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# Welcome to `repo2docker`'s documentation # Welcome to `repo2docker`'s documentation
`repo2docker` lets you **reproducibly build, run, and deploy user environment images for interactive computing and data workflows from source code repositories**. `repo2docker` lets you **reproducibly build and run user environment container images for interactive computing and data workflows from source code repositories**. Optionally, the container image can be pushed to a Docker registry.
`repo2docker` can be used to explore a repository locally by building and executing the Also, `repo2docker` is the tool used to build container images for [JupyterHub](https://jupyterhub.readthedocs.io/en/stable/) and the tool used by [BinderHub](https://binderhub.readthedocs.io) to build images on demand.
constructed image of the repository, or as a means of building images that
are pushed to a Docker registry. It is the tool used by [BinderHub](https://binderhub.readthedocs.io) to build images on demand.
::::{grid} ::::{grid}
:::{grid-item-card} 🔧 Build reproducible data science environments from repositories :::{grid-item-card} 🔧 Build reproducible data science environments from repositories
@ -14,23 +12,25 @@ Build a reproducible data science environment as a Docker image and execute code
Push environment images to a Docker registry for re-use in data science environment services like [JupyterHub](https://jupyterhub.readthedocs.io) or [a Binder instance](https://mybinder.org), or for other communities to build upon your base environment. Push environment images to a Docker registry for re-use in data science environment services like [JupyterHub](https://jupyterhub.readthedocs.io) or [a Binder instance](https://mybinder.org), or for other communities to build upon your base environment.
::: :::
:::{grid-item-card} ☁️ Host repositories in many providers :::{grid-item-card} ☁️ Host repositories in many providers
Host repositories in a provider like GitHub, an open science repository like [Zenodo](https://zenodo.org) or [Figshare](https://figshare.com), a hosted data platform like a [Dataverse installation](https://dataverse.org/), an archive like the Host repositories in: a Git server like [GitHub](https://github.com/) or [GitLab](https://gitlab.com/), an open science repository like [Zenodo](https://zenodo.org) or [Figshare](https://figshare.com), a hosted data platform like a [Dataverse installation](https://dataverse.org/), an archive like the
[Software Heritage Archive](https://archive.softwareheritage.org). [Software Heritage Archive](https://archive.softwareheritage.org).
::: :::
:::: ::::
## What is a user image and why would I build one with `repo2docker`? ## What is a user environment container image and why would I build one with `repo2docker`?
A **user image** contains the entire software environment that a user may access from an interactive data science session. For example, it might contain many **programming languages**, **software for data analysis**, or even **content files and datasets** available to anybody that accesses that environment. User images are built with [Docker](https://www.docker.com/), a standard open source tool for defining, building, and deploying images. A **user environment container image** contains the entire software environment that a user may access from an interactive data science session. For example, it might contain many **programming languages**, **software for data analysis**, or even **content files and datasets** available to anybody that accesses that environment. Container images are built with [Docker](https://www.docker.com/), a standard open source tool for defining, building, and deploying images.
Many data science platforms and services like [JupyterHub](https://jupyterhub.readthedocs.io) and [Binder](https://mybinder.org) launch interactive data science sessions **with a user image attached**, meaning that the user gains access to whatever is in the image. In short, this allows somebody to define and build the user image one time, in a way that users can reproducibly re-use many times. Many data science platforms and services like [JupyterHub](https://jupyterhub.readthedocs.io) and [Binder](https://mybinder.org) launch interactive data science sessions **with a user environment container image attached**, meaning that the user gains access to whatever is in the container image. In short, this allows somebody to define and build the user image one time, in a way that users can reproducibly re-use many times.
Dockerfiles are the standard way that Docker images are defined[^use-dockerfile]. `Dockerfile`s are the standard way that Docker container images are defined.
However, **building images with Dockerfiles takes expertise and time** that is outside the scope of a data scientist or researcher. `repo2docker` makes this workflow more accessible by using community-standard configuration files for computational reproducibility to build user images. However, **building images with `Dockerfile`s takes expertise and time** that is outside the scope of a data scientist or researcher. `repo2docker` makes this workflow more accessible by using community-standard configuration files for computational reproducibility to build user environment container images.
In short, `repo2docker` is a tool to reproducibly build, run, and deploy these user environment Docker images for data science from source code repositories. ```{note}
You can still use a `Dockerfile` with `repo2docker` if you really want to!
```
[^use-dockerfile]: That said, you can still use a Dockerfile if you really want to! In short, `repo2docker` is a tool to reproducibly build and run these user environment container images for data science from source code repositories.
## How `repo2docker` works ## How `repo2docker` works
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[swhid]: https://docs.softwareheritage.org/devel/swh-model/persistent-identifiers.html [swhid]: https://docs.softwareheritage.org/devel/swh-model/persistent-identifiers.html
Please report [Bugs](https://github.com/jupyterhub/repo2docker/issues), Please report [bugs](https://github.com/jupyterhub/repo2docker/issues),
[ask questions](https://gitter.im/jupyterhub/binder) or [ask questions](https://gitter.im/jupyterhub/binder) or
[contribute to the project](https://github.com/jupyterhub/repo2docker/blob/HEAD/CONTRIBUTING.md). [contribute to the project](https://github.com/jupyterhub/repo2docker/blob/HEAD/CONTRIBUTING.md).
## Get started with repo2docker ## Get started with `repo2docker`
This tutorial walks you through setting up repo2docker, building your first environment image, and running it locally with Docker. This tutorial walks you through setting up `repo2docker`, building your first environment image, and running it locally with Docker.
```{toctree} ```{toctree}
:maxdepth: 2 :maxdepth: 2
@ -63,7 +63,7 @@ This tutorial walks you through setting up repo2docker, building your first envi
start start
``` ```
## Learn how to use repo2docker ## Learn how to use `repo2docker`
Our user guide provides all of the information you need to configure and deploy the environment image you want. Our user guide provides all of the information you need to configure and deploy the environment image you want.
@ -72,7 +72,7 @@ Our user guide provides all of the information you need to configure and deploy
use/index use/index
``` ```
## Contribute to repo2docker ## Contribute to `repo2docker`
Our contributor guide describes how you can follow along with the project, learn how to collaborate with our open team, and learn developer workflows and information. Our contributor guide describes how you can follow along with the project, learn how to collaborate with our open team, and learn developer workflows and information.