This is a monorepo designed to host all of the apps that have been created for the Python Dash Gallery.
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.
"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
.
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.
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))
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.
- All data (csv, json, txt, etc) should be in a data folder
/apps/{DASH_APP_NAME}/data/
- All stylesheets and javascript should be in an assets folder
/apps/{DASH_APP_NAME}/assets/
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
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
│ └── ...
└── ...
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()
# 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}
# make sure your code is linted (we use black)
black . --exclude=venv/ --check
# if black is not installed
pip install black
# 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