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Build a Flask Image Management App with Google Cloud Services

This Python script implements a Flask web application for managing images using Google Cloud services. The application enables users to upload images, validating file types and storing them in Google Cloud Storage. Metadata such as filename, content type, and upload timestamp is stored in Firestore. The script also includes an HTTP function for Google Cloud Functions, allowing seamless integration with serverless architecture. The web interface presents an upload form and a grid displaying uploaded images. The script's modular structure includes functions for file validation, file upload, metadata retrieval, and HTML generation. The application demonstrates effective use of Flask, Google Cloud Storage, and Firestore for image management.

Flask Web Application for Image Management

This Python script showcases a robust Flask web application designed for image management. Utilizing Google Cloud services, it enables users to seamlessly upload images, while ensuring file type validation and secure storage in Google Cloud Storage. The integration with Firestore ensures efficient metadata storage, capturing essential details like filename, content type, and upload timestamp. With an HTTP function tailored for Google Cloud Functions, the script exemplifies adaptability within serverless architecture. This comprehensive solution serves as an excellent learning resource, providing insights into Flask, Google Cloud Storage, and Firestore. Whether you're exploring web development or need help with your Python script assignment, this script offers valuable guidance and practical implementation for effective image handling in cloud-based environments.

Block 1: Imports and Initialization

import functions_framework import os import logging from flask import Flask, request, jsonify, redirect from google.cloud import storage, firestore


  • Import necessary libraries and modules, including Flask for the web application, Google Cloud libraries for storage and Firestore, and others.
  • functions_framework is imported for handling Google Cloud Functions.

Block 2: Flask App Setup and Configuration

app = Flask(__name__) # Initialize logging logging.basicConfig(level=logging.DEBUG) # Initialize Firestore db = firestore.Client() # Initialize Cloud Storage storage_client = storage.Client() bucket_name = 'image-upload-bucket4' bucket = storage_client.bucket(bucket_name)


  • Initialize a Flask web application.
  • Set up logging for debugging purposes.
  • Initialize Firestore and Cloud Storage clients.
  • Specify the Cloud Storage bucket name.

Block 3: File Upload Function

def allowed_file(filename): ALLOWED_EXTENSIONS = {'png', 'jpg', 'jpeg', 'gif'} return '.' in filename and filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS @app.route('/upload', methods=['POST']) def upload_file(): # ...


  • Define a function (allowed_file) to check if a file has an allowed extension.
  • Define a route (/upload) that handles HTTP POST requests for file uploads.
  • Validate the uploaded file and save it to Cloud Storage.
  • Save metadata to Firestore.

Block 4: List Files Function

def list_files(): # Retrieve image metadata from Firestore images = db.collection('images').stream() files = [] for image in images: files.append(image.to_dict()) return files


  • Define a function (list_files) to retrieve image metadata from Firestore.
  • Convert Firestore documents to dictionaries and return a list of files.

Block 5: List Images Endpoint

@app.route('/list', methods=['GET']) def list_images(): return jsonify(list_files())


  • Define a route (/list) that handles HTTP GET requests for listing images.
  • Return a JSON response containing the list of files retrieved from Firestore.

Block 6: HTTP Function for Google Cloud Functions

@functions_framework.http def hello_http(request): # ...


  • Define an HTTP function (hello_http) for handling requests from Google Cloud Functions.
  • Determine the request path and method and route the request to the appropriate function (upload_file or list_images).

Block 7: HTML Content

# HTML content integrated within the Python script html_string = """ """


  • Define an HTML template string that includes a form for uploading images and a grid for displaying uploaded images.

Block 8: Flask App Execution

if __name__ == '__main__': app.run(host='', port=int(os.environ.get('PORT', 8080)))


  • Run the Flask application if the script is executed directly.
  • Bind to all available network interfaces (host='') and use the specified port or default to 8080.


In conclusion, this Flask web application not only exemplifies best practices in image management but also serves as an invaluable resource for both novice learners and those seeking assistance with Python script assignments. By seamlessly integrating technologies like Flask, Google Cloud Storage, and Firestore, the script offers practical insights into building robust cloud-based solutions. Whether you're navigating the complexities of web development or specifically require guidance for your Python script assignment, this comprehensive tutorial on ProgrammingHomeworkHelp.com provides a clear roadmap. Explore the intricacies of file validation, secure storage, and serverless architecture, and empower yourself with the skills needed to tackle real-world challenges in image handling and beyond.