restructure to v2

Author: RabidSheep55

.github/workflows/build-base-image.yml

@@ -1,4 +1,4 @@
-name: Test & Deploy Grading Script to AWS Lambda
+name: Test & Deploy Evaluation Function to AWS Lambda
 
 on:
   push:
@@ -20,6 +20,10 @@ jobs:
       run:
         working-directory: app/
 
+    env:
+      REQUEST_SCHEMA_URL: https://raw.githubusercontent.com/lambda-feedback/request-response-schemas/master/request.json
+      RESPONSE_SCHEMA_URL: https://raw.githubusercontent.com/lambda-feedback/request-response-schemas/master/responsev2.json
+
     steps:
       - name: Checkout
         uses: actions/checkout@v2
@@ -33,7 +37,6 @@ jobs:
         run: |
           python -m pip install --upgrade pip
           python -m pip install flake8 pytest
-          python -m pip install -r tools/tools_requirements.txt
           python -m pip install -r requirements.txt
 
       - name: Lint with flake8
@@ -43,29 +46,109 @@ jobs:
           # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
           flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
 
-      - name: Test Handler functions
+      - name: Test Evaluation Function
         run: |
-          pytest -v tests/handling.py::TestHandlerFunction
-      - name: Test JSON schema
+          pytest -v evaluation_tests.py::TestEvaluationFunction
+
+  deploy-staging:
+    name: Deploy Staging
+    needs: test
+    runs-on: ubuntu-latest
+    environment: production
+    env:
+      ECR_REPOSITORY: lambda-feedback-staging-functions-repository
+
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v2
+
+      - name: Set config.json output
+        id: set_config_var
         run: |
-          pytest -v tests/validation.py::TestSchemaValidation
-      - name: Test Grading functions
+          content=`cat ./config.json`
+          # the following lines are only required for multi line json
+          content="${content//'%'/'%25'}"
+          content="${content//$'\n'/'%0A'}"
+          content="${content//$'\r'/'%0D'}"
+          # end of optional handling for multi line json
+          echo "::set-output name=configJson::$content"
+
+      - name: set Evaluation Function Name
+        id: set_function_name
         run: |
-          pytest -v tests/grading.py::TestGradingFunction
+          functionName="${{fromJson(steps.set_config_var.outputs.configJson).EvaluationFunctionName}}"
+          [[ -z "$functionName" ]] && { echo "Add EvaluationFunctionName to config.json" ; exit 1; }
+          echo "::set-output name=function_name::$functionName"
 
-  deploy:
-    name: Deploy
-    needs: test
+      - name: Configure AWS credentials
+        uses: aws-actions/configure-aws-credentials@v1
+        with:
+          aws-access-key-id: ${{ secrets.LAMBDA_CONTAINER_PIPELINE_AWS_ID }}
+          aws-secret-access-key: ${{ secrets.LAMBDA_CONTAINER_PIPELINE_AWS_SECRET }}
+          aws-region: eu-west-2
+
+      - name: Login to Amazon ECR
+        id: login-ecr
+        uses: aws-actions/amazon-ecr-login@v1
+
+      - name: Build, tag, and push image to Amazon ECR
+        id: build-image
+        env:
+          ECR_REGISTRY: ${{ steps.login-ecr.outputs.registry }}
+          IMAGE_TAG: ${{ steps.set_function_name.outputs.function_name }}
+        run: |
+          # Build docker image from algorithm, schema and requirements
+          docker build -t $ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG app/
+          # Push image to ECR
+          docker push $ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG
+          echo "::set-output name=image::$ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG"
+
+      - name: deploy evaluation function
+        id: deploy-evaluation-function
+        env:
+          BACKEND_API_URL: https://hytqbudf4a.eu-west-1.awsapprunner.com
+          API_KEY: ${{ secrets.FUNCTION_ADMIN_API_KEY }}
+          ECR_REGISTRY: ${{ steps.login-ecr.outputs.registry }}
+          IMAGE_TAG: ${{ steps.set_function_name.outputs.function_name }}
+        run: |
+          curl --location --request POST "$BACKEND_API_URL/grading-function/ensure" \
+          --header 'content-type: application/json' \
+          --data-raw "{
+              \"apiKey\": \"$API_KEY\",
+              \"dockerImageUri\": \"$ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG\",
+              \"functionName\": \"$IMAGE_TAG\"
+          }"
+
+  deploy-production:
+    name: Deploy Production
+    needs: deploy-staging
     runs-on: ubuntu-latest
     environment: production
     env:
-      ECR_REPOSITORY: is-exact-equal
-      LAMBDA_FUNCTION_NAME: isExactEqual
+      ECR_REPOSITORY: lambda-feedback-production-functions-repository
 
     steps:
       - name: Checkout
         uses: actions/checkout@v2
 
+      - name: Set config.json output
+        id: set_config_var
+        run: |
+          content=`cat ./config.json`
+          # the following lines are only required for multi line json
+          content="${content//'%'/'%25'}"
+          content="${content//$'\n'/'%0A'}"
+          content="${content//$'\r'/'%0D'}"
+          # end of optional handling for multi line json
+          echo "::set-output name=configJson::$content"
+
+      - name: set Evaluation Function Name
+        id: set_function_name
+        run: |
+          functionName="${{fromJson(steps.set_config_var.outputs.configJson).EvaluationFunctionName}}"
+          [[ -z "$functionName" ]] && { echo "Add EvaluationFunctionName to config.json" ; exit 1; }
+          echo "::set-output name=function_name::$functionName"
+
       - name: Configure AWS credentials
         uses: aws-actions/configure-aws-credentials@v1
         with:
@@ -81,17 +164,26 @@ jobs:
         id: build-image
         env:
           ECR_REGISTRY: ${{ steps.login-ecr.outputs.registry }}
-          IMAGE_TAG: latest
+          IMAGE_TAG: ${{ steps.set_function_name.outputs.function_name }}
         run: |
           # Build docker image from algorithm, schema and requirements
           docker build -t $ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG app/
           # Push image to ECR
           docker push $ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG
           echo "::set-output name=image::$ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG"
 
-      - name: Update lambda function image
+      - name: deploy evaluation function
+        id: deploy-evaluation-function
         env:
+          BACKEND_API_URL: https://vnfapgr7gv.eu-west-1.awsapprunner.com
+          API_KEY: ${{ secrets.FUNCTION_ADMIN_API_KEY }}
           ECR_REGISTRY: ${{ steps.login-ecr.outputs.registry }}
-          IMAGE_TAG: latest
+          IMAGE_TAG: ${{ steps.set_function_name.outputs.function_name }}
         run: |
-          aws lambda update-function-code --function-name $LAMBDA_FUNCTION_NAME --image-uri $ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG
+          curl --location --request POST "$BACKEND_API_URL/grading-function/ensure" \
+          --header 'content-type: application/json' \
+          --data-raw "{
+              \"apiKey\": \"$API_KEY\",
+              \"dockerImageUri\": \"$ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG\",
+              \"functionName\": \"$IMAGE_TAG\"
+          }"

.github/workflows/test-and-deploy.yml

@@ -1,24 +1,22 @@
 # Base image that bundles AWS Lambda Python 3.8 image with some middleware functions
-FROM loumstarlearjet/python-lambda-question-type:testing
+FROM rabidsheep55/python-base-eval-layer
 
-# To avoid setting up the app in the global space,
-# everything is package within an /app directory.
 WORKDIR /app
 
-# Copy and install any packages/modules needed for your grading script.
+# Copy and install any packages/modules needed for your evaluation script.
 COPY requirements.txt .
 RUN pip3 install -r requirements.txt
 
-# Copy the schema needed to check the incoming data is valid
-COPY schema.json ./app/
+# Copy the evaluation and testing scripts
+COPY evaluation.py ./app/
+COPY evaluation_tests.py ./app/
 
-# Copy the grading and testing scripts
-COPY algorithm.py ./app/
-COPY tests/ ./app/tests/
+# Copy Documentation
+COPY docs.md ./app/
 
 # Set permissions so files and directories can be accessed on AWS
 RUN chmod 644 $(find . -type f)
 RUN chmod 755 $(find . -type d)
 
 # The entrypoint for AWS is to invoke the handler function within the app package
-CMD ["/app/app.handler"]
+CMD [ "/app/app.handler" ]

app/Dockerfile

@@ -1,2 +0,0 @@
-from .algorithm import grading_function
-from .tools import handler, validate_request

app/__init__.py

@@ -0,0 +1,50 @@
+# IsExactEqual
+Could be qualified as the simplest form of evaluation function, testing exact equality. This function will use the default python `==` test to compare answer and responses. It doesn't infer any types - meaning it requires a `params.type` to be supplied.
+
+## Inputs
+This function requires a parameter to function properly:
+```json 
+{ 
+  "params": {
+    "type": "<string>" (any of ["int", "float", "str", "dict"])
+  }
+  "response": <>,
+  "answer": <>
+}
+
+```
+
+## Outputs
+Outputs to the `grade` command will feature:
+
+```json
+{
+  "command": "eval",
+  "result": {
+    "is_correct": "<bool>"
+  }
+}
+
+```
+
+## Examples
+
+### Simple String Comparison
+
+```python
+{
+  "answer": "hydrophobic",
+  "response" "hydrophobic",
+  "params": {
+    "type": "str"
+  }
+}
+```
+
+```python
+{
+  "example": {
+    "Something": "something"
+  }
+}
+```

app/docs.md

@@ -1,8 +1,8 @@
-def grading_function(body: dict) -> dict:
+def evaluation_function(response, answer, params) -> dict:
     """
     Function used to grade a student response.
     ---
-    The handler function passes only one argument to grading_function(),
+    The handler function passes only one argument to evaluation_function(),
     which is a dictionary of the structure of the API request body
     deserialised from JSON.
 
@@ -15,31 +15,32 @@ def grading_function(body: dict) -> dict:
 
     The way you wish to structure you code (all in this function, or
     split into many) is entirely up to you. All that matters are the
-    return types and that grading_function() is the main function used
+    return types and that evaluation_function() is the main function used
     to output the grading response.
     """
 
     type_dict = {"float": float, "int": int, "str": str, "dict": dict}
-    req_type = body["params"]["type"]
+    req_type = params.get("type", False)
+
+    if not req_type:
+        raise SyntaxError("params.type is a required field")
+
+    cast_type = type_dict.get(req_type, False)
+
+    if not cast_type:
+        raise SyntaxError(f"Supplied type {req_type} not available")
 
     # Try cast each of the inputs to their requested type:
     errors = []
     try:
-        res = type_dict[req_type](body["response"])
+        res = cast_type(response)
     except ValueError as e:
-        errors += [
-            {"description": f"Could not cast `response` parameter to {req_type}"}
-        ]
+        raise ValueError(f"Could not cast `response` parameter to {req_type}")
 
     try:
-        ans = type_dict[req_type](body["answer"])
+        ans = cast_type(answer)
     except ValueError as e:
-        errors += [{"description": f"Could not cast `answer` parameter to {req_type}"}]
-
-    if errors:
-        return {"error": errors}
-
-    # Are they equaL?
-    is_exact_equal = res == ans
+        raise ValueError(f"Could not cast `answer` parameter to {req_type}")
 
-    return {"is_correct": is_exact_equal}
+    # Are they equal?
+    return {"is_correct": res == ans}