Dash Sample Apps

This monorepo contains open-source apps demoing various capabilities of Dash and integration with the Python or R ecosystem. Most of the apps here are hosted on the Dash Gallery, which runs on the Dash Kubernetes platform and host both open-source apps and demos for Design Kit and Snapshot Engine. Reach out to get a demo of our licensed products.

Running an example app after cloning the repo

You will need to run applications, and specify filenames, from the root directory of the repository. e.g., if the name of the app you want to run is my_dash_app and the app filename is app.py, you would need to run python apps/my_dash_app/app.py from the root of the repository.

Each app has a requirements.txt, install the dependecies in a virtual environment.

Downloading and running a single app

Visit the releases page and download and unzip the app you want. Then cd into the app directory and install its dependencies in a virtual environment in the following way:

python -m venv venv
source venv/bin/activate  # Windows: \venv\scripts\activate
pip install -r requirements.txt

then run the app:

python app.py

Contributing to the sample apps repo

"DDS app" below refers to the deployed application. For example, if the deployment will eventually be hosted at https://dash-gallery.plotly.host/my-dash-app, "DDS app name" is my-dash-app.

Adding a new app

Create an app on Dash Playground. This will be the location of the auto-deployment. To do this, log into the app manager on dash-playground.plotly.host and click "initialize app".

Create a branch from master to work on your app, the name is not required to be anything specific. Switch to this branch, then navigate to the apps/ directory and add a directory for your app.

There are two options when you are naming the folder:

Make the folder have the exact same name as the Dash app name.
(Python apps only) Select any other name, but update the file apps_mapping.py with the Dash app name and the folder name you have selected.

Navigate to the directory you just created, and write a small README that only contains the name of the app. Stage the README and commit it to your branch.

See project boilerplate!

Notes on adding a new Dash for R app

Contributing an app written with Dash for R is very similar to the steps outlined above.

Make the folder have the exact same name as the Dash app name.
Ensure that the file containing your app code is named app.R.
The Procfile should contain

web: R -f /app/app.R

Routing and request pathname prefixes should be set. One approach might be to include

appName <- Sys.getenv("DASH_APP_NAME")
pathPrefix <- sprintf("/%s/", appName)

Sys.setenv(DASH_ROUTES_PATHNAME_PREFIX = pathPrefix,
           DASH_REQUESTS_PATHNAME_PREFIX = pathPrefix)

at the head of your app.R file.

run_server() should be provided the host and port information explicitly, e.g.

app$run_server(host = "0.0.0.0", port = Sys.getenv('PORT', 8050))

Making changes to an existing app

Create a new branch - of any name - for your code changes. Then, navigate to the directory that has the same name as the DDS app.

When you are finished, make a pull request from your branch to the master branch. Once you have passed your code review, you can merge your PR.

Dash app project structure

Data

All data (csv, json, txt, etc) should be in a data folder
/apps/{DASH_APP_NAME}/data/

Assets

All stylesheets and javascript should be in an assets folder
/apps/{DASH_APP_NAME}/assets/

These files will still need to be present within the app folder.

Procfile gets run at root level for deployment
- Make sure python working directory is at the app level
- Ex. web: gunicorn app:server
requirements.txt
- Install project dependecies in a virtual environment

Project boilerplate

apps
├── ...
├── {DASH_APP_NAME}         # app project level
│   ├── assets/             # all stylesheets and javascript files
│   ├── data/               # all data (csv, json, txt, etc)
│   ├── app.py              # dash application entry point
│   ├── Procfile            # used for heroku deployment (how to run app)
│   ├── requirements.txt    # project dependecies
│   └── ...                 
└── ...

Handle relative path

Assets should never use a relative path, as this will fail when deployed to Dash Enterprise due to use of subdirectories for serving apps.

Reading from assets and data folder

Img(src="./assets/logo.png") will fail at root level

Tips

Use get_asset_url()
Use Pathlib for more flexibility

import pathlib
import pandas as pd

# get relative assets
html.Img(src=app.get_asset_url('logo.png'))       # /assets/logo.png

# get relative data

DATA_PATH = pathlib.Path(__file__).parent.joinpath("data")  # /data
df = pd.read_csv(DATA_PATH.joinpath("sample-data.csv"))    # /data/sample-data.csv

with open(DATA_PATH.joinpath("sample-data.csv")) as f:  # /data/sample-data.csv
    some_string = f.read()

Developer Guide

Creating a new project

# branch off master
git checkout -b "{YOUR_CUSTOM_BRANCH}"

# create a new folder in apps/
mkdir /apps/{DASH_APP_NAME}

# push new branch
git push -u origin {YOUR_CUSTOM_BRANCH}

Before committing

# make sure your code is linted (we use black)
black . --exclude=venv/ --check

# if black is not installed
pip install black

App is ready to go!

# once your branch is ready, make a PR into master!

PR has two checkers.
1. make sure your code passed the black linter
2. make sure your project is deployed on dns playground

musicfox / dash-sample-apps