This is repository for the final project of the course Startup Campus.
The primary goal of this project is to make backend for marketplace website. The website will be used to sell and buy products. The website will have a lot of features, but the main ones are:
- Authentication
- Home
- Products
- Cart
- Orders
- Profile
This project comes with a requirement document requirement.
Check documentation for more details. Documentation
You will need docker and docker-compose.
First, clone the project:
$ git clone https://github.com/Cizz22/final-project.git <my-project-name>
$ cd <my-project-name>
Then install dependencies and check that it works
$ make install # Install the pip dependencies on the docker container
$ make daemon # Run the container containing your local python server
If everything works, you should see the available routes here.
in this project you will need storage for images, so you need to create a folder using command
$ make server.storage
after that, you can migrate the database
$ make database.upgrade
You can display availables make commands using make
.
While developing, you will probably rely mostly on make server.start
; however, there are additional scripts at your disposal:
make <script> |
Description |
---|---|
help |
Display availables make commands |
server.install |
Install the pip dependencies on the server's container. |
server.start |
Run your local server in its own docker container. |
server.daemon |
Run your local server in its own docker container as a daemon. |
server.bash |
Connect to server to lauch commands |
server.stop |
Stop server in its docker container |
server.logs |
Display server logs |
server.storage |
Make storage file |
server.nginx |
Run nginx container with its nginx conf file |
database.connect |
Connect to your docker database. |
database.migrate |
Generate a database migration file using alembic, based on your model files. |
database.upgrade |
Run the migrations until your database is up to date. |
database.downgrade |
Downgrade your database by one migration. |
database.seeder |
Run database seeder |
database.drop |
Drop all table |
test |
Run unit tests with pytest in its own container. |
The database is in PostgreSql.
Locally, you can connect to your database using :
$ make database.connect
The application structure presented in this boilerplate is grouped primarily by file type. Please note, however, that this structure is only meant to serve as a guide, it is by no means prescriptive.
.
├── migrations # Database's migrations settings
│ └── versions # Database's migrations versions generated by alembic
├── src # Application source code
│ ├── models # Python classes modeling the database
│ │ ├── abc.py # Abstract base class model
│ │ └── user.py # Definition of the user model
│ ├── repositories # Python classes allowing you to interact with your models
│ │ └── user.py # Methods to easily handle user models
│ ├── resources # Python classes containing the HTTP verbs of your routes
│ │ └── user.py # Rest verbs related to the user routes
│ ├── routes # Routes definitions and links to their associated resources
│ │ ├── __init__.py # Contains every blueprint of your API
│ │ └── user.py # The blueprint related to the user
│ ├── seeder # Database seeder
│ │ ├── __init__.py # Contains main seeder
│ │ └── user.py # User seeder
│ ├── util # Some helpfull, non-business Python functions for your project
│ │ └── parse_params.py # Wrapper for the resources to easily handle parameters
│ ├── config.py # Project configuration settings
│ └── server.py # Server configuration
└── test # Unit tests source code
To develop locally, here are your two options:
$ make server.start # Create the containers containing your python server in your terminal
$ make server.daemon # Create the containers containing your python server as a daemon
The containers will reload by themselves as your source code is changed.
You can check the logs in the ./server.log
file.
To add a unit test, simply create a test_*.py
file anywhere in ./test/
, prefix your test classes with Test
and your testing methods with test_
. Unittest will run them automaticaly.
You can add objects in your database that will only be used in your tests, see example.
You can run your tests in their own container with the command:
$ make test