencies: list        # Optional: Task UIDs this depends on
  input_staging: list       # Optional: Input files to stage
  output_staging: list      # Optional: Output files to collect
  environment: dict         # Optional: Environment variables
  working_directory: string # Optional: Working directory
  cpu_cores: integer        # Optional: CPU cores required
  gpu_cores: integer        # Optional: GPU cores required
  memory: string            # Optional: Memory requirement (e.g., "4GB")
  walltime: string          # Optional: Maximum runtime (e.g., "1:00:00")

Version Information

Current Version: 0.1.0 Release Date: 2024 Source Code: GitHub Repository

API Stability

  • Stable APIs: Core functionality is stable and backward compatible
  • Experimental APIs: Marked with @experimental decorator
  • Deprecated APIs: Will include deprecation warnings

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