first commit

.github/workflows/main.yaml

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+name: workflow
+
+on:
+  push:
+    branches:
+      - main
+    paths-ignore:
+      - 'README.md'
+
+permissions:
+  id-token: write
+  contents: read
+
+jobs:
+  integration:
+    name: Continuous Integration
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout Code
+        uses: actions/checkout@v3
+
+      - name: Lint code
+        run: echo "Linting repository"
+
+      - name: Run unit tests
+        run: echo "Running unit tests"
+
+  build-and-push-ecr-image:
+    name: Continuous Delivery
+    needs: integration
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout Code
+        uses: actions/checkout@v3
+
+      - name: Install Utilities
+        run: |
+          sudo apt-get update
+          sudo apt-get install -y jq unzip
+      - name: Configure AWS credentials
+        uses: aws-actions/configure-aws-credentials@v1
+        with:
+          aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
+          aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
+          aws-region: ${{ secrets.AWS_REGION }}
+
+      - 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 }}
+          ECR_REPOSITORY: ${{ secrets.ECR_REPOSITORY_NAME }}
+          IMAGE_TAG: latest
+        run: |
+          # Build a docker container and
+          # push it to ECR so that it can
+          # be deployed to ECS.
+          docker build -t $ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG .
+          docker push $ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG
+          echo "::set-output name=image::$ECR_REGISTRY/$ECR_REPOSITORY:$IMAGE_TAG"
+          
+          
+  Continuous-Deployment:
+    needs: build-and-push-ecr-image
+    runs-on: self-hosted
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v3
+
+      - name: Configure AWS credentials
+        uses: aws-actions/configure-aws-credentials@v1
+        with:
+          aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
+          aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
+          aws-region: ${{ secrets.AWS_REGION }}
+
+      - name: Login to Amazon ECR
+        id: login-ecr
+        uses: aws-actions/amazon-ecr-login@v1
+
+
+      - name: Pull latest images
+        run: |
+         docker pull ${{secrets.AWS_ECR_LOGIN_URI}}/${{ secrets.ECR_REPOSITORY_NAME }}:latest
+         
+      # - name: Stop and remove  container if running
+      #   run: |
+      #    docker ps -q --filter "name=mltest" | grep -q . && docker stop mltest && docker rm -fv mltest
+
+      - name: Run Docker Image to serve users
+        run: |
+         docker run -d -p 8080:8080 --ipc="host" --name=mltest -e 'AWS_ACCESS_KEY_ID=${{ secrets.AWS_ACCESS_KEY_ID }}' -e 'AWS_SECRET_ACCESS_KEY=${{ secrets.AWS_SECRET_ACCESS_KEY }}' -e 'AWS_REGION=${{ secrets.AWS_REGION }}'  ${{secrets.AWS_ECR_LOGIN_URI}}/${{ secrets.ECR_REPOSITORY_NAME }}:latest
+      - name: Clean previous images and containers
+        run: |
+         docker system prune -f

.gitignore

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+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+pip-wheel-metadata/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+.python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+mlproject.egg-info

Dockerfile

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+FROM python:3.8-slim-buster
+WORKDIR /app
+COPY . /app
+
+RUN apt update -y && apt install awscli -y
+
+RUN apt-get update && apt-get install ffmpeg libsm6 libxext6 unzip -y && pip install -r requirements.txt
+CMD ["python3", "app.py"]

README.md

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+## End to End MAchine Learning Project
+
+1. Docker Build checked
+2. Github Workflow
+3. Iam User In AWS
+
+## Docker Setup In EC2 commands to be Executed
+
+#optinal
+
+sudo apt-get update -y
+
+sudo apt-get upgrade
+
+#required
+
+curl -fsSL https://get.docker.com -o get-docker.sh
+
+sudo sh get-docker.sh
+
+sudo usermod -aG docker ubuntu
+
+newgrp docker
+
+## Configure EC2 as self-hosted runner:
+
+## Setup github secrets:
+
+AWS_ACCESS_KEY_ID=
+
+AWS_SECRET_ACCESS_KEY=
+
+AWS_REGION = us-east-1
+
+AWS_ECR_LOGIN_URI = demo>>  566373416292.dkr.ecr.ap-south-1.amazonaws.com
+
+ECR_REPOSITORY_NAME = simple-app

app.py

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+from flask import Flask,request,render_template
+import numpy as np
+import pandas as pd
+
+
+from sklearn.preprocessing import StandardScaler
+from src.pipeline.predict_pipeline import CustomData,PredictPipeline
+
+application=Flask(__name__)
+
+app=application
+
+## Route for a home page
+
+@app.route('/')
+def index():
+    return render_template('index.html') 
+
+@app.route('/predictdata',methods=['GET','POST'])
+def predict_datapoint():
+    if request.method=='GET':
+        return render_template('home.html')
+    else:
+        data=CustomData(
+            gender=request.form.get('gender'),
+            race_ethnicity=request.form.get('ethnicity'),
+            parental_level_of_education=request.form.get('parental_level_of_education'),
+            lunch=request.form.get('lunch'),
+            test_preparation_course=request.form.get('test_preparation_course'),
+            reading_score=float(request.form.get('writing_score')),
+            writing_score=float(request.form.get('reading_score')))
+
+        pred_df=data.get_data_as_data_frame()
+        print(pred_df)
+
+        predict_pipeline=PredictPipeline()
+        results=predict_pipeline.predict(pred_df)
+        return render_template('home.html',results=results[0])
+
+
+
+if __name__=="__main__":
+    # app.run(host="0.0.0.0",port=8080)        
+    app.run(host='0.0.0.0', port=8080)        
+
+