kopia lustrzana https://github.com/jupyterhub/repo2docker
improving readmes for tests
rodzic
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Binder Directory
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----------------
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top-level Dockerfile will be ignored if binder directory exists.
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@ -1,8 +1,9 @@
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Conda - Mixed Requirements
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--------------------------
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An ``environment.yml`` takes precedence over ``requirements.txt``.
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To install Python packages into a conda environment with pip, use the ``pip`` key in ``environment.yml``:
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An ``environment.yml`` file takes precedence over ``requirements.txt``.
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To install Python packages into a conda environment with pip, use the
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``pip`` key in ``environment.yml``:
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.. sourcecode:: yaml
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@ -1,5 +1,10 @@
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Conda Environment
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-----------------
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Conda Environment and Python 2
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------------------------------
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Conda environments files may allow for more complex builds and dependencies. You
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can specify them in the standard `environment.yml` files.
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``environment.yml`` is the standard method for defining environments with the
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Anaconda (conda) distribution. Conda environment files may allow for more
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complex builds and dependencies than are possible with a single
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``requirements.txt`` file.
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This example shows how to define a Python 2 environment with Anaconda. You can
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define any version of Python that Anaconda supports.
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Conda Environment
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-----------------
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Conda environments files may allow for more complex builds and dependencies. You
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can specify them in the standard `environment.yml` files.
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``environment.yml`` is the standard method for defining environments with the
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Anaconda (conda) distribution. Conda environment files may allow for more
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complex builds and dependencies than are possible with a single
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``requirements.txt`` file.
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Binder Directory
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----------------
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A top-level Dockerfile will be ignored if a ``binder`` directory exists.
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@ -1,7 +1,9 @@
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Docker - Specifying dependencies
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--------------------------------
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You can specify dependencies with Dockerfiles, which may be more flexible
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in running non-standard code. We recommend sourcing your Dockerfile from
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one of the Jupyter base images. In this case, we use a stripped-down image
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that has minimal dependencies installed.
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You can use a Dockerfiles to use a "source" Docker image that has a pre-built
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environment. This may be more flexible in running non-standard code.
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We recommend sourcing your Dockerfile from one of the Jupyter base images
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to ensure that it works with JupyterHub. In this case, we use a stripped-down
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image that has minimal dependencies installed.
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@ -4,4 +4,5 @@ Docker - Legacy Dockerfiles
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This demonstrates the Dockerfile syntax that was often found in the first
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version of Binder. It sources the ``andrewosh`` Docker image, which
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contained many different dependencies, then installs Julia. We encourage
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users to source one of the Jupyter base images as they are more streamlined.
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users to source one of the Jupyter base images as they are more streamlined,
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reliable, and efficient.
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@ -2,6 +2,8 @@ Docker - Running scripts
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------------------------
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It's possible to run scripts using Docker in your build. In this case, we run
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a simple shell script after installing dependencies. However, we recommend
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that you see if it's possible to accomplish what you want using ``apt`` and
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``postInstall`` files, and use Dockerfiles only when necessary.
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a simple shell script after installing dependencies.
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While it's possible to run code with Dockerfiles, we recommend
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that try accomplishing the same thing with ``apt.txt`` and
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``postBuild`` files. Only use Dockerfiles when necessary.
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@ -1,7 +1,17 @@
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Julia - REQUIRE
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---------------
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The simplest way to specify dependencies in Julia, a REQUIRE file simply
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lists the names of packages. Each one will be installed but not pre-compiled.
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In this case, we also specify python dependencies with an ``environment.yml``
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file.
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To specify dependencies in Julia, include a REQUIRE file that lists the names
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of packages you'd like to be installed. For example:
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```
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PyPlot
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IJulia
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DataFrames
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```
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Each one will be installed but **not** pre-compiled. If you'd like to
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pre-compile your Julia packages, consider using a ``postBuild`` file.
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Note that this example also specifies Python dependencies with an
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``environment.yml`` file.
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@ -2,4 +2,9 @@ System - APT Packages
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---------------------
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It is possible to install packages using the Shell with the ``apt.txt`` file.
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In this case we install ``gfortran`` which does not have an easy Python install.
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This allows you to install libraries that aren't easy to install with package
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managers such as ``pip`` or ``conda``. This can be useful if you must install
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something that depends on a low-level library already being present.
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In this case we install ``gfortran``, which does not have an easy Python
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install.
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Binder Directory
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----------------
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Binder Directory for configuration files
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----------------------------------------
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top-level environment.yml will be ignored if binder directory exists.
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If a directory called ``binder/`` exists in the top level of the repository,
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then all configuration files that are **not** in ``binder/`` will be ignored.
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This is particularly useful if you have a ``Dockerfile`` defined in a
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repository, but don't want ``repo2docker``to use it for building the
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environment.
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@ -2,4 +2,4 @@ Python - Requirements.txt
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-------------------------
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The simplest way to specify Python packages is with a ``requirements.txt`` file
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that is compatible with ``pip install``.
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that is compatible with ``pip install``. In this case, we install ``numpy``.
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@ -3,5 +3,6 @@ System - Post-build scripts
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It is possible to run scripts after you've built the environment specified in
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your other files. This could be used to, for example, download data or run
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some configuration scripts. For example, this will download and install a
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Jupyter extension.
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some configuration scripts.
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In this example, we download and install a Jupyter Notebook extension.
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System - Specifying runtime environments
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----------------------------------------
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You can specify runtime environments (such as Python 2 or 3) with a
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``runtime.txt`` file.
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@ -2,8 +2,19 @@ System - Specifying runtime environments
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----------------------------------------
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You can specify runtime environments (such as Python 2 or 3) with a
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``runtime.txt`` file.
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``runtime.txt`` file. To do so, include a line of the following form in
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your ``runtime.txt`` file:
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```
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python-N
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```
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Where ``N`` is either ``2`` or ``3``. If ``N==2``, Python 2.7 will be used.
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If ``N==3``, Python 3.6 will be used.
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This is an example that selects Python 3. Currently you can not use
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this to select a sepcific version of Python 3 (e.g. 3.4 vs 3.6). If you
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this to select a specific version of Python 3 (e.g. 3.4 vs 3.6). If you
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need this level of control we recommend you use a `environment.yml`.
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Note that you can also install Python environments using the Anaconda
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distribution by using an ``environment.yml`` file.
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