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README.md

Python Buildpack Binaries

Building the Docker Images

After every change to your formulae, perform the following from the root of the Git repository (not from builds/) to rebuild the images for each stack:

$ docker build --pull --tag heroku-python-build-cedar-14 --file $(pwd)/builds/cedar-14.Dockerfile .
$ docker build --pull --tag heroku-python-build-heroku-16 --file $(pwd)/builds/heroku-16.Dockerfile .
$ docker build --pull --tag heroku-python-build-heroku-18 --file $(pwd)/builds/heroku-18.Dockerfile .

Using the Image

You can e.g. bash into each of the images you built using their tag:

docker run --rm -ti heroku-python-build-cedar-14 bash
docker run --rm -ti heroku-python-build-heroku-16 bash
docker run --rm -ti heroku-python-build-heroku-18 bash

You then have a shell where you can run bob build, bob deploy, and so forth. You can of course also invoke these programs directly with docker run:

docker run --rm -ti heroku-python-build-heroku-18 bob build runtimes/python-2.7.15

In order to bob deploy, AWS credentials must be set up, as well as name and prefix of your custom S3 bucket (unless you're deploying to the Heroku production buckets that are pre-defined in each Dockerfile); see next section for details.

Configuration

File dockerenv.default contains a list of required env vars; most of these have default values defined in Dockerfile. You can copy this file to a location outside the buildpack and modify it with the values you desire and pass its location with --env-file, or pass the env vars to docker run using --env.

Out of the box, each Dockerfile has the correct values predefined for S3_BUCKET, S3_PREFIX, and S3_REGION. If you're building your own packages, you'll likely want to change S3_BUCKET and S3_PREFIX to match your info. Instead of setting AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY into that file, you may also pass them to docker run through the environment, or explicitly using --env, in order to prevent accidental commits of credentials.

Passing AWS credentials to the container

If you want to deploy packages and thus need to pass AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY, you can either pass them explicitly, through your environment, or through an env file.

Passing credentials explicitly

docker run --rm -ti -e AWS_ACCESS_KEY_ID=... -e AWS_SECRET_ACCESS_KEY=... heroku-python-build-heroku-18 bash

Passing credentials through the environment

The two environment variables AWS_ACCESS_KEY_IDand AWS_SECRET_ACCESS_KEY are defined in builds/dockerenv.default, without values. This will cause Docker to "forward" values for these variables from the current environment, so you can pass them in:

AWS_ACCESS_KEY_ID=... AWS_SECRET_ACCESS_KEY=... docker run --rm -ti --env-file=builds/dockerenv.default heroku-python-build-heroku-18 bash

or

export AWS_ACCESS_KEY_ID=...
export AWS_SECRET_ACCESS_KEY=...
docker run --rm -ti --env-file=builds/dockerenv.default heroku-python-build-heroku-18 bash

Passing credentials through a separate env file

This method is the easiest for users who want to build packages in their own S3 bucket, as they will have to adjust the S3_BUCKET and S3_PREFIX environment variable values anyway from their default values.

For this method, it is important to keep the credentials file in a location outside the buildpack, so that your credentials aren't accidentally committed. Copy builds/dockerenv.default to a safe location outside the buildpack directory, and insert your values for AWS_ACCESS_KEY_IDand AWS_SECRET_ACCESS_KEY.

docker run --rm -ti --env-file=../SOMEPATHOUTSIDE/s3.env heroku-python-build-heroku-18 bash