updated and refactored

.gitignore

@@ -20,7 +20,6 @@ parts/
 sdist/
 var/
 wheels/
-pip-wheel-metadata/
 share/python-wheels/
 *.egg-info/
 .installed.cfg
@@ -50,6 +49,7 @@ coverage.xml
 *.py,cover
 .hypothesis/
 .pytest_cache/
+cover/
 
 # Translations
 *.mo
@@ -72,6 +72,7 @@ instance/
 docs/_build/
 
 # PyBuilder
+.pybuilder/
 target/
 
 # Jupyter Notebook
@@ -82,7 +83,9 @@ profile_default/
 ipython_config.py
 
 # pyenv
-.python-version
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
 
 # pipenv
 #   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
@@ -91,7 +94,31 @@ ipython_config.py
 #   install all needed dependencies.
 #Pipfile.lock
 
-# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+# UV
+#   Similar to Pipfile.lock, it is generally recommended to include uv.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#uv.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+#poetry.toml
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/latest/usage/project/#working-with-version-control
+.pdm.toml
+.pdm-python
+.pdm-build/
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
 __pypackages__/
 
 # Celery stuff
@@ -127,7 +154,42 @@ dmypy.json
 
 # Pyre type checker
 .pyre/
-data
 
-# Makefile install checker
-.install.stamp
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+.idea/
+
+# Abstra
+# Abstra is an AI-powered process automation framework.
+# Ignore directories containing user credentials, local state, and settings.
+# Learn more at https://abstra.io/docs
+.abstra/
+
+# Visual Studio Code
+#  Visual Studio Code specific template is maintained in a separate VisualStudioCode.gitignore
+#  that can be found at https://github.com/github/gitignore/blob/main/Global/VisualStudioCode.gitignore
+#  and can be added to the global gitignore or merged into this file. However, if you prefer,
+#  you could uncomment the following to ignore the entire vscode folder
+# .vscode/
+
+# Ruff stuff:
+.ruff_cache/
+
+# PyPI configuration file
+.pypirc
+
+# Cursor
+#  Cursor is an AI-powered code editor. `.cursorignore` specifies files/directories to
+#  exclude from AI features like autocomplete and code analysis. Recommended for sensitive data
+#  refer to https://docs.cursor.com/context/ignore-files
+.cursorignore
+.cursorindexingignore

README.md

@@ -4,15 +4,9 @@ This repository contains an example of how to use [Redis OM Python](https://gith
 
 ## Installing
 
-You install this project with Poetry.
+First, Install app's dependencies into your Python environment:
 
-First, [install Poetry](https://python-poetry.org/docs/#installation). You can probably pip install it into your Python environment:
-
-    $ pip install poetry
-
-Then install the example app's dependencies:
-
-    $ poetry install
+    $ pip install -r requirements.txt
 
 ## Running the Examples
 
@@ -22,23 +16,31 @@ To try the API, first, start the one of the servers.
 
 You can start the synchronous server like this, from your terminal:
 
-    $ poetry run uvicorn main:app
-
+```bash
+uvicorn main:app
+```
+
 Or the async server like this:
 
-    $ poetry run uvicorn async_main:app
+```bash
+uvicorn async_main:app
+```
 
 Then, in another shell, create a customer:
 
-    $ curl -X POST  "http://localhost:8000/customer" -H 'Content-Type: application/json' -d '{"first_name":"Andrew","last_name":"Brookins","email":"a@example.com","age":"38","join_date":"2020-01-02"}'
-    {"pk":"01FM2G8EP38AVMH7PMTAJ123TA","first_name":"Andrew","last_name":"Brookins","email":"a@example.com","join_date":"2020-01-02","age":38,"bio":""}
+```bash
+curl --location 'http://localhost:8000/customer' \
+--header 'Content-Type: application/json' \
+--data-raw '{"first_name":"Andrew","last_name":"Brookins","email":"a@example.com","age":"38","join_date":"2020-01-02"}'
+```
 
 Copy the "pk" value, which is the model's primary key, and make another request to get that customer:
 
-    $ curl "http://localhost:8000/customer/01FM2G8EP38AVMH7PMTAJ123TA"
-    {"pk":"01FM2G8EP38AVMH7PMTAJ123TA","first_name":"Andrew","last_name":"Brookins","email":"a@example.com","join_date":"2020-01-02","age":38,"bio":""}
+```bash
+curl --location 'http://localhost:8000/customer/01FM2G8EP38AVMH7PMTAJ123TA'
+```
 
 You can also get a list of all customer PKs:
-
-    $ curl "http://localhost:8000/customers"
-    {"customers":["01FM2G8EP38AVMH7PMTAJ123TA"]}
+```bash
+curl --location 'http://localhost:8000/customers'
+```

async_main.py

@@ -22,30 +22,27 @@
     $ curl "http://localhost:8000/customers"
     {"customers":["01FM2G8EP38AVMH7PMTAJ123TA"]}
 """
-
 import datetime
+from collections.abc import AsyncIterator
+from contextlib import asynccontextmanager
 from typing import Optional
 
-import aioredis
-
+from aredis_om.connections import get_redis_connection
+from aredis_om.model import HashModel, NotFoundError
 from fastapi import FastAPI, HTTPException
-from starlette.requests import Request
-from starlette.responses import Response
-
 from fastapi_cache import FastAPICache
 from fastapi_cache.backends.redis import RedisBackend
 from fastapi_cache.decorator import cache
-
 from pydantic import EmailStr
-
-from aredis_om.model import HashModel, NotFoundError
-from aredis_om.connections import get_redis_connection
+from redis import asyncio as aioredis
+from starlette.requests import Request
+from starlette.responses import Response
 
 # This Redis instance is tuned for durability.
-REDIS_DATA_URL = "redis://localhost:6380"
+REDIS_DATA_URL = "redis://localhost:6379"
 
 # This Redis instance is tuned for cache performance.
-REDIS_CACHE_URL = "redis://localhost:6381"
+REDIS_CACHE_URL = "redis://localhost:6379"
 
 
 class Customer(HashModel):
@@ -63,7 +60,14 @@ class Meta:
         database = get_redis_connection(url=REDIS_DATA_URL, decode_responses=True)
 
 
-app = FastAPI()
+@asynccontextmanager
+async def lifespan(_: FastAPI) -> AsyncIterator[None]:
+    redis = aioredis.from_url(REDIS_CACHE_URL)
+    FastAPICache.init(RedisBackend(redis), prefix="fastapi-cache")
+    yield
+
+
+app = FastAPI(lifespan=lifespan)
 
 
 @app.post("/customer")
@@ -86,9 +90,3 @@ async def get_customer(pk: str, request: Request, response: Response):
         return await Customer.get(pk)
     except NotFoundError:
         raise HTTPException(status_code=404, detail="Customer not found")
-
-
-@app.on_event("startup")
-async def startup():
-    r = aioredis.from_url(REDIS_CACHE_URL, encoding="utf8", decode_responses=True)
-    FastAPICache.init(RedisBackend(r), prefix="fastapi-cache")

docker-compose.yml

@@ -0,0 +1,12 @@
+version: "3.9"
+services:
+  redis:
+    container_name: redis_om_python_flask_starter
+    image: "redis/redis-stack:latest"
+    ports:
+      - 6379:6379
+      - 8001:8001
+    deploy:
+      replicas: 1
+      restart_policy:
+        condition: on-failure

main.py

@@ -22,24 +22,21 @@
     $ curl "http://localhost:8000/customers"
     {"customers":["01FM2G8EP38AVMH7PMTAJ123TA"]}
 """
-
 import datetime
+from collections.abc import AsyncIterator
+from contextlib import asynccontextmanager
 from typing import Optional
 
-import aioredis
-
 from fastapi import FastAPI, HTTPException
-from starlette.requests import Request
-from starlette.responses import Response
-
 from fastapi_cache import FastAPICache
 from fastapi_cache.backends.redis import RedisBackend
 from fastapi_cache.decorator import cache
-
 from pydantic import EmailStr
-
-from redis_om.model import HashModel, NotFoundError
+from redis import asyncio as aioredis
 from redis_om.connections import get_redis_connection
+from redis_om.model import HashModel, NotFoundError
+from starlette.requests import Request
+from starlette.responses import Response
 
 # This Redis instance is tuned for durability.
 REDIS_DATA_URL = "redis://localhost:6380"
@@ -63,7 +60,14 @@ class Meta:
         database = get_redis_connection(url=REDIS_DATA_URL, decode_responses=True)
 
 
-app = FastAPI()
+@asynccontextmanager
+async def lifespan(_: FastAPI) -> AsyncIterator[None]:
+    redis = aioredis.from_url(REDIS_CACHE_URL)
+    FastAPICache.init(RedisBackend(redis), prefix="fastapi-cache")
+    yield
+
+
+app = FastAPI(lifespan=lifespan)
 
 
 @app.post("/customer")
@@ -86,9 +90,3 @@ async def get_customer(pk: str, request: Request, response: Response):
         return Customer.get(pk)
     except NotFoundError:
         raise HTTPException(status_code=404, detail="Customer not found")
-
-
-@app.on_event("startup")
-async def startup():
-    r = aioredis.from_url(REDIS_CACHE_URL, encoding="utf8", decode_responses=True)
-    FastAPICache.init(RedisBackend(r), prefix="fastapi-cache")