Skip to content

Latest commit

 

History

History
78 lines (51 loc) · 2.67 KB

README.md

File metadata and controls

78 lines (51 loc) · 2.67 KB
Raw

Poetry inside Docker

This dockerfile contains the awesome new Python packaging tools Poetry, created by Sébastien Eustace.

How to use this image

$ docker run -it --rm nicklehmann/poetry:py3.7-preview-alpine 
Poetry version 1.0.0b9

USAGE
  poetry [-h] [-q] [-v [<...>]] [-V] [--ansi] [--no-ansi] [-n] <command> [<arg1>] ... [<argN>]

ARGUMENTS
  <command>              The command to execute
  <arg>                  The arguments of the command

GLOBAL OPTIONS
    [...]

AVAILABLE COMMANDS
    [...]

The image behaves like you are using poetry installed normally. So you can just append the commands and options as you normally would.

$ docker run -it --rm nicklehmann/poetry:py3.7-preview-alpine install --help
BusyBox v1.30.1 (2019-06-12 17:51:55 UTC) multi-call binary.

Usage: install [-cdDsp] [-o USER] [-g GRP] [-m MODE] [-t DIR] [SOURCE]... DEST

Copy files and set attributes

	-c	Just copy (default)
	-d	Create directories
	-D	Create leading target directories
	-s	Strip symbol table
	-p	Preserve date
	-o USER	Set ownership
	-g GRP	Set group ownership
	-m MODE	Set permissions
	-t DIR	Install to DIR

You can also base your own image on this as follows:

FROM nicklehmann/poetry:py3.7-latest-alpine

ARG STAGE

ADD poetry.lock pyproject.toml ./
RUN poetry install $(test "$STAGE" == production && echo "--no-dev") --no-interaction --no-ansi

COPY . .

CMD ["python", "yourscript.py"]

Normal installation

Instead of downloading the installation script from the internet and executing it, poetry is installed manually using virtualenv and pip. I am not a fan of piping content from the internet in my build scripts / CI and decided against that. Furthermore, it is not totally clear to me what the get-poetry.py does. Therefore, installing it like any other python CLI tool is much more clear to me.

Virtualenv

In this image, poetry installs dependencies into the system site-packages. There is no point in creating virtualenvs inside docker containers. While some might argue that this is a more natural flow for experienced python programmers, for me this is just the case if you also work with normal virtualenvs. Because I try to use docker containers everywhere, installing everything at system level makes more sense and the integration with tools like PyCharm easier.

Contribute

If you want to generate all dockerfiles after having made a change, execute the generate.sh script. It will invoke fish-pepper as a docker container, generate the dockerfiles and move them to the top-level directory.