Flask Boilerplate utilizando Semantic-UI, docker, nginx y gunicorn
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| app | před 8 roky | |
| nginx | před 9 roky | |
| screenshots | před 10 roky | |
| .dockerignore | před 9 roky | |
| .gitignore | před 9 roky | |
| .pylintrc | před 9 roky | |
| Dockerfile | před 9 roky | |
| LICENSE | před 8 roky | |
| Makefile | před 9 roky | |
| README.md | před 8 roky | |
| docker-compose.yml | před 9 roky | |
| manage.py | před 9 roky | |
| requirements.txt | před 9 roky |
I didn't really like the Flask starter projects I found searching the web. I really like Flask and I use it for quite a few projects so I decided to make a clean, readable, documented starter project. I didn't include any makefile or fabric as I feel it imposes a choice to the user of this project, I rather keep things simple (even though the word is subject to interpretation).
If you have any suggestions or want to help, feel free to drop me a line at maxhalford25@gmail.com or to create an issue.
I did what most people recommend for the application's structure. Basically, everything is contained in the app/ folder.
static/ and templates/ folders. The templates/ folder contains macros, error views and a common layout.views/ folder to separate the user and the website logic, which could be extended to the the admin views.forms/ folder, as the project grows it will be useful to split the WTForms code into separate files.models.py script contains the SQLAlchemy code, for the while it only contains the logic for a users table.toolbox/ folder is a personal choice, in it I keep all the other code the application will need.manage.py. Enter python manage.py -? to get a list of existing commands.Install the requirements and setup the development environment.
make install && make dev
Create the database.
python manage.py initdb
Run the application.
python manage.py runserver
Navigate to localhost:5000.
pip install virtualenv
virtualenv venv
venv/bin/activate (venv\scripts\activate on Windows)
make install
make dev
python manage.py initdb
python manage.py runserver
The current application can be deployed with Docker in a few commands.
cd ~/path/to/application/
docker-machine create -d virtualbox --virtualbox-memory 512 --virtualbox-cpu-count 1 dev
docker-machine env dev
eval "$(docker-machine env dev)"
docker-compose build
docker-compose up -d
docker-compose run web make dev
docker-compose run web python3 manage.py initdb
Then access the IP address given by docker-machine ip dev et voilà. This is exactly how OpenBikes's API is being deployed.
The goal is to keep most of the application's configuration in a single file called config.py. I added a config_dev.py and a config_prod.py who inherit from config_common.py. The trick is to symlink either of these to config.py. This is done in by running make dev or make prod.
I have included a working Gmail account to confirm user email addresses and reset user passwords, although in production you should't include the file if you push to GitHub because people can see it. The same goes for API keys, you should keep them secret. You can read more about secret configuration files here.
Read this for information on the possible configuration options.
The MIT License (MIT). Please see the license file for more information.