Automatic Program Corrector Backend is a RESTful back-end server built with Python's FastAPI framework. It provides functionality that allows for automatically generating unit test cases for uploaded files. Data is persisted in a MySQL database.

1. Make sure Python 3.6+ is installed on your machine, as well as pip. Instructions on how to install pip

Prerequisite: have docker installed on your machine.

2. Make sure pynguin is in the home directory

   cd ~
   git clone https://github.com/se2p/pynguin.git

3. Create input, output, and package directories. Create package/package.txt

   cd ~/pynguin
   mkdir input output package
   touch package/package.txt

4. Create input, output, and package volumes

   docker volume create input
   docker volume create output
   docker volume create package
   # run "docker volume ls" to check that volumes got created successfully

5. Containerize the app by running the Makefile script

   make # make docker
   # OR RUN THE BELOW INSTEAD
   docker build \
   	  -t $(IMAGE):$(VERSION) . \
   	  -f ./docker/Dockerfile --no-cache
   	  

6. Check your docker Image container Tag for Pynguin container

   docker image ls
      # output would be something like the below

   REPOSITORY TAG IMAGE ID CREATED SIZE appname latest a4962c112cd9 6 days ago 169MB pynguin 9ccbdc17 203050f9142a 6 days ago 153MB hello-app latest 518ae29ba4ea 6 days ago 169MB ubuntu latest a457a74c9aaa 3 weeks ago 65.6MB

7. Run Pynguin in docker container ( for testing on our terminal/CMD_PROMPT)

   docker run \
       -v ~/pynguin/input:/input:ro \
       -v ~/pynguin/output:/output \
       -v ~/pynguin/package:/package:ro pynguin:<DOCKER_IMAGE_TAG> --project-path /input \
       --output-path /output \
       --module-name PYTHON_FILE_NAME -v

8. Create a virtual environment and activate it by executing the following commands:

   cd APC_backend # navigate to project directory
   pip install virtualenv
   virtualenv env # create a virtual environment
   source env/bin/activate # activate the virtual environment

9. To install the required dependencies, execute the following command:

   pip install -r requirements.txt # installs required dependencies
   

10. From APC_backend directory, run the following command:

    mkdir input output

11. Download MySQL Community Server and MySQL Workbench

12. Create a root user account. Note down your host name, user, and password

13. Import the database.sql file from MySQL Workbench Server settings.

14. To create .env file to store the server's environment variables, execute the following commands:

touch .env # creates .env file
vim .env # use vim or open the .env file in a code editor 

15. Set the values for the following host, user, and password keys:

host=HOST_NAME # typically host is localhost 
user=USER_NAME
password=PASSWORD
db=DB_NAME

16. In file PynguinAPI.sh, set the DOCKER_IMAGE_TAG variable to the docker image tag for Pynguin container

# ...
DOCKER_IMAGE_TAG="<PYNGUIN_DOCKER_IMAGE_TAG>"
# ...

17. To run the app, execute the following command on your terminal:

uvicorn main:app --reload # note on this method of running the server. 
# The server automatically reloads when a change is done in the back-end code
# An alternative way is to run the main.py Python file --> python3 main.py

18. Notes:

• The server automatically runs on http://localhost:8000

• To access the API documentation (both documentations provide the same functionaltiy, one might just have a preference):

  a. Swagger API Documentation: http://localhost:8000/docs

  b. ReDoc Documentation: http://localhost:8000/redoc

1. Download ngrok

2. Unzip to install:

   unzip /path/to/ngrok.zip

3. Connect your account:

   ./ngrok authtoken <token>

4. To start a HTTP tunnel forwarding to your local port PORT_NUMBER, run this next:

   ./ngrok http PORT_NUMBER

• note: To call fetch() API from the front-end when testing locally we need to sign our backend with an SSL/TLS certificate marking it secure (https). An easy way to do that is by using ngrok!