docs(feature_flags): snippets split, improved, and lint

examples/feature_flags/sam/template.yaml

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+AWSTemplateFormatVersion: "2010-09-09"
+Description: Lambda Powertools for Python Feature flags sample template
+Resources:
+  FeatureStoreApp:
+    Type: AWS::AppConfig::Application
+    Properties:
+      Description: "AppConfig Application for feature toggles"
+      Name: product-catalogue
+
+  FeatureStoreDevEnv:
+    Type: AWS::AppConfig::Environment
+    Properties:
+      ApplicationId: !Ref FeatureStoreApp
+      Description: "Development Environment for the App Config Store"
+      Name: dev
+
+  FeatureStoreConfigProfile:
+    Type: AWS::AppConfig::ConfigurationProfile
+    Properties:
+      ApplicationId: !Ref FeatureStoreApp
+      Name: features
+      LocationUri: "hosted"
+
+  HostedConfigVersion:
+    Type: AWS::AppConfig::HostedConfigurationVersion
+    Properties:
+      ApplicationId: !Ref FeatureStoreApp
+      ConfigurationProfileId: !Ref FeatureStoreConfigProfile
+      Description: 'A sample hosted configuration version'
+      Content: |
+        {
+              "premium_features": {
+                "default": false,
+                "rules": {
+                  "customer tier equals premium": {
+                    "when_match": true,
+                    "conditions": [
+                      {
+                        "action": "EQUALS",
+                        "key": "tier",
+                        "value": "premium"
+                      }
+                    ]
+                  }
+                }
+              },
+              "ten_percent_off_campaign": {
+                "default": false
+              }
+          }
+      ContentType: 'application/json'
+
+  ConfigDeployment:
+    Type: AWS::AppConfig::Deployment
+    Properties:
+      ApplicationId: !Ref FeatureStoreApp
+      ConfigurationProfileId: !Ref FeatureStoreConfigProfile
+      ConfigurationVersion: !Ref HostedConfigVersion
+      DeploymentStrategyId: "AppConfig.AllAtOnce"
+      EnvironmentId: !Ref FeatureStoreDevEnv

examples/feature_flags/src/appconfig_provider_options.py

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+from typing import Any
+
+from botocore.config import Config
+from jmespath.functions import Functions, signature
+
+from aws_lambda_powertools.utilities.feature_flags import AppConfigStore, FeatureFlags
+from aws_lambda_powertools.utilities.typing import LambdaContext
+
+boto_config = Config(read_timeout=10, retries={"total_max_attempts": 2})
+
+
+# Custom JMESPath functions
+class CustomFunctions(Functions):
+    @signature({"types": ["object"]})
+    def _func_special_decoder(self, features):
+        # You can add some logic here
+        return features
+
+
+custom_jmespath_options = {"custom_functions": CustomFunctions()}
+
+
+app_config = AppConfigStore(
+    environment="dev",
+    application="product-catalogue",
+    name="features",
+    max_age=120,
+    envelope="special_decoder(features)",  # using a custom function defined in CustomFunctions Class
+    sdk_config=boto_config,
+    jmespath_options=custom_jmespath_options,
+)
+
+feature_flags = FeatureFlags(store=app_config)
+
+
+def lambda_handler(event: dict, context: LambdaContext):
+    apply_discount: Any = feature_flags.evaluate(name="ten_percent_off_campaign", default=False)
+
+    price: Any = event.get("price")
+
+    if apply_discount:
+        # apply 10% discount to product
+        price = price * 0.9
+
+    return {"price": price}

examples/feature_flags/src/appconfig_provider_options_features.json

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+{
+	"logging": {
+		  "level": "INFO",
+		  "sampling_rate": 0.1
+	 },
+	"features": {
+	  "ten_percent_off_campaign": {
+		"default": true
+	  }
+	}
+  }

examples/feature_flags/src/appconfig_provider_options_payload.json

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+{
+    "product": "laptop",
+    "price": 1000
+}

examples/feature_flags/src/beyond_boolean.py

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+from typing import Any
+
+from aws_lambda_powertools.utilities.feature_flags import AppConfigStore, FeatureFlags
+from aws_lambda_powertools.utilities.typing import LambdaContext
+
+app_config = AppConfigStore(environment="dev", application="comments", name="config")
+
+feature_flags = FeatureFlags(store=app_config)
+
+
+def lambda_handler(event: dict, context: LambdaContext):
+    # Get customer's tier from incoming request
+    ctx = {"tier": event.get("tier", "standard")}
+
+    # Evaluate `has_premium_features` based on customer's tier
+    premium_features: Any = feature_flags.evaluate(name="premium_features", context=ctx, default=[])
+
+    return {"Premium features enabled": premium_features}

examples/feature_flags/src/beyond_boolean_features.json

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+{
+	"premium_features": {
+	  "boolean_type": false,
+	  "default": [],
+	  "rules": {
+		"customer tier equals premium": {
+		  "when_match": [
+			"no_ads",
+			"no_limits",
+			"chat"
+		  ],
+		  "conditions": [
+			{
+			  "action": "EQUALS",
+			  "key": "tier",
+			  "value": "premium"
+			}
+		  ]
+		}
+	  }
+	}
+  }

examples/feature_flags/src/beyond_boolean_payload.json

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+{
+    "username": "lessa",
+    "tier": "premium",
+    "basked_id": "random_id"
+}

examples/feature_flags/src/conditions.json

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+{
+	"conditions": [
+		{
+			"action": "EQUALS",
+			"key": "tier",
+			"value": "premium"
+		}
+	]
+}

examples/feature_flags/src/custom_s3_store_provider.py

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+import json
+from typing import Any, Dict
+
+import boto3
+from botocore.exceptions import ClientError
+
+from aws_lambda_powertools.utilities.feature_flags.base import StoreProvider
+from aws_lambda_powertools.utilities.feature_flags.exceptions import (
+    ConfigurationStoreError,
+)
+
+
+class S3StoreProvider(StoreProvider):
+    def __init__(self, bucket_name: str, object_key: str):
+        # Initialize the client to your custom store provider
+
+        super().__init__()
+
+        self.bucket_name = bucket_name
+        self.object_key = object_key
+        self.client = boto3.client("s3")
+
+    def _get_s3_object(self) -> Dict[str, Any]:
+        # Retrieve the object content
+        parameters = {"Bucket": self.bucket_name, "Key": self.object_key}
+
+        try:
+            response = self.client.get_object(**parameters)
+            return json.loads(response["Body"].read().decode())
+        except ClientError as exc:
+            raise ConfigurationStoreError("Unable to get S3 Store Provider configuration file") from exc
+
+    def get_configuration(self) -> Dict[str, Any]:
+        return self._get_s3_object()
+
+    @property
+    def get_raw_configuration(self) -> Dict[str, Any]:
+        return self._get_s3_object()

examples/feature_flags/src/datetime_feature.py

@@ -1,14 +1,37 @@
 from aws_lambda_powertools.utilities.feature_flags import AppConfigStore, FeatureFlags
+from aws_lambda_powertools.utilities.typing import LambdaContext
 
 app_config = AppConfigStore(environment="dev", application="product-catalogue", name="features")
 
 feature_flags = FeatureFlags(store=app_config)
 
 
-def lambda_handler(event, context):
-    # Get customer's tier from incoming request
+def lambda_handler(event: dict, context: LambdaContext):
+    """
+    This feature flag is enabled under the following conditions:
+    - Start date: December 25th, 2022 at 12:00:00 PM EST
+    - End date: December 31st, 2022 at 11:59:59 PM EST
+    - Timezone: America/New_York
+
+    Rule condition to be evaluated:
+        "conditions": [
+          {
+            "action": "SCHEDULE_BETWEEN_DATETIME_RANGE",
+            "key": "CURRENT_DATETIME",
+            "value": {
+              "START": "2022-12-25T12:00:00",
+              "END": "2022-12-31T23:59:59",
+              "TIMEZONE": "America/New_York"
+            }
+          }
+        ]
+    """
+
+    # Checking if the Christmas discount is enable
     xmas_discount = feature_flags.evaluate(name="christmas_discount", default=False)
 
     if xmas_discount:
         # Enable special discount on christmas:
-        pass
+        return {"message": "The Christmas discount is enabled."}
+
+    return {"message": "The Christmas discount is not enabled."}

examples/feature_flags/src/extracting_envelope.py

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+from typing import Any
+
+from aws_lambda_powertools.utilities.feature_flags import AppConfigStore, FeatureFlags
+from aws_lambda_powertools.utilities.typing import LambdaContext
+
+app_config = AppConfigStore(
+    environment="dev", application="product-catalogue", name="features", envelope="feature_flags"
+)
+
+feature_flags = FeatureFlags(store=app_config)
+
+
+def lambda_handler(event: dict, context: LambdaContext):
+    apply_discount: Any = feature_flags.evaluate(name="ten_percent_off_campaign", default=False)
+
+    price: Any = event.get("price")
+
+    if apply_discount:
+        # apply 10% discount to product
+        price = price * 0.9
+
+    return {"price": price}

examples/feature_flags/src/extracting_envelope_features.json

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+{
+	"logging": {
+		  "level": "INFO",
+		  "sampling_rate": 0.1
+	 },
+	"features": {
+	  "ten_percent_off_campaign": {
+		"default": true
+	  }
+	}
+  }

examples/feature_flags/src/extracting_envelope_payload.json

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+{
+    "product": "laptop",
+    "price": 1000
+}

examples/feature_flags/src/feature_with_rules.json

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+{
+    "premium_feature": {
+        "default": false,
+        "rules": {
+            "customer tier equals premium": {
+                "when_match": true,
+                "conditions": [
+                    {
+                        "action": "EQUALS",
+                        "key": "tier",
+                        "value": "premium"
+                    }
+                ]
+            }
+        }
+    },
+    "non_boolean_premium_feature": {
+        "default": [],
+        "rules": {
+            "customer tier equals premium": {
+                "when_match": ["remove_limits", "remove_ads"],
+                "conditions": [
+                    {
+                        "action": "EQUALS",
+                        "key": "tier",
+                        "value": "premium"
+                    }
+                ]
+            }
+        }
+    }
+}

examples/feature_flags/src/getting_all_enabled_features.py

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+from aws_lambda_powertools.event_handler import APIGatewayRestResolver
+from aws_lambda_powertools.utilities.feature_flags import AppConfigStore, FeatureFlags
+from aws_lambda_powertools.utilities.typing import LambdaContext
+
+app = APIGatewayRestResolver()
+
+app_config = AppConfigStore(environment="dev", application="product-catalogue", name="features")
+
+feature_flags = FeatureFlags(store=app_config)
+
+
+@app.get("/products")
+def list_products():
+    # getting fields from request
+    # https://awslabs.github.io/aws-lambda-powertools-python/latest/core/event_handler/api_gateway/#accessing-request-details
+    json_body = app.current_event.json_body
+    headers = app.current_event.headers
+
+    ctx = {**headers, **json_body}
+
+    # getting price from payload
+    price: float = float(json_body.get("price"))
+    percent_discount: int = 0
+
+    # all_features is evaluated to ["premium_features", "geo_customer_campaign", "ten_percent_off_campaign"]
+    all_features: list[str] = feature_flags.get_enabled_features(context=ctx)
+
+    if "geo_customer_campaign" in all_features:
+        # apply 20% discounts for customers in NL
+        percent_discount += 20
+
+    if "ten_percent_off_campaign" in all_features:
+        # apply additional 10% for all customers
+        percent_discount += 10
+
+    price = price * (100 - percent_discount) / 100
+
+    return {"price": price}
+
+
+def lambda_handler(event: dict, context: LambdaContext):
+    return app.resolve(event, context)