feat: add pre-commit hooks

.github/ISSUE_TEMPLATE/bug_report.md

@@ -36,7 +36,7 @@ assignees: ''
 
 * **Powertools version used**:
 * **Packaging format (Layers, PyPi)**:
-* **AWS Lambda function runtime:** 
+* **AWS Lambda function runtime:**
 * **Debugging logs**
 
 > [How to enable debug mode](https://awslabs.github.io/aws-lambda-powertools-python/#debug-mode)**

.github/ISSUE_TEMPLATE/rfc.md

@@ -10,7 +10,7 @@ assignees: ''
 ## Key information
 
 * RFC PR: (leave this empty)
-* Related issue(s), if known: 
+* Related issue(s), if known:
 * Area: (i.e. Tracer, Metrics, Logger, etc.)
 * Meet [tenets](https://awslabs.github.io/aws-lambda-powertools-python/#tenets): (Yes/no)
 

.pre-commit-config.yaml

@@ -0,0 +1,38 @@
+# We use poetry to run formatting and linting before commit/push
+# Longers checks such as tests, security and complexity baseline
+# are run as part of CI to prevent slower feedback loop
+# All checks can be run locally via `make pr`
+
+repos:
+    - repo: https://github.com/pre-commit/pre-commit-hooks
+      rev: v2.4.0
+      hooks:
+          - id: check-merge-conflict
+          - id: trailing-whitespace
+          - id: end-of-file-fixer
+          - id: check-toml
+    - repo: https://github.com/pre-commit/pygrep-hooks
+      rev: v1.5.1
+      hooks:
+          - id: python-use-type-annotations
+    - repo: local
+      hooks:
+          - id: black
+            name: formatting::black
+            entry: poetry run black
+            language: system
+            types: [python]
+          - id: isort
+            name: formatting::isort
+            entry: poetry run isort -rc
+            language: system
+            types: [python]
+    - repo: local
+      hooks:
+          - id: flake8
+            name: linting::flake8
+            entry: poetry run flake8
+            language: system
+            types: [python]
+            exclude: example
+fail_fast: true

CHANGELOG.md

@@ -1,4 +1,4 @@
-# Changelog 
+# Changelog
 All notable changes to this project will be documented in this file.
 
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),

LICENSE

@@ -12,4 +12,3 @@ FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
 COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
 IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
 CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
-

Makefile

@@ -3,16 +3,16 @@ target:
 	@$(MAKE) pr
 
 dev:
-	pip install --upgrade pip poetry
+	pip install --upgrade pip poetry pre-commit
 	poetry install
+	pre-commit install
 
 dev-docs:
 	cd docs && npm install
 
 format:
-	poetry run isort -rc .
-	poetry run black aws_lambda_powertools
-	poetry run black tests
+	poetry run isort -rc aws_lambda_powertools tests example
+	poetry run black aws_lambda_powertools tests
 
 lint: format
 	poetry run flake8

aws_lambda_powertools/metrics/schema.json

@@ -111,4 +111,4 @@
             }
         }
     }
-}
+}

aws_lambda_powertools/middleware_factory/factory.py

@@ -27,7 +27,7 @@ def lambda_handler_decorator(decorator: Callable = None, trace_execution=False):
     Environment variables
     ---------------------
     POWERTOOLS_TRACE_MIDDLEWARES : str
-        uses `aws_lambda_powertools.tracing.Tracer` 
+        uses `aws_lambda_powertools.tracing.Tracer`
         to create sub-segments per middleware (e.g. `"true", "True", "TRUE"`)
 
     Parameters

bandit.baseline

@@ -223,4 +223,4 @@
       "test_name": "blacklist"
     }
   ]
-}
+}

docs/content/core/logger.mdx

@@ -39,7 +39,7 @@ You can also explicitly set a service name via `service` param or via `POWERTOOL
 ```python:title=app.py
 from aws_lambda_powertools.logging import Logger
 # POWERTOOLS_SERVICE_NAME defined
-logger = Logger() # highlight-line 
+logger = Logger() # highlight-line
 
 # Explicit definition
 Logger(service="payment", level="INFO")
@@ -58,7 +58,7 @@ Key | Type | Example | Description
 **sampling_rate** | int |  0.1 | Debug logging sampling rate in percentage e.g. 1% in this case
 **message** | any |  "Collecting payment" | Log statement value. Unserializable JSON values will be casted to string
 
-## Capturing context Lambda info 
+## Capturing context Lambda info
 
 You can enrich your structured logs with key Lambda context information via `inject_lambda_context`.
 
@@ -109,7 +109,7 @@ Key | Type | Example
 <summary><strong>Exerpt output in CloudWatch Logs</strong></summary>
 
 ```json:title=cloudwatch_logs.json
-{  
+{
    "timestamp":"2020-05-24 18:17:33,774",
    "level":"INFO",
    "location":"collect.handler:1",
@@ -125,7 +125,7 @@ Key | Type | Example
    "message": "Collecting payment"
 }
 
-{  
+{
    "timestamp":"2020-05-24 18:17:33,774",
    "level":"INFO",
    "location":"collect.handler:15",
@@ -137,7 +137,7 @@ Key | Type | Example
    "cold_start": true,
    "sampling_rate": 0.0,
 // highlight-start
-   "message":{  
+   "message":{
       "operation":"collect_payment",
       "charge_id": "ch_AZFlk2345C0"
    }
@@ -148,7 +148,7 @@ Key | Type | Example
 
 ## Appending additional keys
 
-You can append your own keys to your existing Logger via `structure_logs` with **append** param. 
+You can append your own keys to your existing Logger via `structure_logs` with **append** param.
 
 ```python:title=collect.py
 from aws_lambda_powertools.logging import Logger
@@ -166,7 +166,7 @@ def handler(event, context)
 <summary><strong>Exerpt output in CloudWatch Logs</strong></summary>
 
 ```json:title=cloudwatch_logs.jsonn
-{  
+{
    "timestamp": "2020-05-24 18:17:33,774",
    "level": "INFO",
    "location": "collect.handler:1",
@@ -209,7 +209,7 @@ def handler(event, context)
 <summary><strong>Exerpt output in CloudWatch Logs</strong></summary>
 
 ```json:title=cloudwatch_logs.json
-{  
+{
    "timestamp": "2020-05-24 18:17:33,774",
    "level": "INFO",
    "location": "collect.handler:1",
@@ -223,4 +223,4 @@ def handler(event, context)
    "message": "Collecting payment"
 }
 ```
-</details>
+</details>

docs/content/core/metrics.mdx

@@ -39,7 +39,7 @@ You can also pass a service name via `service` param or `POWERTOOLS_SERVICE_NAME
 from aws_lambda_powertools.metrics import Metrics, MetricUnit
 
 # POWERTOOLS_METRICS_NAMESPACE and POWERTOOLS_SERVICE_NAME defined
-metrics = Metrics() # highlight-line 
+metrics = Metrics() # highlight-line
 
 # Explicit definition
 Metrics(namespace="ServerlessAirline", service="orders")  # creates a default dimension {"service": "orders"} under the namespace "ServerlessAirline"
@@ -69,7 +69,7 @@ CloudWatch EMF supports a max of 100 metrics. Metrics will automatically flush a
 
 ## Creating a metric with a different dimension
 
-CloudWatch EMF uses the same dimensions across all your metrics. Use `single_metric` if you have a metric that should have different dimensions. 
+CloudWatch EMF uses the same dimensions across all your metrics. Use `single_metric` if you have a metric that should have different dimensions.
 
 <Note type="info">
   Generally, this would be an edge case since you <a href="https://aws.amazon.com/cloudwatch/pricing/">pay for unique metric</a>. Keep the following formula in mind:
@@ -105,7 +105,7 @@ def lambda_handler(evt, ctx):
 
 `log_metrics` decorator **validates**, **serializes**, and **flushes** all your metrics. During metrics validation, if any of the following criteria is met, `SchemaValidationError` exception will be raised:
 
-* At least of one Metric and Dimension 
+* At least of one Metric and Dimension
 * Maximum of 9 dimensions
 * Namespace is set, and no more than one
 * Metric units must be [supported by CloudWatch](https://docs.aws.amazon.com/AmazonCloudWatch/latest/APIReference/API_MetricDatum.html)
@@ -141,7 +141,7 @@ metrics = Metrics(namespace="ExampleApplication", service="booking")
 metrics.add_metric(name="ColdStart", unit="Count", value=1)
 
 # highlight-start
-your_metrics_object = metrics.serialize_metric_set() 
+your_metrics_object = metrics.serialize_metric_set()
 metrics.clear_metrics()
 print(json.dumps(your_metrics_object))
 # highlight-end

docs/content/core/tracer.mdx

@@ -39,15 +39,15 @@ You can either explicitly pass using `service` param or via `POWERTOOLS_SERVICE_
 ```python:title=app.py
 from aws_lambda_powertools.tracing import Tracer
 # POWERTOOLS_SERVICE_NAME defined
-tracer = Tracer() # highlight-line 
+tracer = Tracer() # highlight-line
 
 # Explicit definition
 tracer = Tracer(service="booking")
 ```
 
 ## Lambda handler
 
-You can trace your Lambda function handler via `capture_lambda_handler`. 
+You can trace your Lambda function handler via `capture_lambda_handler`.
 
 When using this decorator, Tracer performs these additional tasks to ease operations:
 
@@ -56,7 +56,7 @@ When using this decorator, Tracer performs these additional tasks to ease operat
 
 ```python:title=lambda_handler.py
 from aws_lambda_powertools.tracing import Tracer
-tracer = Tracer() 
+tracer = Tracer()
 
 @tracer.capture_lambda_handler # highlight-line
 def handler(event, context)
@@ -73,7 +73,7 @@ You can add annotations using `put_annotation` method from Tracer.
 
 ```python:title=app.py
 from aws_lambda_powertools.tracing import Tracer
-tracer = Tracer() 
+tracer = Tracer()
 
 @tracer.capture_lambda_handler
 def handler(event, context):
@@ -89,7 +89,7 @@ You can add metadata using `put_metadata` method from Tracer.
 
 ```python:title=app.py
 from aws_lambda_powertools.tracing import Tracer
-tracer = Tracer() 
+tracer = Tracer()
 
 @tracer.capture_lambda_handler
 def handler(event, context):
@@ -125,7 +125,7 @@ from aws_lambda_powertools.tracing import Tracer
 tracer = Tracer()
 
 # highlight-start
-@tracer.capture_method 
+@tracer.capture_method
 async def collect_payment():
     ...
 # highlight-end
@@ -194,7 +194,7 @@ async def collect_payment(charge_id):
     ...
 ```
 
-## Reusing Tracer across your code 
+## Reusing Tracer across your code
 
 Tracer keeps a copy of its configuration after the first initialization. This is useful for scenarios where you want to use Tracer in more than one location across your code base.
 
@@ -214,7 +214,7 @@ def handler(event, context)
 from aws_lambda_powertools.tracing import Tracer
 # highlight-start
 # new instance using existing configuration with auto patching overriden
-tracer = Tracer(auto_patch=False) 
+tracer = Tracer(auto_patch=False)
 # highlight-end
 ```
 

docs/content/dummy.md

@@ -5,4 +5,4 @@ description: Dummy description
 
 ## Test
 
-dummy content
+dummy content

docs/content/index.mdx

@@ -23,7 +23,7 @@ Powertools is available in PyPi. You can use your favourite dependency managemen
 
 * **AWS Lambda only** – We optimise for AWS Lambda function environments and supported runtimes only. Utilities might work with web frameworks and non-Lambda environments, though they are not officially supported.
 * **Eases the adoption of best practices** – The main priority of the utilities is to facilitate best practices adoption, as defined in the AWS Well-Architected Serverless Lens; all other functionality is optional.
-* **Keep it lean** – Additional dependencies are carefully considered for security and ease of maintenance, and prevent negatively impacting startup time. 
+* **Keep it lean** – Additional dependencies are carefully considered for security and ease of maintenance, and prevent negatively impacting startup time.
 * **We strive for backwards compatibility** – New features and changes should keep backwards compatibility. If a breaking change cannot be avoided, the deprecation and migration process should be clearly defined.
 * **We work backwards from the community** – We aim to strike a balance of what would work best for 80% of customers. Emerging practices are considered and discussed via Requests for Comment (RFCs)
 * **Idiomatic** – Utilities follow programming language idioms and language-specific best practices.

docs/content/utilities/middleware_factory.mdx

@@ -25,7 +25,7 @@ from aws_lambda_powertools.middleware_factory import lambda_handler_decorator
 
 # highlight-start
 @lambda_handler_decorator
-def middleware_before_after(handler, event, context): 
+def middleware_before_after(handler, event, context):
 # highlight-end
     # logic_before_handler_execution()
     response = handler(event, context)

docs/gatsby-config.js

@@ -62,7 +62,7 @@ module.exports = {
                     'AWS SAM Docs': {
                         href: 'https://docs.aws.amazon.com/serverless-application-model/latest/developerguide/what-is-sam.html',
                     }
-                }                
+                }
             }
         },
         {

docs/src/components/Note/index.js

@@ -20,4 +20,4 @@ const Note = ({ type = 'info', title = '', children }) => {
     )
 }
 
-export default Note
+export default Note

docs/src/gatsby-theme-apollo-docs/components/header-button.js

@@ -1,2 +1,2 @@
 // Shadow Header built-in component and remove `Launch Graph Manager`
-export default () => null;
+export default () => null;

example/.gitignore

@@ -241,4 +241,4 @@ $RECYCLE.BIN/
 
 */build/*
 
-# End of https://www.gitignore.io/api/osx,linux,python,windows,pycharm,visualstudiocode
+# End of https://www.gitignore.io/api/osx,linux,python,windows,pycharm,visualstudiocode

example/README.md

@@ -19,13 +19,13 @@ This project contains source code and supporting files for a serverless applicat
 
 - hello_world - Code for the application's Lambda function.
 - events - Invocation events that you can use to invoke the function.
-- tests - Unit tests for the application code. 
+- tests - Unit tests for the application code.
 - template.yaml - A template that defines the application's AWS resources.
 - requirements-dev.txt - Dev dependencies to run unit tests successfully
 
 The application uses several AWS resources, including Lambda functions and an API Gateway API. These resources are defined in the `template.yaml` file in this project. You can update the template to add AWS resources through the same deployment process that updates your application code.
 
-If you prefer to use an integrated development environment (IDE) to build and test your application, you can use the AWS Toolkit.  
+If you prefer to use an integrated development environment (IDE) to build and test your application, you can use the AWS Toolkit.
 The AWS Toolkit is an open source plug-in for popular IDEs that uses the SAM CLI to build and deploy serverless applications on AWS. The AWS Toolkit also adds a simplified step-through debugging experience for Lambda function code. See the following links to get started.
 
 * [PyCharm](https://docs.aws.amazon.com/toolkit-for-jetbrains/latest/userguide/welcome.html)

example/hello_world/app.py

@@ -20,7 +20,7 @@
 
 _cold_start = True
 
-metrics.add_dimension(name="operation", value="example") # added at cold start only
+metrics.add_dimension(name="operation", value="example")  # added at cold start only
 
 
 async def aioboto_task():

example/pytest.ini

@@ -1,3 +1,3 @@
 [pytest]
 addopts = -ra -v
-testpaths = ./tests
+testpaths = ./tests