feat(examples): reduce streaming example

packages/pynumaflow-lite/manifests/reducestream/Dockerfile

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+FROM python:3.11-slim-bullseye AS builder
+
+ENV PYTHONFAULTHANDLER=1 \
+  PYTHONUNBUFFERED=1 \
+  PYTHONHASHSEED=random \
+  PIP_NO_CACHE_DIR=on \
+  PIP_DISABLE_PIP_VERSION_CHECK=on \
+  PIP_DEFAULT_TIMEOUT=100 \
+  POETRY_HOME="/opt/poetry" \
+  POETRY_VIRTUALENVS_IN_PROJECT=true \
+  POETRY_NO_INTERACTION=1 \
+  PYSETUP_PATH="/opt/pysetup"
+
+ENV PATH="$POETRY_HOME/bin:$PATH"
+
+RUN apt-get update \
+    && apt-get install --no-install-recommends -y \
+        curl \
+        wget \
+        # deps for building python deps
+        build-essential \
+    && apt-get install -y git \
+    && apt-get clean && rm -rf /var/lib/apt/lists/* \
+    && curl -sSL https://install.python-poetry.org | python3 -
+
+FROM builder AS udf
+
+WORKDIR $PYSETUP_PATH
+COPY ./ ./
+
+# NOTE: place the built wheel in this directory before building the image
+RUN pip install $PYSETUP_PATH/pynumaflow_lite-0.1.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
+
+RUN poetry lock
+RUN poetry install --no-cache --no-root && \
+    rm -rf ~/.cache/pypoetry/
+
+CMD ["python", "reducestream_counter.py"]
+

packages/pynumaflow-lite/manifests/reducestream/README.md

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+To create the `wheel` file, refer [root](../../README.md)
+
+## HOWTO build Image
+
+```bash
+docker build . -t quay.io/numaio/numaflow/pynumaflow-lite-reducestream-counter:v1 --load
+```
+
+Load it now to `k3d`
+
+### `k3d`
+
+```bash
+k3d image import quay.io/numaio/numaflow/pynumaflow-lite-reducestream-counter:v1
+```
+
+### Minikube
+
+```bash
+minikube image load quay.io/numaio/numaflow/pynumaflow-lite-reducestream-counter:v1
+```
+
+#### Delete image from minikube
+
+`minikube` doesn't like pushing the same image over, delete and load if you are using
+the same tag.
+
+```bash
+minikube image rm quay.io/numaio/numaflow/pynumaflow-lite-reducestream-counter:v1
+```
+
+## Run the pipeline
+
+```bash
+kubectl apply -f pipeline.yaml
+```
+
+

packages/pynumaflow-lite/manifests/reducestream/pipeline.yaml

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+apiVersion: numaflow.numaproj.io/v1alpha1
+kind: Pipeline
+metadata:
+  name: reducestream-counter
+spec:
+  vertices:
+    - name: in
+      source:
+        # A self data generating source
+        generator:
+          rpu: 10
+          duration: 1s
+    - name: reducestream
+      partitions: 1
+      udf:
+        container:
+          image: quay.io/numaio/numaflow/pynumaflow-lite-reducestream-counter:v1
+          imagePullPolicy: Never
+        groupBy:
+          window:
+            fixed:
+              length: 10s
+              streaming: true
+          keyed: true
+          storage:
+            emptyDir: { }
+    - name: sink
+      scale:
+        min: 1
+      sink:
+        log: { }
+  edges:
+    - from: in
+      to: reducestream
+    - from: reducestream
+      to: sink
+

packages/pynumaflow-lite/manifests/reducestream/pyproject.toml

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+[project]
+name = "reducestream-counter"
+version = "0.1.0"
+description = "Reduce streaming counter example using pynumaflow-lite"
+authors = [
+    { name = "Vigith Maurice", email = "vigith@gmail.com" }
+]
+readme = "README.md"
+requires-python = ">=3.11"
+dependencies = [
+]
+
+[build-system]
+requires = ["poetry-core>=2.0.0,<3.0.0"]
+build-backend = "poetry.core.masonry.api"
+

packages/pynumaflow-lite/manifests/reducestream/reducestream_counter.py

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+"""
+Reduce Streaming Counter Example
+
+This example demonstrates how to use ReduceStreamer to emit intermediate results
+as data arrives, rather than waiting until all data is received.
+
+The counter increments for each datum and emits a message every 10 items,
+plus a final message at the end.
+"""
+import asyncio
+import signal
+from collections.abc import AsyncIterable, AsyncIterator
+
+from pynumaflow_lite import reducestreamer
+
+
+class ReduceCounter(reducestreamer.ReduceStreamer):
+    """
+    A reduce streaming counter that emits intermediate results.
+
+    This demonstrates the key difference from regular Reducer:
+    - Regular Reducer: waits for all data, then returns Messages
+    - ReduceStreamer: yields Message objects incrementally as an async iterator
+    """
+
+    def __init__(self, initial: int = 0) -> None:
+        self.counter = initial
+
+    async def handler(
+        self,
+        keys: list[str],
+        datums: AsyncIterable[reducestreamer.Datum],
+        md: reducestreamer.Metadata,
+    ) -> AsyncIterator[reducestreamer.Message]:
+        """
+        Process datums and yield messages incrementally.
+
+        Args:
+            keys: List of keys for this window
+            datums: Async iterable of incoming data
+            md: Metadata containing window information
+
+        Yields:
+            Message objects to send to the next vertex
+        """
+        iw = md.interval_window
+        print(f"Handler started for keys={keys}, window=[{iw.start}, {iw.end}]")
+
+        async for _ in datums:
+            self.counter += 1
+
+            # Emit intermediate result every 10 items
+            if self.counter % 10 == 0:
+                msg = (
+                    f"counter:{self.counter} "
+                    f"interval_window_start:{iw.start} "
+                    f"interval_window_end:{iw.end}"
+                ).encode()
+                print(f"Yielding intermediate result: counter={self.counter}")
+                # Early release of data - this is the key feature of reduce streaming!
+                yield reducestreamer.Message(msg, keys=keys)
+
+        # Emit final result
+        msg = (
+            f"counter:{self.counter} (FINAL) "
+            f"interval_window_start:{iw.start} "
+            f"interval_window_end:{iw.end}"
+        ).encode()
+        print(f"Yielding final result: counter={self.counter}")
+        yield reducestreamer.Message(msg, keys=keys)
+
+
+# Optional: ensure default signal handlers are in place so asyncio.run can handle them cleanly.
+signal.signal(signal.SIGINT, signal.default_int_handler)
+try:
+    signal.signal(signal.SIGTERM, signal.SIG_DFL)
+except AttributeError:
+    pass
+
+
+async def start(creator: type, init_args: tuple):
+    """Start the reduce stream server."""
+    sock_file = "/var/run/numaflow/reducestream.sock"
+    server_info_file = "/var/run/numaflow/reducestreamer-server-info"
+    server = reducestreamer.ReduceStreamAsyncServer(sock_file, server_info_file)
+
+    loop = asyncio.get_running_loop()
+    try:
+        loop.add_signal_handler(signal.SIGINT, lambda: server.stop())
+        loop.add_signal_handler(signal.SIGTERM, lambda: server.stop())
+    except (NotImplementedError, RuntimeError):
+        pass
+
+    try:
+        print("Starting Reduce Stream Counter Server...")
+        await server.start(creator, init_args)
+        print("Shutting down gracefully...")
+    except asyncio.CancelledError:
+        try:
+            server.stop()
+        except Exception:
+            pass
+        return
+
+
+if __name__ == "__main__":
+    asyncio.run(start(ReduceCounter, (0,)))
+