vastai-sdk-patterns

Owned Vast.ai Python SDK Lifecycles

Overview

Use the highest-level client that preserves the required control. Keep resource identity and cleanup ownership explicit, normalize provider response variants at one boundary, and never hide a billable instance behind an unbounded retry.

Prerequisites

• Chosen high-level, synchronous, asynchronous, or Serverless client surface
• Typed internal model for offers, instances, terminal states, and provider errors
• Idempotency, timeout, test-double, and cleanup design

Instructions

Step 1: Select one client boundary

Use VastAI for broad CLI-equivalent operations, SyncClient for typed synchronous instance control, AsyncClient inside an async context, or Serverless for endpoint inference.

Step 2: Normalize responses once

Map provider dictionaries and error shapes into a small internal result type. Preserve offer ID, contract ID, status, price, and raw error code for diagnosis.

Step 3: Separate plan from mutation

Search and score offers without creating resources. Require an approved plan object before calling create, update, destroy, or credit operations.

Step 4: Own the lifecycle

Persist the returned instance ID immediately, apply a monotonic deadline, classify terminal failure states, and place destroy or handoff in an explicit finalizer.

Step 5: Test failure boundaries

Cover 401, 403, 429, malformed responses, create-without-ID, readiness timeout, and cleanup failure using local fakes.

Step 6: Expose a redacted receipt

Return normalized decisions and state transitions; never return the API key or full environment.

Authentication

Construct clients from VAST_API_KEY or the approved local configuration. Do not pass keys as literals, serialize client objects, or let provider credentials cross into workload payloads.

Tool Discipline

Use Read and Grep to inspect manifests, configuration, provider output, and existing tests before proposing a mutation. Use Write or Edit only for the approved plan, implementation, test, or redacted receipt; do not create, update, destroy, or fund Vast.ai resources without explicit operator approval.

Output

• Client-selection decision and typed adapter contract
• Bounded lifecycle implementation with local failure tests
• Redacted mutation and cleanup receipt

Return client type, package version, plan identity, provider resource IDs, terminal outcome, and cleanup owner.

Examples

An async job runner uses AsyncClient as a context manager, records instance.id before waiting, cancels on its deadline, and destroys the instance in a tested finalizer.

Error Handling

Resources

• First-party source notes
• Official SDK skill
• Python SDK reference
• API rate limits and errors