https://github.com/e-alizadeh/dash-app
The code to build a containerized Dash app in Python and deploy it to Heroku.
https://github.com/e-alizadeh/dash-app
dash docker heroku-app python
Last synced: 3 months ago
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The code to build a containerized Dash app in Python and deploy it to Heroku.
- Host: GitHub
- URL: https://github.com/e-alizadeh/dash-app
- Owner: e-alizadeh
- License: mit
- Created: 2021-08-22T20:22:09.000Z (over 3 years ago)
- Default Branch: master
- Last Pushed: 2021-12-05T20:51:10.000Z (over 3 years ago)
- Last Synced: 2025-01-16T10:32:27.845Z (4 months ago)
- Topics: dash, docker, heroku-app, python
- Language: Python
- Homepage: https://demo-app-ealizadeh.herokuapp.com/
- Size: 202 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# dash-app
This repo contains the code to generate an interactive dashboard in Python using the Dash library.
# Development Environment
For development purpose, I'd like to use [conda](https://docs.conda.io/en/latest/) environment
with [Poetry](https://python-poetry.org/) as the package dependency resolver.
You can check my post below if you're curious about the reasons for this development environment.
[A Guide to Python Environment, Dependency and Package Management: Conda + Poetry](https://ealizadeh.com/blog/guide-to-python-env-pkg-dependency-using-conda-poetry)
## Create conda environment
Assuming that you have conda and poetry installed and you're in the root directory of the repo,
you need to do the following:
- Create conda environment: `conda env create -f dev-env.yaml`.
- Activate the conda environment: `conda activate `.
- Install the packages: `poetry install`
# Deployment Environment
Only for simplicity, the way I'm creating the deployment environment is different.
I've basically created a deploy-env.txt file that I will use Pip to install.
The main reason for this approach is:
- To reduce the Docker image size since conda usually makes the docker image size larger.
- To have a simpler Dockerfile
Ideally, the above deployment environment should be created in a virtual environment!!
A reminder, this is just a proof-of-concept 😁
# Running the app
## Locally (outside the container)
- Activate the environment: `conda activate dash_app`
- Go to `app/` directory.
- Run `python app.py`
- Go to http://localhost:8000/
## Run from the Docker container
- Run `docker build -t app-image .` (don't forget the last dot in the command!!)
- Run `docker run -d --name app-container -p 7000:8000 app-image`
Few points:
First time running `docker build` may take time since it downloads a docker image from DockerHub and then installs the environment.
This will be cached, so next times will be much faster.
In the `docker run`, the host port (8080) is mapped to the Docker container port 8000 (the port that Dash app is using).
Hence, to check the app, you need to go to http://localhost:7000/
### If you have any question, feel free to contact me [here](https://ealizadeh.com/contact).