meep-backend

Setup

Docker-compose

1. Install Docker. Compose should be bundled with it.
2. Start the containers: docker-compose up --build -d.
3. Seed the development database: docker container exec meep-backend_api_1 python /meep/api/src/db_operations.py reset dev. You should only need to do this the first time you run the app.
4. In a browser, or some other client, type localhost/api/locations. If you see a bunch of json data, it worked!

Useful docker commands

• Shell into database:

  docker container exec -it meep-backend_db_1 psql -U meep -h meep-backend_db_1 -d meep_api

  password: supersafe

• Shell into api container

  docker container exec -it meep-backend_api_1 /bin/ash

• Shell into nginx container

  docker container exec -it meep-backend_web_server_1 /bin/bash

• view log files (similar for api)

  docker logs meep-backend_web_server_1

Run only the api container with Docker:

1. Install Docker
2. Build docker image from dockerfile:

   docker build -t meep-backend:gunicorn src

3. Create and run a container from the image:

   docker run -p 8001:8000 meep-backend:gunicorn

   or to allow live editing of the code in the container, do

   docker run -p 8001:8000 -v $(pwd)/src:/meep/api/src meep-backend:gunicorn

   • On windows, the command for live editing probably won't work. instead of $(pwd)/src on the left side of the bind mount, you will have to provide an absolute path to the project folder that contains the Dockerfile (src at the time of writing). After that, there is a chance that you will get a different error. Restart docker and try again. It usually works on the second attempt. Please note that this is a temporary workaround while we find a less annoying way to run the project on windows.
4. In a browser, try typing http://localhost:8001/locations to see if it worked.

Unix without docker

1. Install python

    sudo apt-get install python3

2. Install virtualenv

   
    sudo apt install virtualenv

3. clone the master branch

   
    git clone git@github.com:codeforkansascity/meep-backend.git

4. move into project root directory

   
    cd meep-backend

5. create a virtual environment in the project root directory

   
    virtualenv venv

6. activate the virtual environment

   
    source venv/bin/activate

7. pip install requiremnets

   
    pip install -r src/requirements.txt

8. Install sqlite3

   
    sudo apt install sqlite3

9. create a sqlite database touch dev.db

10. set dev database environment variable export DEV_DATABASE_URL=sqlite:///dev.db

11. Open the database in sqlite with sqlite3 dev.db; check to see if it created the tables with .tables

12. try to display data from a table select * from projects; you should see a list of projects display

13. set flask environment variable to development

    export FLASK_ENV=development

14. Set flask app environment variable

    export FLASK_APP="src/app:create_app()"

15. run the app

    flask run

16. test to see if it worked: in a browser, type localhost:5000/projects you should see some json containing project data

Windows without docker

1. Install python
2. Install pip
3. Install virtualenv
4. clone the master branch
5. create a virtual environment in the project root directory
6. activate the virtual environment venv\Scripts\activate
7. pip install requirements pip install -r requirements.txt
8. set dev database environment variable set DEV_DATABASE_URL=sqlite:///dev.db
9. set flask environment variable to development

   set FLASK_ENV=development

10. set flask app variable to point towards app.py

    set FLASK_APP=src\app.py

11. run the app

    flask run

12. test to see if it worked: in a browser, type localhost:5000/projects you should see some json containing project data

Tests

1. Start the containers as normal: docker-compose up --build -d
2. Run pytest in the api container to run all discovered tests: docker exec -it meep-backend_api_1 pytest
   • Optionally, shell into the api container as normal (docker container exec -it meep-backend_api_1 /bin/ash) and then enter the pytest command
     • Add -v command line argument for more detailed view of both failing and passing tests: pytest -v
     • Only run tests in a specific package by specifying its directory: pytest ../tests/unit
     • Only run tests in a specific module by specifying its directory and filename: pytest ../tests/unit/test_models.py
     • Only run a specific test in a specific module: pytest ../tests/unit/test_models.py::test_insert_location

meep Shell Script

• Checkout the meep shell script in the root directory for some shorter ways of running some of these commands with either the shell script itself or by copying the shorthand aliases into your dev environment.