docs: hello_world python binding example #2083
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WalkthroughThis change adds a new example under Changes
Sequence Diagram(s)sequenceDiagram
participant Client
participant Runtime
participant Backend
Client->>Runtime: Register worker
Runtime->>Backend: Start service with endpoint
Client->>Backend: Send request (comma-separated words)
loop For each word
Backend-->>Client: Stream greeting ("Hello, <word>!")
end
Estimated code review effort🎯 2 (Simple) | ⏱️ ~8 minutes Poem
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Actionable comments posted: 1
🧹 Nitpick comments (3)
examples/runtime/hello_world/README.md (3)
24-31: Add language specification to code block.The ASCII art diagram should specify a language for proper rendering.
-``` +```text Client (dynamo_worker) │ ▼ ┌─────────────┐ │ Backend │ Dynamo endpoint (/generate) └─────────────┘ -``` +```
55-56: Fix unordered list indentation.The list items should not be indented as they are top-level items.
- - **etcd**: A distributed key-value store used for service discovery and metadata storage - - **NATS**: A high-performance message broker for inter-component communication +- **etcd**: A distributed key-value store used for service discovery and metadata storage +- **NATS**: A high-performance message broker for inter-component communication
86-91: Add language specification to output example.The expected output code block should specify the language for better rendering.
-``` +```text Hello world! Hello sun! Hello moon! Hello star! -``` +```
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Configuration used: .coderabbit.yaml
Review profile: CHILL
Plan: Pro
📒 Files selected for processing (3)
examples/runtime/hello_world/README.md(1 hunks)examples/runtime/hello_world/client.py(1 hunks)examples/runtime/hello_world/hello_world.py(1 hunks)
🧰 Additional context used
🧠 Learnings (3)
examples/runtime/hello_world/client.py (1)
Learnt from: nnshah1
PR: #1444
File: tests/fault_tolerance/utils/metrics.py:30-32
Timestamp: 2025-07-01T13:55:03.940Z
Learning: The @dynamo_worker() decorator in the dynamo codebase returns a wrapper that automatically injects the runtime parameter before calling the wrapped function. This means callers only need to provide the non-runtime parameters, while the decorator handles injecting the runtime argument automatically. For example, a function with signature async def get_metrics(runtime, log_dir) decorated with @dynamo_worker() can be called as get_metrics(log_dir) because the decorator wrapper injects the runtime parameter.
examples/runtime/hello_world/README.md (1)
Learnt from: nnshah1
PR: #1444
File: tests/fault_tolerance/utils/metrics.py:30-32
Timestamp: 2025-07-01T13:55:03.940Z
Learning: The @dynamo_worker() decorator in the dynamo codebase returns a wrapper that automatically injects the runtime parameter before calling the wrapped function. This means callers only need to provide the non-runtime parameters, while the decorator handles injecting the runtime argument automatically. For example, a function with signature async def get_metrics(runtime, log_dir) decorated with @dynamo_worker() can be called as get_metrics(log_dir) because the decorator wrapper injects the runtime parameter.
examples/runtime/hello_world/hello_world.py (1)
Learnt from: nnshah1
PR: #1444
File: tests/fault_tolerance/utils/metrics.py:30-32
Timestamp: 2025-07-01T13:55:03.940Z
Learning: The @dynamo_worker() decorator in the dynamo codebase returns a wrapper that automatically injects the runtime parameter before calling the wrapped function. This means callers only need to provide the non-runtime parameters, while the decorator handles injecting the runtime argument automatically. For example, a function with signature async def get_metrics(runtime, log_dir) decorated with @dynamo_worker() can be called as get_metrics(log_dir) because the decorator wrapper injects the runtime parameter.
🪛 LanguageTool
examples/runtime/hello_world/README.md
[style] ~36-~36: Consider using “who” when you are referring to a person instead of an object.
Context: ...ated word - Client: A Dynamo worker that connects to and sends requests to the b...
(THAT_WHO)
[style] ~98-~98: Consider using “who” when you are referring to a person instead of an object.
Context: ...eetings - worker: A dynamo worker that sets up the service, creates the endpoi...
(THAT_WHO)
[style] ~102-~102: Consider using “who” when you are referring to a person instead of an object.
Context: ...t.py) - **worker`**: A dynamo worker that connects to the backend service and pro...
(THAT_WHO)
🪛 markdownlint-cli2 (0.17.2)
examples/runtime/hello_world/README.md
24-24: Fenced code blocks should have a language specified
(MD040, fenced-code-language)
55-55: Unordered list indentation
Expected: 0; Actual: 1
(MD007, ul-indent)
56-56: Unordered list indentation
Expected: 0; Actual: 1
(MD007, ul-indent)
86-86: Fenced code blocks should have a language specified
(MD040, fenced-code-language)
🔇 Additional comments (5)
examples/runtime/hello_world/hello_world.py (2)
37-53: LGTM! Proper implementation of Dynamo worker pattern.The worker function correctly demonstrates the Dynamo distributed runtime patterns:
- Creates namespace and component structure
- Properly initializes the service
- Serves the endpoint with the streaming function
- Good logging for debugging
55-57: LGTM! Proper async main entry point.Good use of uvloop for performance optimization and proper async execution of the worker.
examples/runtime/hello_world/client.py (2)
23-38: LGTM! Clean client implementation demonstrating proper Dynamo patterns.The client code properly demonstrates:
- Correct use of
@dynamo_worker()decorator- Proper service endpoint resolution
- Client creation and readiness waiting
- Async streaming consumption
The implementation is clean and follows Dynamo best practices.
40-42: LGTM! Consistent async setup with backend.Proper use of uvloop and async execution pattern matching the backend service.
examples/runtime/hello_world/README.md (1)
18-103: LGTM! Comprehensive and well-structured documentation.The README provides excellent documentation covering:
- Clear architecture explanation
- Detailed component descriptions
- Prerequisites and setup instructions
- Running instructions with expected output
- Code structure breakdown
The documentation effectively guides users through understanding and running the example.
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I like it. Simple. Thanks!
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