Assignments > HW2: Build Your Second Feature

Due on Fri, 12/08 @ 11:59PM. 20 Points.

I. Introduction

For your second homework assignment, you will be creating one more feature for the class app. Please take a look at the Issue Tracker and assign yourself a task.

By the end of HW2, we should have the foundation of a functioning app that allows people to browse and join groups!

II. Background Information

1. Docker Setup

Pull the latest changes to your local repo.

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git checkout main
git pull

Make sure that…

1. Docker is running and
2. Any old containers that use port 8000 are stopped

Then, build the images / containers:

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docker compose up

This command tells Docker to read the instructions in the compose.yaml file and build 4 containers:

You should only need to run docker compose up once. Subsequently, you can just start and stop your containers from the CLI or via the Docker dashboard.

If your containers built successfully, visit http://localhost:8000 and behold! The app running!

The easiest way to stop and start your container is by using the Docker Dashboard.

2. Fast API (Python) Development Notes

Server Command Line Cheatsheet

SQLAlchemy Cheat Sheet

See Lab 8

Viewing the Log Files (for Uvicorn Web App)

If you run into server errors, navigate to the Docker Dashboard, navigate to the app-server-1 container, and click on it to see the server log file.

Where to put stuff

Testing Your FastAPI Endpoints

Web Tester

To test your endpoints manually, navigate to http://localhost:8000/docs and tinker with your tests.

Automated Tests

All automated tests that interact with the database should be created in the src/db/tests directory. Because there is some “magic” involved with the pytest testing framework, we wanted to share a few notes:

1. conftest.py is run before every test. In this folder, a bunch of fixtures are defined, primarily to populate a test database with fake data. These fixtures include:
   • testing_setup_teardown(), which is run on every test setup and teardown the test database and to create a async database session.
   • users() which creates a bunch of fake users.
   • tasks() which creates a bunch of fake tasks.

conftest.py also has a global object called tester which has a reference to:

• current_user: the fake, logged in user
• client: the test client
• db_async_session: an asynchronous database session

To see an example of how to use the tester object, take a look at src/tests/db/test_tasks.py

Feel free to create additional fixtures and / or helper functions in the conftest.py file.

Running the tests

To run all of the tests, execute the following command:

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docker exec -it app-server-1 poetry run pytest

Or, you can test specific modules and specific functions, by including the python file at the end.

• The “-v” flag will give you more specific feedback in your test results
• the “-s” flag will output all print statments
• the “-W ignore::DeprecationWarning” statement will suppress deprecation warnings

Here’s an example that tests all of the functions in one file:

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docker exec -it app-server-1 poetry run pytest tests/db/test_tasks.py -vs -W ignore::DeprecationWarning

3. Node / React Development Notes

Node Command Line Cheatsheet

Debugging while using Parcel

Recall that Parcel’s job is to compile a “production version” of your react application everytime you save. Give this:

1. Turn off your autosave (so that you don’t confuse parcel).
2. If changes to your react app aren’t being reflected in the UI, try deleting the build directory and then making a small change to one of your React files to trigger a rebuild.

4. Database Development Notes

To access your database and issue queries to PostgreSQL, do the following from the command line:

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docker exec -it app-db-1 bash

Then, once you’re on the database server’s bash shell, connect to the database as follows:

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psql -U app_user -d app_db

Once you’re on the PostgreSQL shell and connected to the app_db database, you can issue SQL commands. For instance:

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select * from users;

When you want to exit the psql shell, type: \q

SQL Cheat Sheet

See Lab 8

Rebuilding the Database with Fake Data

To rebuild the database with fake data, issue the following command:

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docker exec -it app-server-1 poetry run python db/populate.py

III. Submitting Homework 2

You will be submitting Homework 2 by making a pull request that adheres the guidelines below:

• Ensures all of the code quality checks pass
• Ensures all of the tests pass
• Ensures you’re using descriptive commit messages
• Ensures that your pull request summary text is descriptive

A note on GitHub workflows

Every time you make a pull request, a GitHub Workflow is triggered (see the .github/workflows/pr.yml file). This is a first round check to ensure that code formatting standards have been followed and that all of the tests pass.

This workflow file checks the following:

1. Code quality (by invoking src/scripts/check.sh)
2. Tests (by invoking src/scripts/test-ui.sh and scripts/test-server.sh

Given this, please ensure that you have already formatted your code and run all of the tests before creating a pull request.

If you made changes to a python file, please run (from src directory):

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bash scripts/fix-python.sh
docker exec -it app-server-1 bash scripts/test-server.sh

If you made changes to an HTML, CSS, or JavaScript file, please run (from the ui directory):

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npm run lint
npm run format
npm run check

All checks must pass before your pull request is reviewed.