Merge pull request #211 from DSC-McMaster-U/docker_secret

Credentials Deployment to Backend Docker Image

.github/workflows/docker.yml

@@ -2,14 +2,6 @@ name: "Manually Deploy Docker Files to Artifact Registry"
 
 on:
   workflow_dispatch:
-    # push:            
-    #     branches:
-    #         - 'main'
-    #     paths:
-    #         -'backend/'
-    #         -'frontend/'
-    #         -'machine-learning/Dockerfile'
-
 
 jobs:
     deploy:
@@ -28,15 +20,19 @@ jobs:
           with: 
             credentials_json: ${{ secrets.OWNER_SA_KEY }}
 
+        - name: Decode credentials.json
+          run: echo "${{ secrets.B64_ENCODED_KEY }}" | base64 --decode > credentials.json
+
         - name: Install GCloud CLI
           uses: google-github-actions/setup-gcloud@v0
 
         - name: Build and Push Backend Docker Image
           env:
             GOOGLE_PROJECT: ${{ secrets.PROJECT_ID }}
+            CREDENTIALS_JSON: ${{ secrets.B64_ENCODED_KEY }}
           run: |
             gcloud auth configure-docker us-central1-docker.pkg.dev
-            docker build -t us-central1-docker.pkg.dev/automate-gdsc/backend-images/backend:latest ./backend
+            docker build --build-arg CREDENTIALS_JSON=./credentials.json -t us-central1-docker.pkg.dev/automate-gdsc/backend-images/backend:latest ./backend
             docker push us-central1-docker.pkg.dev/automate-gdsc/backend-images/backend:latest 
 
         - name: Build and Push Frontend Docker Image

backend/Dockerfile

@@ -1,3 +1,6 @@
+# argument to be passed while running the docker build command
+ARG CREDENTIALS_JSON
+
 # Use the official Python 3.11 image from Docker Hub
 FROM python:3.11.6-slim
 
@@ -22,10 +25,11 @@ COPY pyproject.toml poetry.lock ./
 RUN poetry config virtualenvs.create false && poetry install --no-dev
 
 # Copy the creds file and compute dir into the container
-COPY credentials.json ./
 COPY compute ./compute
+COPY  ${CREDENTIALS_JSON} ./
 
 # Copy the FastAPI application into the container
+COPY big_query.py ./
 COPY main.py ./
 
 # Specify the command to run the FastAPI application using uvicorn

backend/main.py

@@ -1,22 +1,24 @@
 from http.client import HTTPException
 from google.cloud import storage
-from google.cloud import bigquery
 from starlette.responses import FileResponse
 from io import BytesIO, StringIO
 import pandas as pd
 import os
 from fastapi import FastAPI, File, UploadFile, Form
 from fastapi.responses import JSONResponse
 from fastapi.middleware.cors import CORSMiddleware
+
+# custom functions for EDA and AutoML
 from compute.autoEDA import generate_eda
 from compute.autoML import generate_model
+from big_query import bq_ops
+
 
 import csv
 
 app = FastAPI()
 
 DATA_BUCKET = "automate-ml-datasets"
-BQ_DATASET = "automl_dataset_1"
 GRAPH_BUCKET = "automate_ml_graphs"
 origins = ["*"]
 
@@ -197,69 +199,11 @@ async def getModel():
     return FileResponse(path=model_path, filename=model_path.split("/")[-1], media_type='application/octet-stream')
 
 
-# get file from bucket, load it to big query as a table & display the rows
+# big query operations
 @app.get("/api/bq")
 async def bq(fileName, query=None):
-
-    # construct client objects (authorized with the service account json file)
-    bq_client = bigquery.Client.from_service_account_json("./credentials.json")
-    storage_client = storage.Client.from_service_account_json("./credentials.json")
-
-    # check if the file name has .csv extension, if not, add it
-    # if not fileName.endswith('.csv'):
-    #     fileName += '.csv'
-
-    uri = f"gs://{DATA_BUCKET}/{fileName}"
-
-    # if file does not exist in the bucket, return an error
-    blob = storage_client.get_bucket(DATA_BUCKET).blob(fileName)
-    if not blob.exists():
-        return {"error": f"File {fileName} does not exist in the bucket."}
-
-    fileName = fileName.replace('.csv', '')
-    table_id = f"{BQ_DATASET}.{fileName}_table"
-
-    # if table does not exist, load it
-    # try:
-    #     bq_client.get_table(table_id)
-    # except:
-    job_config = bigquery.LoadJobConfig(
-        autodetect=True,  # Automatically infer the schema.
-        source_format=bigquery.SourceFormat.CSV,
-        skip_leading_rows=1,  # column headers
-        write_disposition=bigquery.WriteDisposition.WRITE_TRUNCATE,  # Overwrite the table
-    )
-    # Make an API request
-    load_job = bq_client.load_table_from_uri(
-        uri, table_id, job_config=job_config
-    )
-    # Waits for the job to complete.
-    load_job.result() 
-
-    #------------------------------------------ Query ops ----------------------------------------#
-
-    query = query.upper() if query else None
-
-    # List of potentially harmful operations
-    harmful_ops = ['DROP', 'DELETE', 'INSERT', 'UPDATE']
-
-    # Check if the query contains any harmful operations
-    if query and any(op in query.upper() for op in harmful_ops):
-        print("\nQuery contains harmful operations!\nusing default query.\n")
-        final_query = f"SELECT * FROM `{table_id}`"
-    else:
-        print("\nQuery is safe to be passed.\n")
-        # remove everything before the `SELECT` keyword from the received query
-        query = query[query.find("SELECT"):] if query else None
-        final_query = query.replace("FROM TABLE", f"FROM `{table_id}`") if query else f"SELECT * FROM `{table_id}`"
-    print("Final Query:\n", final_query, "\n")
-
-    query_job = bq_client.query(final_query)
-    rows = query_job.result()
-
-    # display the rows
-    data = []
-    for row in rows:
-        data.append(dict(row))
-
-    return {"message": f"Loaded {table_id} with {rows.total_rows} rows.", "data": data}
+    try:
+        result = bq_ops(fileName, query)
+        return result
+    except Exception as e:
+        return {"error": f"An error occurred: {str(e)}"}

cloud-infra/k8s/frontend-deployment.yaml

@@ -25,6 +25,6 @@ spec:
         imagePullPolicy: Always
         ports:
         - containerPort: 3000
-        env:
-        - name: APP_ENV
-          value: "production"
+        # env:
+        # - name: APP_ENV
+        #   value: "production"

docker-compose.yml

@@ -2,11 +2,14 @@ version: '3'
 services:
   frontend-service:
     build: ./frontend
-    environment:
-      - APP_ENV=development
+    # environment:
+    #   - APP_ENV=development
     ports:
       - '3000:3000'
   backend-service:
-    build: ./backend
+    build:
+      context: ./backend
+      args:
+        - CREDENTIALS_JSON=./backend/credentials.json
     ports:
       - '8000:8000'