Release v1.1.0

.env.example

@@ -1,3 +1,3 @@
-IS_DEBUG = False
-API_KEY = sample_api_key
-DEFAULT_MODEL_PATH=./sample_model/lin_reg_california_housing_model.joblib
+IS_DEBUG=False
+API_KEY=sample_api_key
+DEFAULT_MODEL_PATH=./sample_model/lin_reg_california_housing_model.joblib

.flake8

@@ -0,0 +1,122 @@
+[flake8]
+
+################### PROGRAM ################################
+
+# Specify the number of subprocesses that Flake8 will use to run checks in parallel.
+jobs = auto
+
+
+################### OUTPUT #################################
+
+########## Verbosity ##########
+
+# Increase the verbosity of Flake8’s output.
+verbose = 0
+# Decrease the verbosity of Flake8’s output.
+quiet = 0
+
+
+########## Formatting ##########
+
+# Select the formatter used to display errors to the user.
+format = default
+
+# Print the total number of errors.
+count = True
+# Print the source code generating the error/warning in question.
+show-source = True
+# Count the number of occurrences of each error/warning code and print a report.
+statistics = True
+
+
+########## Targets ##########
+
+# Redirect all output to the specified file.
+output-file = .flake8.log
+# Also print output to stdout if output-file has been configured.
+tee = True
+
+
+################### FILE PATTERNS ##########################
+
+# Provide a comma-separated list of glob patterns to exclude from checks.
+exclude =
+    # git folder
+    .git,
+    # python cache
+    __pycache__,
+    # pytest cache
+    .pytest_cache,
+    # mypy cache
+    .mypy_cache
+# Provide a comma-separate list of glob patterns to include for checks.
+filename =
+    *.py
+
+
+################### LINTING ################################
+
+########## Environment ##########
+
+# Provide a custom list of builtin functions, objects, names, etc.
+builtins =
+
+
+########## Options ##########
+
+# Report all errors, even if it is on the same line as a `# NOQA` comment.
+disable-noqa = False
+
+# Set the maximum length that any line (with some exceptions) may be.
+max-line-length = 88
+# Set the maximum allowed McCabe complexity value for a block of code.
+max-complexity = 10
+# Toggle whether pycodestyle should enforce matching the indentation of the opening bracket’s line.
+# incluences E131 and E133
+hang-closing = True
+
+
+########## Rules ##########
+
+# ERROR CODES
+#
+# E/W  - PEP8 errors/warnings (pycodestyle)
+# F    - linting errors (pyflakes)
+# C    - McCabe complexity error (mccabe)
+#
+# E133 - closing bracket is missing indentation (conflicts with black)
+# E203 - whitespace before ‘:’ (conflicts with black)
+# W503 - line break before binary operator
+# F401 - module imported but unused
+# F403 - ‘from module import *’ used; unable to detect undefined names
+#
+
+# Specify a list of codes to ignore.
+ignore =
+    E133,
+    E203,
+    W503
+# Specify the list of error codes you wish Flake8 to report.
+select =
+    E,
+    W,
+    F,
+    C
+# Specify a list of mappings of files and the codes that should be ignored for the entirety of the
+# file.
+per-file-ignores =
+    __init__.py:F401,F403
+
+# Enable off-by-default extensions.
+enable-extensions =
+
+
+########## Docstring ##########
+
+# Enable PyFlakes syntax checking of doctests in docstrings.
+# doctests = True
+
+# Specify which files are checked by PyFlakes for doctest syntax.
+include-in-doctest =
+# Specify which files are not to be checked by PyFlakes for doctest syntax.
+exclude-in-doctest =

.gitignore

@@ -33,6 +33,7 @@ wheels/
 #  before PyInstaller builds the exe, so as to inject date/other infos into it.
 *.manifest
 *.spec
+.env
 
 # Installer logs
 pip-log.txt
@@ -41,6 +42,7 @@ pip-delete-this-directory.txt
 # Unit test / coverage reports
 htmlcov/
 htmlcov-py36/
+htmlcov-py311/
 .tox/
 .coverage
 .coverage.*

README.md

@@ -8,12 +8,14 @@ To experiment and get a feeling on how to use this skeleton, a sample regression
 
 ## Requirements
 
-Python 3.6+
+- Python 3.11+
+- Poetry
 
 ## Installation
 Install the required packages in your local environment (ideally virtualenv, conda, etc.).
+
 ```bash
-pip install -r requirements
+poetry install
 ``` 
 
 
@@ -23,36 +25,61 @@ pip install -r requirements
 
 2. In the `.env` file configure the `API_KEY` entry. The key is used for authenticating our API. <br>
    A sample API key can be generated using Python REPL:
+
 ```python
 import uuid
 print(str(uuid.uuid4()))
 ```
 
 ## Run It
 
-1. Start your  app with: 
+1. Start your  app with:
+
 ```bash
+set -a
+source .env
+set +a
 uvicorn fastapi_skeleton.main:app
 ```
 
 2. Go to [http://localhost:8000/docs](http://localhost:8000/docs).
-
 3. Click `Authorize` and enter the API key as created in the Setup step.
-![Authroization](./docs/authorize.png)
-
+![Authroization](./docs/authorize.png) 
 4. You can use the sample payload from the `docs/sample_payload.json` file when trying out the house price prediction model using the API.
    ![Prediction with example payload](./docs/sample_payload.png)
 
-## Run Tests
+## Linting
+
+This skeleton code uses isort, mypy, flake, black, bandit for linting, formatting and static analysis.
+
+Run linting with:
 
-If you're not using `tox`, please install with:
 ```bash
-pip install tox
+./scripts/linting.sh
 ```
 
-Run your tests with: 
+## Run Tests
+
+Run your tests with:
+
 ```bash
-tox
+./scripts/test.sh
 ```
 
-This runs tests and coverage for Python 3.6 and Flake8, Autopep8, Bandit.
+This runs tests and coverage for Python 3.11 and Flake8, Autopep8, Bandit.
+
+
+## Changelog
+
+v.1.0.0 - Initial release
+
+- Base functionality for using FastAPI to serve ML models.
+- Full test coverage 
+
+v.1.1.0 - Update to Python 3.11, FastAPI 0.108.0
+
+- Updated to Python 3.11
+- Added linting script
+- Updated to pydantic 2.x
+- Added poetry as package manager
+

fastapi_skeleton/api/routes/heartbeat.py

@@ -1,4 +1,3 @@
-
 from fastapi import APIRouter
 
 from fastapi_skeleton.models.heartbeat import HearbeatResult

fastapi_skeleton/api/routes/prediction.py

@@ -12,10 +12,9 @@
 @router.post("/predict", response_model=HousePredictionResult, name="predict")
 def post_predict(
     request: Request,
-    authenticated: bool = Depends(security.validate_request),
-    block_data: HousePredictionPayload = None
+    block_data: HousePredictionPayload,
+    _: bool = Depends(security.validate_request),
 ) -> HousePredictionResult:
-
     model: HousePriceModel = request.app.state.model
     prediction: HousePredictionResult = model.predict(block_data)
 

fastapi_skeleton/api/routes/router.py

@@ -1,10 +1,7 @@
-
-
 from fastapi import APIRouter
 
 from fastapi_skeleton.api.routes import heartbeat, prediction
 
 api_router = APIRouter()
 api_router.include_router(heartbeat.router, tags=["health"], prefix="/health")
-api_router.include_router(prediction.router, tags=[
-                          "prediction"], prefix="/model")
+api_router.include_router(prediction.router, tags=["prediction"], prefix="/model")

fastapi_skeleton/core/config.py

@@ -1,5 +1,3 @@
-
-
 from starlette.config import Config
 from starlette.datastructures import Secret
 

fastapi_skeleton/core/event_handlers.py

@@ -1,5 +1,3 @@
-
-
 from typing import Callable
 
 from fastapi import FastAPI
@@ -23,11 +21,13 @@ def start_app_handler(app: FastAPI) -> Callable:
     def startup() -> None:
         logger.info("Running app start handler.")
         _startup_model(app)
+
     return startup
 
 
 def stop_app_handler(app: FastAPI) -> Callable:
     def shutdown() -> None:
         logger.info("Running app shutdown handler.")
         _shutdown_model(app)
+
     return shutdown

fastapi_skeleton/core/security.py

@@ -1,5 +1,3 @@
-
-
 import secrets
 from typing import Optional
 

fastapi_skeleton/main.py

@@ -1,12 +1,8 @@
-
-
 from fastapi import FastAPI
 
 from fastapi_skeleton.api.routes.router import api_router
-from fastapi_skeleton.core.config import (API_PREFIX, APP_NAME, APP_VERSION,
-                                          IS_DEBUG)
-from fastapi_skeleton.core.event_handlers import (start_app_handler,
-                                                  stop_app_handler)
+from fastapi_skeleton.core.config import API_PREFIX, APP_NAME, APP_VERSION, IS_DEBUG
+from fastapi_skeleton.core.event_handlers import start_app_handler, stop_app_handler
 
 
 def get_app() -> FastAPI:

fastapi_skeleton/models/heartbeat.py

@@ -1,5 +1,3 @@
-
-
 from pydantic import BaseModel
 
 

fastapi_skeleton/models/payload.py

@@ -1,5 +1,5 @@
-
 from typing import List
+
 from pydantic import BaseModel
 
 
@@ -23,4 +23,5 @@ def payload_to_list(hpp: HousePredictionPayload) -> List:
         hpp.population_per_block,
         hpp.average_house_occupancy,
         hpp.block_latitude,
-        hpp.block_longitude]
+        hpp.block_longitude,
+    ]

fastapi_skeleton/models/prediction.py

@@ -1,5 +1,3 @@
-
-
 from pydantic import BaseModel
 
 

fastapi_skeleton/services/models.py

@@ -1,29 +1,23 @@
-
-
-from typing import List
-
 import joblib
 import numpy as np
 from loguru import logger
 
 from fastapi_skeleton.core.messages import NO_VALID_PAYLOAD
-from fastapi_skeleton.models.payload import (HousePredictionPayload,
-                                             payload_to_list)
+from fastapi_skeleton.models.payload import HousePredictionPayload, payload_to_list
 from fastapi_skeleton.models.prediction import HousePredictionResult
 
 
-class HousePriceModel(object):
+class HousePriceModel:
+    RESULT_UNIT_FACTOR = 100
 
-    RESULT_UNIT_FACTOR = 100000
-
-    def __init__(self, path):
+    def __init__(self, path: str) -> None:
         self.path = path
         self._load_local_model()
 
-    def _load_local_model(self):
+    def _load_local_model(self) -> None:
         self.model = joblib.load(self.path)
 
-    def _pre_process(self, payload: HousePredictionPayload) -> List:
+    def _pre_process(self, payload: HousePredictionPayload) -> np.ndarray:
         logger.debug("Pre-processing payload.")
         result = np.asarray(payload_to_list(payload)).reshape(1, -1)
         return result
@@ -32,18 +26,15 @@ def _post_process(self, prediction: np.ndarray) -> HousePredictionResult:
         logger.debug("Post-processing prediction.")
         result = prediction.tolist()
         human_readable_unit = result[0] * self.RESULT_UNIT_FACTOR
-        hpp = HousePredictionResult(median_house_value=human_readable_unit)
+        hpp = HousePredictionResult(median_house_value=int(human_readable_unit))
         return hpp
 
-    def _predict(self, features: List) -> np.ndarray:
+    def _predict(self, features: np.ndarray) -> np.ndarray:
         logger.debug("Predicting.")
         prediction_result = self.model.predict(features)
         return prediction_result
 
-    def predict(self, payload: HousePredictionPayload):
-        if payload is None:
-            raise ValueError(NO_VALID_PAYLOAD.format(payload))
-
+    def predict(self, payload: HousePredictionPayload) -> HousePredictionResult:
         pre_processed_payload = self._pre_process(payload)
         prediction = self._predict(pre_processed_payload)
         logger.info(prediction)