A command line tool to deploy your application to Heroku without
using git push. It creates a source tarball, uploads it, builds a slug and
deploys it on Heroku. The Heroku Dev Center article
Building and Releasing Using the Platform API explains the details.
$ npm install heroku-slugify --global
heroku-slugify uses node-heroku-client
to talk to the Heroku API. You must set the HEROKU_API_KEY environment
variable, otherwise authentication will fail.
$ heroku-slugify --help
usage: heroku-slugify [-h] -a APP -v VERSION [-s SOURCE] [-t TIMEOUT]
[-i INTERVAL]
Deploy a new Heroku slug
Optional arguments:
-h, --help Show this help message and exit.
-a APP, --app APP Heroku app id
-v VERSION, --version VERSION
Version to deploy
-d DIRECTORY, --directory DIRECTORY
Name of the directory containing the files for the
tarball (default: heroku)
-s SOURCE, --source SOURCE
File name of source tarball (default: source.tar.gz)
-t TIMEOUT, --timeout TIMEOUT
Timeout for build in seconds (default: 120 s)
-i INTERVAL, --interval INTERVAL
Interval to check build status in seconds (default:
10 s)
Create a source tarball, upload it, build a slug and deploy it on Heroku.
A simple example is to deploy a Jupyter Notebook
on a Heroku Dyno. Instead of creating a Git repository and pushing it to the
heroku remote we just create three configuration files and deploy them using
heroku-slugify.
The following steps show you how to do this. You just need a Heroku account to start!
By default heroku-slugify will collect all files in the directory heroku to
create the source tarball that contains the Heroku slug configuration. So your
first step is to create this directory:
$ mkdir heroku
Now you specify the Python packages you want to install by writing them into the
heroku/requirements.txt file:
$ echo "jupyter" > heroku/requirements.txt
The next step sets the Python version your Dyno will use:
$ echo "python-3.5.1" > heroku/runtime.txt
You also need a Procfile to configure the Jupyter Notebook webserver:
$ echo "web: jupyter notebook --no-browser --ip=* --port=$PORT /tmp" > heroku/Procfile
Now you should have a heroku directory with three files in it:
$ tree heroku/
heroku/
├── Procfile
├── requirements.txt
└── runtime.txt
0 directories, 3 files
That's all you need to deploy your Heroku Dyno!
If you don't have a Heroku app you can use for testing, create one now:
$ heroku apps:create --no-remote
As explained in the configuration section you must set the HEROKU_API_KEY
environment variable, otherwise authentication will fail:
$ export HEROKU_API_KEY=<YOUR_HEROKU_API_KEY_HERE>
Now you are ready to deploy the Jupyter Notebook using heroku-slugify:
$ heroku-slugify --app <YOUR_HEROKU_APP_ID_HERE> --version 1.0
[2016-03-21 16:22:12.637] [INFO] app id: rocky-oasis-34863
[2016-03-21 16:22:12.642] [INFO] version: 1.0
[2016-03-21 16:22:12.643] [INFO] source tarball: source.tar.gz
[2016-03-21 16:22:12.643] [INFO] timeout: 120 s
[2016-03-21 16:22:12.643] [INFO] interval: 10 s
[2016-03-21 16:22:12.643] [LOG] rm -f source.tar.gz
[2016-03-21 16:22:12.653] [LOG] tar czvf source.tar.gz -C heroku/ $(ls heroku/)
[2016-03-21 16:22:12.663] [LOG] a Procfile
[2016-03-21 16:22:12.663] [LOG] a requirements.txt
[2016-03-21 16:22:12.663] [LOG] a runtime.txt
[2016-03-21 16:22:12.663] [LOG]
[2016-03-21 16:22:13.270] [LOG] curl "https://s3-external-1.amazonaws.com/heroku-sources-production/heroku.com/ef0dc77f-6047-4be8-ab25-d3154215af31?AWSAccessKeyId=AKIAJURUZ6XB34ESX54A&Signature=mcxRSHmAS6hor9ekpIVb%2B5RDBBg%3D&Expires=1458577333" -X PUT -H "Content-Type:" --data-binary @source.tar.gz
[2016-03-21 16:22:14.230] [LOG] % Total % Received % Xferd Average Speed Time Time Time Current
[2016-03-21 16:22:14.230] [LOG] Dload Upload Total Spent Left Speed
100 272 0 0 100 272 0 286 --:--:-- --:--:-- --:--:-- 286
[2016-03-21 16:22:14.230] [LOG]
[2016-03-21 16:22:15.830] [DIR] { app: { id: '8ea98634-b053-44cc-a26c-d17c966dc2a7' },
buildpacks: null,
created_at: '2016-03-21T15:22:15+00:00',
id: '704b7a99-bc7c-441f-b00c-4d54c5b36f16',
output_stream_url: 'https://build-output.heroku.com/streams/8e/8ea98634-b053-44cc-a26c-d17c966dc2a7/logs/70/704b7a99-bc7c-441f-b00c-4d54c5b36f16.log?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAJQUUZPBDLMDG7K7Q%2F20160321%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20160321T152215Z&X-Amz-Expires=86400&X-Amz-SignedHeaders=host&X-Amz-Signature=8b89368f7e5c9302950592463cad4de85e7530f07b1caf0149e529278e8b3ca4',
slug: null,
source_blob:
{ checksum: null,
url: 'https://s3-external-1.amazonaws.com/heroku-sources-production/heroku.com/ef0dc77f-6047-4be8-ab25-d3154215af31?AWSAccessKeyId=AKIAJURUZ6XB34ESX54A&Signature=QTPd7vWCQNXl0SbFrkJSpxeHAOk%3D&Expires=1458577333',
version: '1.0',
version_description: null },
status: 'pending',
updated_at: '2016-03-21T15:22:15+00:00',
user:
{ email: '[email protected]',
id: '573b6879-718b-4beb-a075-1324534e5dd8' } }
[2016-03-21 16:22:16.413] [LOG] build status: pending
[2016-03-21 16:22:27.039] [LOG] build status: pending
[2016-03-21 16:22:37.660] [LOG] build status: pending
[2016-03-21 16:22:48.288] [LOG] build status: pending
[2016-03-21 16:22:58.891] [LOG] build status: pending
[2016-03-21 16:23:09.522] [LOG] build status: pending
[2016-03-21 16:23:20.174] [LOG] build status: pending
[2016-03-21 16:23:30.806] [LOG] build status: pending
[2016-03-21 16:23:41.403] [LOG] build status: pending
[2016-03-21 16:23:52.014] [LOG] build status: pending
[2016-03-21 16:24:02.787] [LOG] build status: succeeded
Now open the Jupyter Notebook in your browser:
$ heroku open --app <YOUR_HEROKU_APP_ID_HERE>
That's it! heroku-slugify makes it as simply as possible to deploy your
packaged application to a Heroku Dyno. You can not only deploy Python packages,
but any package format a Heroku buildpack exists for.
In case you want to destroy your Heroku Dyno, run the following command:
$ heroku apps:destroy --app <YOUR_HEROKU_APP_ID_HERE>
Please note that anyone who has the URL of your Heroku Dyno has full access to the host! This is just an example and not something you should run in production!