docs: large projects documentation/tutorial added

docs/large_project_structure.md

@@ -0,0 +1,187 @@
+If you have a large project with maybe multiple `streams` we recommend the following project structure:
+
+```
+├── my-project
+│   ├── my_project
+│   │   ├── __init__.py
+│   │   ├── app.py
+│   │   ├── resources.py
+│   │   ├── streams.py
+│   │   └── streams_roster.py
+│   │── tests
+│   │   ├── __init__.py
+│   │   ├── conftest.py
+│   │── pyproject.toml
+│   │── README.md
+```
+
+- The file `my_project/resouces.py` contains the creation of the `StreamEngine`
+- The file `my_project/app.py` contains the entrypoint of your program
+- The file `my_project/streams.py` contains all the `Streams`
+
+A full project example ready to use can be found [here](https://github.com/kpn/kstreams/tree/master/examples/recommended-worker-app)
+
+!!! note
+    This is just a recommendation, there are many ways to structure your project
+
+## Resources
+
+This python module contains any global resource that will be used later in the application, for example `DB connections` or the `StreamEngine`. Typically we will have the following:
+
+```python
+from kstreams import backends, create_engine
+
+backend = backends.Kafka(
+    bootstrap_servers=["localhost:9092"],
+    security_protocol=backends.kafka.SecurityProtocol.PLAINTEXT,
+)
+
+stream_engine = kstreams.create_engine(
+    title="my-stream-engine",
+    backend=backend,
+)
+```
+
+Then later `stream_engine` can be reused to start the application.
+
+## Streams
+
+When starting your project you can have `N` number of `Streams` with its `handler`, let's say in `streams.py` module. All of the `Streams` will run next to each other and because they are in the same project it is really easy to share common code. However, this comes with a downside of `scalability` as it is not possible to take the advantages of `kafka` and scale up `Streams` individually. In next versions the `StreamEngine` will be able to select which `Stream/s` should run to mitigate this issue. Typically, your `streams.py` will look like:
+
+```python
+from kstreams import Stream
+
+from .streams_roster import stream_roster, stream_two_roster
+
+
+my_stream = Stream(
+    "local--hello-world",
+    func=stream_roster,
+    config={
+        "group_id": "example-group",
+    },
+    ...
+)
+
+my_second_stream = Stream(
+    "local--hello-world-2",
+    func=stream_two_roster,
+    config={
+        "group_id": "example-group-2",
+    },
+    ...
+)
+
+...
+```
+
+and `streams_roster.py` contains all the `coroutines` that will be executed when an event arrives
+
+```python
+import logging
+
+from kstreams import ConsumerRecord, Send, Stream
+
+logger = logging.getLogger(__name__)
+
+
+async def stream_roster(cr: ConsumerRecord, send: Send) -> None:
+    logger.info(f"showing bytes: {cr.value}")
+    value = f"Event confirmed. {cr.value}"
+
+    await send(
+        "another-topic-to-wink",
+        value=value.encode(),
+        key="1",
+    )
+
+
+async def stream_two_roster(cr: ConsumerRecord, send: Send, stream: Stream) -> None:
+    ...
+```
+
+It is worth to note three things:
+
+- We separate the `Stream` with its `coroutine` to be able to test the `business logic` easily
+- If you need to produce events inside a `Stream` add the `send coroutine` using [dependency-injection](https://kpn.github.io/kstreams/stream/#dependency-injection)
+- We are not using `StreamEngine` at all to avoid `circular import` errors
+
+## Application
+
+The `entrypoint` is usually in `app.py`. The module contains the import of `stream_engine`, it's `hooks` and the `streams` to be added to the `engine`:
+
+```python
+import aiorun
+import asyncio
+import logging
+
+from kstreams.stream_utils import StreamErrorPolicy
+
+from .resources import stream_engine
+from .streams import my_stream, my_second_stream
+
+logger = logging.getLogger(__name__)
+
+
+# hooks
+@stream_engine.after_startup
+async def init_events():
+    await stream_engine.send("local--hello-world", value="Hi Kstreams!")
+
+
+# add the stream to the stream_engine
+stream_engine.add_stream(my_stream, error_policy=StreamErrorPolicy.RESTART)
+stream_engine.add_stream(my_second_stream, error_policy=StreamErrorPolicy.STOP_ENGINE)
+
+
+async def start():
+    await stream_engine.start()
+
+
+async def stop(loop: asyncio.AbstractEventLoop):
+    await stream_engine.stop()
+
+
+def main():
+    logging.basicConfig(level=logging.INFO)
+    logger.info("Starting application...")
+    aiorun.run(start(), stop_on_unhandled_errors=True, shutdown_callback=stop)
+```
+
+To run it we recommend [aiorun](https://github.com/cjrh/aiorun). It can be also run with `asyncio` directly but `aiorun` does all the boilerplate for us.
+
+## Tests
+
+In this module you test your application using the `TestStreamClient`, usually provided as a `fixture` thanks to `pytest`. The package `pytest-asyncio` is also needed 
+to test `async` code.
+
+```python
+# conftest.py
+import pytest
+
+from kstreams.test_utils import TestStreamClient
+
+from my_project.resources import stream_engine
+
+
+@pytest.fixture
+def stream_client():
+    return TestStreamClient(stream_engine=stream_engine)
+```
+
+then you can test your streams
+
+```python
+# test_app.py
+import pytest
+
+
+@pytest.mark.asyncio
+async def test_my_stream(stream_client):
+    topic = "local--hello-world"  # Use the same topic as the stream
+    event = b'{"message": "Hello world!"}'
+
+    async with stream_client:
+        metadata = await stream_client.send(topic, value=event, key="1")
+        assert metadata.topic == topic
+```

examples/recommended-worker-app/recommended_worker_app/app.py

@@ -4,11 +4,11 @@
 import aiorun
 
 from .resources import stream_engine
-from .streams import consume
+from .streams import my_stream
 
 logger = logging.getLogger(__name__)
 
-stream_engine.add_stream(consume)
+stream_engine.add_stream(my_stream)
 
 
 async def start():

examples/recommended-worker-app/recommended_worker_app/resources.py

@@ -1,3 +1,11 @@
-import kstreams
+from kstreams import backends, create_engine
 
-stream_engine = kstreams.create_engine(title="my-stream-engine")
+backend = backends.Kafka(
+    bootstrap_servers=["localhost:9092"],
+    security_protocol=backends.kafka.SecurityProtocol.PLAINTEXT,
+)
+
+stream_engine = create_engine(
+    title="my-stream-engine",
+    backend=backend,
+)

examples/recommended-worker-app/recommended_worker_app/streams.py

@@ -1,17 +1,11 @@
-import logging
+from kstreams import Stream
 
-from kstreams import ConsumerRecord, Send, stream
+from .streams_roster import stream_roster
 
-logger = logging.getLogger(__name__)
-
-
-@stream("local--hello-world", group_id="example-group")
-async def consume(cr: ConsumerRecord, send: Send) -> None:
-    logger.info(f"showing bytes: {cr.value}")
-    value = f"Event confirmed. {cr.value}"
-
-    await send(
-        "local--kstreams",
-        value=value.encode(),
-        key="1",
-    )
+my_stream = Stream(
+    "local--hello-world",
+    func=stream_roster,
+    config={
+        "group_id": "example-group",
+    },
+)

examples/recommended-worker-app/recommended_worker_app/streams_roster.py

@@ -0,0 +1,16 @@
+import logging
+
+from kstreams import ConsumerRecord, Send
+
+logger = logging.getLogger(__name__)
+
+
+async def stream_roster(cr: ConsumerRecord, send: Send) -> None:
+    logger.info(f"showing bytes: {cr.value}")
+    value = f"Event confirmed. {cr.value}"
+
+    await send(
+        "local--kstreams",
+        value=value.encode(),
+        key="1",
+    )

mkdocs.yml

@@ -36,6 +36,7 @@ nav:
   - Testing: 'test_client.md'
   - Middleware: 'middleware.md'
   - Utils: 'utils.md'
+  - Large Projects: 'large_project_structure.md'
 
 markdown_extensions:
   - pymdownx.highlight