Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/merll/docker-map

Managing Docker images, containers, and their dependencies in Python.
https://github.com/merll/docker-map

docker docker-configurations docker-containers dockerfile python

Last synced: 2 months ago
JSON representation

Managing Docker images, containers, and their dependencies in Python.

Awesome Lists containing this project

README 

        
Docker-Map

==========



Managing Docker images, containers, and their dependencies in Python.

---------------------------------------------------------------------



Project: https://github.com/merll/docker-map



Docs: https://docker-map.readthedocs.io/en/latest/



Overview

========

This package provides tools for building Docker images, create containers,

connect dependent resources, and run them in development as well as production

environments.



The library builds on functionality of the Docker Remote API client for Python,

`docker-py`. Its main target is to reduce the repetitive and error-prone code that is

required for creating and connecting containers in a non-trivial stack. It can be used

standalone for custom orchestration or for enhancing available deployment / remote

execution utilities (see [Docker-Fabric](https://github.com/merll/docker-fabric),

[Salt Container-Map](https://github.com/merll/salt-container-map)).



Containers and their dependencies are configured object-based, through Python dictionaries,

or YAML files.



Building images

===============

Writing Dockerfiles is not hard. However, it only allows for using variable context to a

limited extent. For example, you may want to re-define directory paths in your project,

without having to adjust it in multiple places; or you keep frequently reoccurring tasks

(e.g. creating system user accounts) in your Dockerfile, and would like to use templates

rather than copy & paste.



Dockerfiles

-----------

A `DockerFile` object generates a Dockerfile, that can either be saved locally or sent

off to Docker through the remote API. Supports common commands such as `addfile` (`ADD`)

or `run`, but also formats `CMD` and `ENTRYPOINT` appropriately for running a shell or

exec command.



Docker file context

-------------------

`DockerContext` generates a Docker context tarball, that can be sent to the remote API.

Its main purpose is to add files from `DockerFile` automatically, so that the Dockerfile

and the context tarball are consistent.



Creating, connecting, and running containers

============================================

This package reduces repetitions of names and paths in API commands, by introducing the

following main features:



* Automatically create, configure, and assign shared volumes.

* Automatically update containers if their shared volumes are inconsistent, their image,

  or their configuration has been updated.

* Use alias names instead of paths to bind host volumes to container shares.

* Automatically create and start containers when their dependent containers are started.



Container configuration

-----------------------

`ContainerConfiguration` objects keep the elements of a configured container. Their main

elements are:



* `image`: Docker image to base the container on (default is identical to container name).

* `clients`: Optional list of clients to run the identical container configuration on.

* `instances`: Can generate multiple instances of a container with varying host mappings;

  by default there is one main instance of each container.

* `shares`: Volumes that are simply shared by the container, only for the purpose of

  keeping data separate from the container instance, or for linking the entire container

  to another.

* `binds`: Host volume mappings. Uses alias names instead of directory paths.

* `uses`: Can be names of other containers, or volumes shared by another volume through

  `attaches`. Has the same effect as the `volumes_from` argument in the API, but using alias

  names and automatically resolving these to paths.

* `links`: For container linking. Container names are translated to instance name on the map.

* `attaches`: Generates a separate container for the purpose of sharing data with another

  one, assigns file system permissions as set in `permissions` and `user`. This makes

  configuration of sockets very easy.

* `exposes`: Configures port bindings for linked containers and on host interfaces.

* `exec_commands`: Launches commands on containers after they have been created and started.

* `create_options` and `host_config` provide the possibility to add further keyword

  arguments such as `command` or `entrypoint`, which are passed through to the `docker-py`

  client.



Container maps

--------------

`ContainerMap` objects contain three sets of elements:



1. Container names, each associated with a `ContainerConfiguration`.

2. Volumes, mapping shared directory paths to alias names.

3. Host shares, mapping host directory paths to alias names.



Clients, as defined in a `ContainerConfiguration`, can also be set globally on map level.



`ContainerConfiguration` instances and their elements can be created and used in a

dictionary-like or attribute syntax, e.g.

`container_map.containers.container_name.uses` or

`container_map.containers['container_name']['uses']`.

Volume aliases are stored in `container_map.volumes` and host binds in

`container_map.host`; they support the same syntax variations as containers.



Client configuration

--------------------

`ClientConfiguration` objects allow for a host-specific management of parameters, such as

service URL and timeout. For example, the `interfaces` property translates the `exposes`

setting for a configuration on each host into a port binding argument with the local

address.



Combining the elements

----------------------

`MappingDockerClient` applies one or multiple `ContainerMap` instances to one or

multiple Docker clients. A container on the map can easily be created with all its

dependencies by running `client.create('container_name')`.



Running the container can be as easy as

`client.start('container_name')`

or can be enhanced with custom parameters such as

`client.start('container_name', expose={80: 80})`.



If all configuration is stored on the map, creation and start are combined in

`client.startup('container_name')`.