async-operations

name	async-operations
description	Asynchronous operation patterns including polling, timeouts, and non-blocking workflows. Use when user asks about async rendering, non-blocking operations, polling, timeouts, or parallel rendering.
license	LicenseRef-NvidiaProprietary
version	0.3.0
author	NVIDIA ovrtx
tags	["ovrtx","async","operations"]
tools	["Read","Grep"]

Async Operations

When to Use

Use this skill when the user asks about async rendering, non-blocking operations, polling, timeouts, or parallel rendering.

Inputs

Resolve inputs in this order: existing repository files and referenced snippets, explicit user request, then broader agent context.

• Target API surface: Python, C/C++, or both.
• Operation type: USD load/reference, render step, reset, clone, query, attribute read/write, or result fetch.
• Desired control flow: blocking wait, non-blocking poll, finite timeout, progress reporting, or two-stage result fetching.
• Language-specific handle involved: Python Operation, pending fetch object, C ovrtx_op_id_t, or result handle.
• Repository source snippets referenced below. Treat these snippets as the API source of truth.

Prerequisites

• Use an ovrtx checkout that contains the referenced examples and docs tests.
• Read the relevant > **Source:** snippet before writing or explaining API usage.
• Know whether the async operation completes directly or returns a second-phase object that must be fetched after wait.

Instructions

1. Identify whether the caller needs blocking execution, non-blocking polling, progress reporting, or two-phase result fetching.
2. In Python, use the two-stage pattern for result-bearing operations: call the _async method, wait() for a pending fetch object, then fetch() the final result.
3. For non-blocking Python waits, call wait(timeout_ns=0) first and handle None as "still running"; use a finite or infinite wait only when the workflow is ready to block.
4. In C, treat every enqueue result as asynchronous: check the enqueue status, wait on op_index, inspect operation errors, then fetch or destroy result handles as required.
5. When changing code, run the narrow async/status docs test or example that owns the snippet whenever practical.

Output Format

• For explanations, cite the relevant API names, source snippets, and caveats.
• For code changes, summarize the files changed, snippets affected, and validation run.

Scripts

This skill has no scripts.

Limitations

• The referenced snippets remain the source of truth; update or add tested snippets before documenting new API usage.

Overview

All ovrtx enqueue operations (open_usd, add_usd_reference, step, write_attribute, etc.) are internally asynchronous and stream-ordered. In Python, the default methods (e.g., open_usd, add_usd_reference, step) block until completion. The _async variants return Operation objects that support polling and custom timeouts.

In C, all enqueue calls return immediately with an ovrtx_op_id_t that can be polled or waited on.

Python

Non-blocking USD load

Source: tests/docs/python/test_support_api.py snippet doc-open-usd-async

The same polling pattern applies to open_usd_async and add_usd_reference_async — call op.wait(timeout_ns=0) to poll, or op.wait() to block.

Non-blocking step with two-stage timeout

Source: tests/docs/python/test_camera_sensors.py snippet doc-step-async

Infinite wait (default)

Source: examples/python/minimal/main.py snippet step

The synchronous step() is equivalent to step_async().wait().

step_async returns Operation[PendingFetch[RenderProductSetOutputs]]

In 0.3.0 the Python RendererResult return type was removed; step_async() now follows the standard two-phase Operation / PendingFetch lifecycle.

Source: tests/docs/python/test_camera_sensors.py snippet doc-step-async

Query progress on long-running operations

Operation.query_status() returns a point-in-time OperationStatus (state, progress, resource counters). Safe to call repeatedly while the op is PENDING; it becomes unavailable after wait() consumes the operation.

Source: tests/docs/python/test_base.py snippet doc-operation-status

C

Poll with zero timeout

Source: examples/c/minimal/main.cpp snippet load-usd-and-wait

The load snippet demonstrates polling with ovrtx_timeout_t{0}.

Poll loop with sleep

Source: examples/c/minimal/main.cpp snippet load-usd-and-wait

Block indefinitely

Source: examples/c/minimal/main.cpp snippet step-renderer

Uses ovrtx_timeout_infinite to block until completion.

Check for errors after wait

Source: examples/c/minimal/main.cpp snippet load-usd-and-wait

Check wait_result.num_error_ops after any ovrtx_wait_op call.

Query operation progress

For long-running operations (e.g., USD loading), call ovrtx_query_op_status(renderer, op_id, &status) to get progress and named resource counters, then ovrtx_release_op_status(renderer, &status) to release the returned pointers. Counter names are operation-dependent (e.g., "shaders", "textures", "materials" during USD loading). A total of 0 means the total is not yet known.

Source: examples/python/status-queries/main.py snippet wait-operation-with-status

Source: examples/c/status-queries/main.cpp snippet wait-operation-with-status-c

For the full pattern, use the status-queries skill.

Key Types / Functions

Python	C
Operation.wait(timeout_ns=None)	ovrtx_wait_op(renderer, op_id, timeout, &wait_result)
Operation.wait(timeout_ns=0)	ovrtx_wait_op with timeout.time_out_ns = 0
Operation.wait() → PendingFetch, then .fetch()	ovrtx_wait_op + per-op fetch call (ovrtx_fetch_results / ovrtx_fetch_read_result / ovrtx_fetch_query_results)
Operation.query_status() → OperationStatus	ovrtx_query_op_status(renderer, op_id, &status) + ovrtx_release_op_status(renderer, &status)
RuntimeError on failure	wait_result.num_error_ops > 0
Python copies status into dataclasses	ovrtx_release_op_status(renderer, &status) -- must call after each successful query

C timeout constants:

• ovrtx_timeout_t{0} -- non-blocking poll
• ovrtx_timeout_infinite -- block indefinitely
• ovrtx_timeout_t{5000000000} -- 5 seconds in nanoseconds

C wait result fields:

• error_op_ids / num_error_ops -- operations that errored since last wait
• lowest_pending_op_id -- 0 if all operations complete, nonzero if still pending

Troubleshooting

• In Python, Operation.wait() with no arguments blocks forever -- this is usually what you want.
• wait(timeout_ns=0) returns None on timeout, which is distinct from a successful result. For operations that return None on success (like reset_stage), use the Operation object's state to distinguish.
• In Python, call Operation.query_status() before Operation.wait() completes; completed operations release their wait-phase context.
• In C, ovrtx_wait_op waits for all operations up to and including the given op_id, not just that single operation.
• In C, check the ovrtx_wait_op return status before interpreting wait_result fields.
• In C, release each successful ovrtx_query_op_status() result with ovrtx_release_op_status().
• Error strings from ovrtx_get_last_op_error() are valid only until the next ovrtx_wait_op call on the same thread.

In Attached Mode (ovrtx 0.4+)

When ovrtx is attached to ovstage, the write side of the async model moves to ovstage's ordinal-keyed submit/observe: ovstage enqueues return an op_index immediately, and ordinal sealing (ovstage_advance_write_floor) is what makes writes observable. ovrtx observes the sealed state by passing the same ordinal to ovrtx_step_with_stage(..., ordinal) and ovrtx_update_from_stage(ordinal). See ovstage skills/cpu-ahead-gpu-async/SKILL.md for the authoritative async model.

See docs/core/ovstage_integration.rst, skills/update-0_3-0_4-c/SKILL.md and skills/update-0_3-0_4-python/SKILL.md.

References

• Use the > **Source:** directives in this skill to locate tested snippets before reusing API patterns.
• Keep related skills, docs, and snippets synchronized when changing the workflow.