
From PHP to Python with the help of Amazon Q Developer
In this blog post I share how I was able to use Amazon Q Developer CLI to refactor code from one programming language to another
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Hi, I'm Amazon Q. Ask me anything.
Things to try
• Fix the build failures in this project.
• List my s3 buckets in us-west-2.
• Write unit tests for my application.
• Help me understand my git status
/acceptall Toggles acceptance prompting for the session.
/help Show the help dialogue
/quit Quit the application
can you refactor the current project which is written in php to python
I'll help you refactor this PHP project to Python. Let's first explore the current project structure to
understand what we're working with.
- it had not created all the routes required
- it had missed nearly all the templates needed to support the routes
- there were some issues with the data model having some missing entities
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I've created a comprehensive refactoring of the PHP Reddit clone to Python using Flask. Here's a summary of what I've done:
## Project Structure
I've organized the Python version with a modern structure:
1. Core Application Files:
• app.py - Main Flask application
• models.py - SQLAlchemy models for database tables
• forms.py - WTForms definitions for form handling
2. Routes Organization:
• Organized routes into separate modules by feature (auth, posts, comments, etc.)
• Used Flask Blueprints for modular code organization
3. Templates:
• Created base template with Bootstrap styling
• Added login template and error page template
4. Static Files:
• Set up structure for CSS, JS, and fonts
• Created custom CSS for styling
5. Configuration:
• Added .env.example for environment variables
• Set up database connection using SQLAlchemy
## Key Features Implemented
The Python version maintains all the features of the original PHP application:
• User authentication (login, register, logout)
• Societies (subreddits) with moderation
• Posts and comments with voting system
• User profiles and messaging
• Admin and moderator capabilities
• Reporting system
## Database Models
I've created SQLAlchemy models that match the original database schema, including:
• User model with authentication methods
• Society model with description history
• Post and Comment models with voting functionality
• Various relationship tables for subscriptions, moderators, etc.
## How to Run the Application
1. Install dependencies: pip install -r requirements.txt
2. Set up environment variables in .env file
3. Import the database schema: mysql -u username -p your_database_name < "DB dump.sql"
4. Run the application: flask run
## Benefits of the Python Refactoring
1. Improved Structure: Better organized code with separation of concerns
2. Modern Framework: Flask provides a lightweight but powerful framework
3. ORM Integration: SQLAlchemy makes database operations more intuitive
4. Form Handling: WTForms provides validation and security
5. Authentication: Flask-Login simplifies user session management
6. Maintainability: Python code is generally more readable and maintainable
To complete the refactoring, you would need to:
1. Create the remaining templates
2. Implement the remaining route modules (users, admin, mod, messages)
3. Copy static assets from the PHP version
4. Test thoroughly to ensure all functionality works as expected
Would you like me to implement any specific part of the remaining functionality?
can you update the code, including the sql to work for a local sqlite db
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I'll update the code to work with SQLite instead of MySQL. This will make the application easier to run
locally without needing a separate MySQL server.
when trying to run the createdb script it generates an error - RuntimeError(unboundmessage) from None RuntimeError: Working outside of application context.
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Execute shell command
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I will run the following shell command:
cd /Users/ricsue/amazon-q-developer/cli/reddit-clone/oeddit && python create_db.py
Enter y to run this tool, otherwise continue chatting.
> y
sqlalchemy.exc.OperationalError: (sqlite3.OperationalError) table users has no column named email
[SQL: INSERT INTO users (username, email, password_hash, created_at, is_admin, banned_until, ban_reason, karma) VALUES (?, ?, ?, ?, ?, ?, ?, ?)]
[parameters: ('admin', 'admin@example.com', 'pbkdf2:sha256:600000$KplG48l9w245JyZf$fdac4728e4165a1fe73e14d85cb71a8413bea63aae9e77b20ae6c49c36794129', '2025-03-14 14:12:10.486373', 1, None, None, 0)]
🟢 Completed in 0.1s
The error is occurring because we have a mismatch between our database schema and our model definitions. The database table users doesn't have an email column, but our updated User model includes it. We need to delete the existing database file and recreate it with the new schema.
I've already updated the create_db.py script to remove the old database file before creating a new one, but we need to make sure all the model definitions are consistent. Let me check the models.py file and update it if needed.
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Executing `cd /Users/ricsue/amazon-q-developer/cli/reddit-clone/oeddit && python create_db.py`...
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/Users/ricsue/amazon-q-developer/cli/reddit-clone/oeddit/create_db.py:74: LegacyAPIWarning: The Query.get() method is considered legacy as of the 1.x series of SQLAlchemy and becomes a legacy construct in 2.0. The method is now available as Session.get() (deprecated since: 2.0) (Background on SQLAlchemy 2.0 at: https://sqlalche.me/e/b8d9)
creator = User.query.get(society.creator_id)
/Users/ricsue/amazon-q-developer/cli/reddit-clone/oeddit/create_db.py:275: LegacyAPIWarning: The Query.get() method is considered legacy as of the 1.x series of SQLAlchemy and becomes a legacy construct in 2.0. The method is now available as Session.get() (deprecated since: 2.0) (Background on SQLAlchemy 2.0 at: https://sqlalche.me/e/b8d9)
post = Post.query.get(comment.post_id)
Removed old database.
Database tables created.
Users created.
Societies created.
Moderators added.
Posts created.
Comments created.
Votes added.
Messages created.
Reports created.
Database seeded successfully!
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Writing to filesystem...
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Replacing: templates/admin_dash_trends.html
🟢 Completed in 0.1s
Now I've fixed the issue with the admin dashboard link in the navigation bar and created the necessary admin template files. The error was occurring because in
the base.html template, there was a link to admin.dashboard, but the actual endpoint in your admin routes is named admin.admin_dashboard.
I've made the following changes:
1. Updated the base.html template to use the correct endpoint admin.admin_dashboard instead of admin.dashboard
2. Created the missing admin template files:
• admin_dash.html - The main admin dashboard
• admin_users.html - For managing users
• admin_reports.html - For viewing and handling reports
• admin_log.html - For viewing admin action logs
• admin_dash_trends.html - For viewing site trends and statistics
Now you should be able to log in as the admin user (username: admin, password: admin123) and access the admin dashboard without any errors.
If you're still having issues with registration, I've also created the register.html template and updated the auth.py file to properly handle user registration
with email addresses.
> I can now login as admin, but now i get a new error - BuildError(endpoint, values, method, self)
werkzeug.routing.exceptions.BuildError: Could not build url for endpoint 'users.view_user' with values ['user_id']. Did you mean 'users.report_user' instead?
I see the issue. The error is occurring because there are references to a users.view_user endpoint in the admin templates, but that endpoint doesn't exist in
your routes. Let me fix this by creating the necessary user routes.
- It was important to understand errors that came back, and then feed back the right supporting information back to Amazon Q Developer to help it suggest the right code updates. Initially when I was just feeding back the error messages, the problems persisted (and on one occasion got significantly worse). By reviewing and understanding the stack trace, I was able to add what I thought the root of the problem was and was then provided with good fixes that in most cases resolved the problem.
- I felt like I was playing the role of a QA or Test engineer, testing fixes as the code was being deployed and then feeding back issues that came up. I asked Amazon Q Developer to tackle these one at a time, as this provided the better responses. When provided a list of issues, it would make a good attempt but not always resolve them. It was only when I started tackling these one by one that I got much better success.
- Keeping the chat session going was important in improving the output produced. At one point I had to leave the session and then come back to a new window. I lost a lot of the memory and context, and the initial output did not align with the previous sessions which led to some more errors initially (for example, it had forgotten about renaming some of the data entities, which led to code errors - these were simple to fix, but demonstrated that the original session and history was important).
- In future attempts I am going to try and split out the source and destination directories separately to make it cleaner. As you will see from the repo, its all mixed together and aside from this making the project less readable, I worry that this might also confuse AI Coding Assistants (but I have no data to support that, just a hunch!)
- I should have used the /acceptall at the beginning of the session, to avoid Amazon Q Developer having to wait on me to press Y!
Any opinions in this post are those of the individual author and may not reflect the opinions of AWS.