mirror of https://github.com/mamba-org/mamba.git
refactor documentation (#953)
This commit is contained in:
Adrien Delsalle
GitHub
parent
842e4447e4
commit
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=============
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Build locally
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=============
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Local development environment
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=============================
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Clone the repo
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**************
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Start by cloning the repo:
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.. code::
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git clone https://github.com/mamba-org/mamba.git
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Then move to the newly created directory:
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.. code::
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cd mamba
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Install dev requirements
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************************
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| Make sure you have Mamba's development requirements installed in your environment.
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| To do so, you can use your existing ``mamba`` or ``micromamba`` installation:
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.. code::
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mamba env update --name <env_name> --file environment-dev.yml
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.. code::
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micromamba install --name <env_name> --file environment-dev.yml
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If you don't have one, refer to the :ref:`installation<installation>` page.
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``mamba`` relies on ``python setup.py`` installation while others targets rely on ``cmake`` configuration.
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.. note::
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All ``cmake`` commands listed below use ``bash`` multi-line syntax.
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On Windows, replace ``\`` trailing character with ``^``.
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Build ``mamba``
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===============
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If you build ``mamba`` in a different environment than *base*, you must also install ``conda``
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in that environment:
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.. code::
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mamba install conda -c conda-forge
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For a local (dev) build, run in the environment:
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.. code::
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pip install -e .
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This will build and install ``mamba`` in the current environment.
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Build ``micromamba``
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====================
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Dynamically linked
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******************
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To build ``micromamba``, just activate the ``BUILD_EXE`` flag in ``cmake`` command:
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.. code:: bash
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mkdir -p build
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cd build
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cmake .. \
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-BUILD_EXE=ON
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cmake --build . -j
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.. note::
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Feel free to use your favorite generator: ``make``, ``ninja``, etc.
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.. note::
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If you need to install, use to install in your current development environment:
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- ``-DCMAKE_INSTALL_PREFIX=$CONDA_PREFIX`` [unix]
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- ``-DCMAKE_INSTALL_PREFIX=$CONDA_PREFIX\\Library`` [win]
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| Doing so, you have built the dynamically linked version of ``micromamba``.
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| It's well fitted for development but is not the artefact shipped when installing ``micromamba``.
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Statically linked
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*****************
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``micromamba`` is a fully statically linked executable. To build it, you need to install extra requirements:
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.. code::
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micromamba install --name <env_name> --file environment-static-dev.yml
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It will install the development version of dependencies, including static libraries.
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Now you can run ``cmake`` with the additional flag ``STATIC_DEPENDENCIES`` turned on:
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.. code:: bash
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mkdir -p build
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cd build
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cmake .. \
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-DBUILD_EXE=ON \
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-DSTATIC_DEPENDENCIES=ON
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cmake --build . -j
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Tests
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*****
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You should now be able to run the Python-based test suite:
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.. code::
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pytest ./test/micromamba
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Build ``libmamba``
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==================
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Shared library
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**************
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You need to enable the build of ``libmamba`` shared library using ``BUILD_SHARED`` flag in ``cmake`` command:
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.. code:: bash
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mkdir -p build
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cd build
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cmake .. \
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-DBUILD_SHARED=ON
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cmake --build . -j
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Static library
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**************
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| The static build of ``libmamba`` is enabled by default (``BUILD_STATIC=ON``).
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| You can run :
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.. code:: bash
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mkdir -p build
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cd build
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cmake ..
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cmake --build . -j
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Tests
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*****
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First, compile the ``gtest``-based C++ test suite:
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.. code::
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mkdir -p build
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cd build
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cmake .. \
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-DENABLE_TESTS=ON
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cmake --build . -j
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You should now be able to run:
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.. code::
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./test/test_mamba
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Alternatively you can use:
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.. code::
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make test
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.. note::
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The static version of ``libmamba`` is necessary to build the C++ tests, don't disable it!
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@ -0,0 +1,15 @@
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==============
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Contributing
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==============
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When contributing to this repository, it is always a good idea to first
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discuss the change you wish to make via issue, email, or any other method with
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the owners of this repository before making a change.
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We welcome all kinds of contribution -- code or non-code -- and value them
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highly. We pledge to treat everyones contribution fairly and with respect and
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we are here to help awesome pull requests over the finish line.
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Please note we have a code of conduct, and follow it in all your interactions with the project.
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We follow the `NumFOCUS code of conduct <https://numfocus.org/code-of-conduct>`_.
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Internals of mamba
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==================
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Mamba comes with a C++ core (for speed and efficiency), and a clean Python API on top. The core of mamba uses:
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|
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- ``libsolv`` to solve dependencies (the same library used in RedHat dnf and other Linux package managers)
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- ``curl`` for reliable and fast downloads
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- ``libarchive`` to extract the packages
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|
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@ -1,33 +0,0 @@
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Getting started with mamba
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==========================
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For new users
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-------------
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We strongly recommend to start from `mambaforge`, a community project of the conda-forge community.
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You can download `mambaforge` for [Windows, macOS and Linux under this link](https://github.com/conda-forge/miniforge#mambaforge).
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Mambaforge comes with the popular `conda-forge` channel preconfigured, but you can modify the configuration to use any channel you like.
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After successful installation, you can use the mamba commands as described in [How to Use](how_to_use).
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For conda users
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---------------
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If you are already a conda user, very good! Using mamba will feel natural.
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To get mamba, install it _into the base environment_ from the `conda-forge` channel:
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```
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conda install mamba -n base -c conda-forge
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```
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_Note: Installing mamba into any other environment can cause unexpected behavior._
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There is little difference between using conda & mamba. You can swap almost all commands:
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- `mamba install ...`
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- `mamba create -n ... -c ... ...`
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- `mamba list`
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The one difference is that you should still use `conda` for activation and deactivation.
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Internals of mamba
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==================
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Mamba comes with a C++ core (for speed and efficiency), and a clean Python API on top. The core of mamba uses:
|
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- `libsolv` to solve dependencies (the same library used in RedHat dnf and other Linux package managers)
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- `curl` for reliable and fast downloads
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- `libarchive` to extract the packages
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How to use mamba
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================
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If you already know `conda`, great, you already know `mamba`! mamba is a drop-in replacement and uses the same commands and configuration options as conda.
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For everyone else, here is a short overview over how to use mamba:
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Create an environment
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---------------------
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Mamba handles multiple environments. The initial environment is called the _base_ environment and in general, you should not install packages into the base environment. Rather it's good practice to create new environments whenever you work on a specific project. Mamba has advanced file deduplication to keep the memory footprint of having multiple environments low.
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The `mamba create` command creates a new environment. Mamba's environments are similar to virtual environments known from Python's `virtualenv` and similar software, but more powerful since mamba also manages _native_ dependencies and generalizes the virtual environment concept to many programming languages.
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You can create a virtual environment with the name `nameofmyenv` by calling
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```
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mamba create -n nameofmyenv <list of packages>
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```
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After this process has finished, you can _activate_ the virtual environment by calling `conda activate <nameofmyenv>`.
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For example, to install JupyterLab from the `conda-forge` channel and then run it, you could use the following commands:
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```
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mamba create -n myjlabenv jupyterlab -c conda-forge
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conda activate myjlabenv # activate our environment
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jupyter lab # this will start up jupyter lab and open a browser
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```
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Once an environment is activated, `mamba install` can be used to install further packages into the environment.
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```
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conda activate myjlabenv
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mamba install bqplot # now you can use bqplot in myjlabenv
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```
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Welcome to mamba's documentation!
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=================================
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Mamba is a fast, robust, and cross-platform package manager that runs on Windows, OS X and Linux (ARM64 and PPC64LE included).
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Mamba is fully compatible with `conda` packages and supports most of conda's commands. In fact, mamba was conceived as a _drop-in_ replacement for conda, offering higher speed and more reliable environment solutions.
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We recommend to [start from `mambaforge`](getting_started) or install mamba through `conda install mamba -n base -c conda-forge`, if you're already a conda user.
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Mamba also offers a flavor specifically for the CI use-case ([micromamba](micromamba)). Micromamba is a single-file executable that comes with everything to start installing packages.
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```{toctree}
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:maxdepth: 2
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:caption: "Contents:"
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getting_started
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how_to_use
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python_api
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micromamba
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how_mamba_works
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```
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Indices and tables
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==================
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* {ref}`Index <genindex>`
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* {ref}`Search <search>`
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<!-- * {ref}`modindex <modindex>` -->
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|
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Welcome to Mamba's documentation!
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=================================
|
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|
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Mamba is a fast, robust, and cross-platform package manager.
|
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|
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It runs on Windows, OS X and Linux (ARM64 and PPC64LE included) and is fully compatible with ``conda`` packages and supports most of conda's commands.
|
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|
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The ``mamba-org`` organization hosts multiple Mamba flavors:
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|
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- ``mamba``: a Python-based CLI conceived as a *drop-in* replacement for ``conda``, offering higher speed and more reliable environment solutions
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- ``micromamba``: a pure C++-based CLI, self-contained in a single-file executable
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- ``libmamba``: a C++ library exposing low-level and high-level APIs on top of which both ``mamba`` and ``micromamba`` are built
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.. note::
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In this documentation, ``Mamba`` will refer to all flavors while flavor-specific details will mention ``mamba``, ``micromamba`` or ``libmamba``.
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|
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.. note::
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:ref:`micromamba<micromamba>` is especially well fitted for the CI use-case but not limited to that!
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|
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You can try Mamba now by visiting the :ref:`installation page<installation>`!
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|
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|
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.. toctree::
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:caption: INSTALLATION
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:maxdepth: 2
|
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:hidden:
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|
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installation
|
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|
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.. toctree::
|
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:caption: USER GUIDE
|
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:maxdepth: 2
|
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:hidden:
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|
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user_guide/concepts
|
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user_guide/mamba
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user_guide/micromamba
|
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user_guide/configuration
|
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|
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.. toctree::
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:caption: API reference
|
||||
:maxdepth: 2
|
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:hidden:
|
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|
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python_api
|
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|
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.. toctree::
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:caption: developer zone
|
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:maxdepth: 2
|
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:hidden:
|
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|
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developer_zone/contributing
|
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developer_zone/build_locally
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developer_zone/internals
|
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|
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.. _installation:
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|
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============
|
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Installation
|
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============
|
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|
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.. _mamba-install:
|
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|
||||
mamba
|
||||
=====
|
||||
|
||||
Fresh install
|
||||
*************
|
||||
|
||||
We strongly recommend to start from ``mambaforge``, a community project of the conda-forge community.
|
||||
|
||||
| You can download `mambaforge <https://github.com/conda-forge/miniforge#mambaforge>`_ for Windows, macOS and Linux.
|
||||
| ``mambaforge`` comes with the popular ``conda-forge`` channel preconfigured, but you can modify the configuration to use any channel you like.
|
||||
|
||||
| After successful installation, you can use the mamba commands as described in :ref:`mamba user guide<mamba>`.
|
||||
|
||||
|
||||
Existing ``conda`` install
|
||||
**************************
|
||||
|
||||
If you are already a ``conda`` user, very good!
|
||||
|
||||
To get ``mamba``, just install it *into the base environment* from the ``conda-forge`` channel:
|
||||
|
||||
.. code::
|
||||
|
||||
conda install mamba -n base -c conda-forge
|
||||
|
||||
|
||||
.. warning::
|
||||
Installing mamba into any other environment than base can cause unexpected behavior
|
||||
|
||||
.. _umamba-install:
|
||||
|
||||
micromamba
|
||||
==========
|
||||
|
||||
``micromamba`` is completely statically linked, which allows you to drop it in some place and just execute it.
|
||||
|
||||
Download and unzip the executable (from the official conda-forge package):
|
||||
|
||||
.. _umamba-install-linux:
|
||||
|
||||
Linux
|
||||
*****
|
||||
|
||||
Ensure that basic utilities are installed. We need ``wget`` and ``tar`` with support for ``bzip2``.
|
||||
Also you need a glibc based system like Ubuntu, Fedora or Centos (Alpine Linux does not work natively).
|
||||
|
||||
The following magic URL always returns the latest available version of micromamba, and the ``bin/micromamba`` part is automatically extracted using ``tar``.
|
||||
|
||||
.. code:: sh
|
||||
|
||||
wget -qO- https://micro.mamba.pm/api/micromamba/linux-64/latest | tar -xvj bin/micromamba
|
||||
|
||||
|
||||
.. note::
|
||||
Additional builds are available for linux-aarch64 (ARM64) and linux-ppc64le. Just modify ``linux-64`` in the URL above to match the desired architecture.
|
||||
|
||||
After extraction is completed, we can use the micromamba binary.
|
||||
|
||||
If you want to quickly use micromamba in an ad-hoc usecase, you can run
|
||||
|
||||
.. code::
|
||||
|
||||
export MAMBA_ROOT_PREFIX=/some/prefix # optional, defaults to ~/micromamba
|
||||
eval "$(./bin/micromamba shell hook -s posix)"
|
||||
|
||||
This shell hook modifies your shell variables to include the micromamba command.
|
||||
|
||||
If you want to persist these changes, you can automatically write them to your ``.bashrc`` (or ``.zshrc``) by running ``./micromamba shell init ...``.
|
||||
This also allows you to choose a custom MAMBA_ROOT_ENVIRONMENT, which is where the packages and repodata cache will live.
|
||||
|
||||
.. code::
|
||||
|
||||
sh
|
||||
./bin/micromamba shell init -s bash -p ~/micromamba # this writes to your .bashrc file
|
||||
# sourcing the bashrc file incorporates the changes into the running session.
|
||||
# better yet, restart your terminal!
|
||||
source ~/.bashrc
|
||||
|
||||
Now you can activate the base environment and install new packages, or create other environments.
|
||||
|
||||
.. code::
|
||||
|
||||
micromamba activate # this activates the base environment
|
||||
micromamba install python=3.6 jupyter -c conda-forge
|
||||
# or
|
||||
micromamba create -n new_prefix xtensor -c conda-forge
|
||||
micromamba activate new_prefix
|
||||
|
||||
.. _umamba-install-osx:
|
||||
|
||||
OS X
|
||||
****
|
||||
|
||||
``micromamba`` has OS X support as well. Instructions are largely the same as :ref:`linux<umamba-install-linux>`:
|
||||
|
||||
.. code:: bash
|
||||
|
||||
curl -Ls https://micro.mamba.pm/api/micromamba/osx-64/latest | tar -xvj bin/micromamba
|
||||
mv bin/micromamba ./micromamba
|
||||
|
||||
# directly execute the hook
|
||||
eval "$(./bin/micromamba shell hook -s posix)"
|
||||
|
||||
# ... or shell init
|
||||
./micromamba shell init -s zsh -p ~/micromamba
|
||||
source ~/.zshrc
|
||||
micromamba activate
|
||||
micromamba install python=3.6 jupyter -c conda-forge
|
||||
|
||||
.. _umamba-install-win:
|
||||
|
||||
Windows
|
||||
*******
|
||||
|
||||
| ``micromamba`` also has Windows support! For Windows, we recommend powershell.
|
||||
| Below are the commands to get micromamba installed in ``PowerShell``.
|
||||
|
||||
|
||||
.. code:: powershell
|
||||
|
||||
Invoke-Webrequest -URI https://micro.mamba.pm/api/micromamba/win-64/latest -OutFile micromamba.tar.bz2
|
||||
C:\PROGRA~1\7-Zip\7z.exe x micromamba.tar.bz2 -aoa
|
||||
C:\PROGRA~1\7-Zip\7z.exe x micromamba.tar -ttar -aoa -r Library\bin\micromamba.exe
|
||||
|
||||
MOVE -Force Library\bin\micromamba.exe micromamba.exe
|
||||
.\micromamba.exe --help
|
||||
|
||||
# You can use e.g. $HOME\micromambaenv as your base prefix
|
||||
$Env:MAMBA_ROOT_PREFIX="C:\Your\Root\Prefix"
|
||||
|
||||
# Invoke the hook
|
||||
.\micromamba.exe shell hook -s powershell | Out-String | Invoke-Expression
|
||||
|
||||
# ... or initialize the shell
|
||||
.\micromamba.exe shell init -s powershell -p C:\Your\Root\Prefix
|
||||
# and use micromamba directly
|
||||
micromamba create -f ./test/env_win.yaml -y
|
||||
micromamba activate yourenv
|
||||
|
|
@ -1,266 +0,0 @@
|
|||
# micromamba
|
||||
|
||||
Micromamba is a small, pure-C++ executable with enough functionalities to _bootstrap_ fully functional conda-environments.
|
||||
Currently, given micromamba's early stage, it's main usage is in continous integration pipelines: since it's a single executable, based on mamba, it bootstraps _fast_.
|
||||
|
||||
```{admonition} Warning
|
||||
:class: warning
|
||||
|
||||
Note that micromamba is still in early development and not considered ready-for-general-usage yet! It has been used with great success in CI systems, though, and we encourage this usage.
|
||||
```
|
||||
|
||||
## Installation
|
||||
|
||||
`micromamba` works in the bash & zsh shell on Linux & OS X.
|
||||
It's completely statically linked, which allows you to drop it in some place and just execute it.
|
||||
|
||||
Note: it's advised to use micromamba in containers & CI only.
|
||||
|
||||
Download and unzip the executable (from the official conda-forge package):
|
||||
|
||||
#### Linux / Basic Usage
|
||||
|
||||
Ensure that basic utilities are installed. We need `wget` and `tar` with support for `bzip2`.
|
||||
Also you need a glibc based system like Ubuntu, Fedora or Centos (Alpine Linux does not work natively).
|
||||
|
||||
The following magic URL always returns the latest available version of micromamba, and the `bin/micromamba` part is automatically extracted using `tar`.
|
||||
|
||||
```sh
|
||||
wget -qO- https://micro.mamba.pm/api/micromamba/linux-64/latest | tar -xvj bin/micromamba
|
||||
```
|
||||
|
||||
```{admonition} Warning
|
||||
:class: info
|
||||
|
||||
Additional builds are available for linux-aarch64 (ARM64) and linux-ppc64le. Just modify `linux-64` in the URL above to match the desired architecture.
|
||||
```
|
||||
|
||||
After extraction is completed, we can use the micromamba binary.
|
||||
|
||||
If you want to quickly use micromamba in an ad-hoc usecase, you can run
|
||||
|
||||
```
|
||||
export MAMBA_ROOT_PREFIX=/some/prefix # optional, defaults to ~/micromamba
|
||||
eval "$(./bin/micromamba shell hook -s posix)"
|
||||
```
|
||||
|
||||
This shell hook modifies your shell variables to include the micromamba command.
|
||||
|
||||
If you want to persist these changes, you can automatically write them to your `.bashrc` (or `.zshrc`) by running `./micromamba shell init ... `.
|
||||
This also allows you to choose a custom MAMBA_ROOT_ENVIRONMENT, which is where the packages and repodata cache will live.
|
||||
|
||||
```sh
|
||||
./bin/micromamba shell init -s bash -p ~/micromamba # this writes to your .bashrc file
|
||||
# sourcing the bashrc file incorporates the changes into the running session.
|
||||
# better yet, restart your terminal!
|
||||
source ~/.bashrc
|
||||
```
|
||||
|
||||
Now you can activate the base environment and install new packages, or create other environments.
|
||||
|
||||
```sh
|
||||
micromamba activate # this activates the base environment
|
||||
micromamba install python=3.6 jupyter -c conda-forge
|
||||
# or
|
||||
micromamba create -n new_prefix xtensor -c conda-forge
|
||||
micromamba activate new_prefix
|
||||
```
|
||||
|
||||
#### OS X
|
||||
|
||||
Micromamba has OS X support as well. Instructions are largely the same:
|
||||
|
||||
```sh
|
||||
curl -Ls https://micro.mamba.pm/api/micromamba/osx-64/latest | tar -xvj bin/micromamba
|
||||
mv bin/micromamba ./micromamba
|
||||
|
||||
# directly execute the hook
|
||||
eval "$(./bin/micromamba shell hook -s posix)"
|
||||
|
||||
# ... or shell init
|
||||
./micromamba shell init -s zsh -p ~/micromamba
|
||||
source ~/.zshrc
|
||||
micromamba activate
|
||||
micromamba install python=3.6 jupyter -c conda-forge
|
||||
```
|
||||
|
||||
#### Windows
|
||||
|
||||
Micromamba also has Windows support! For Windows, we recommend powershell. Below are the commands to get micromamba installed in `PowerShell`.
|
||||
|
||||
```powershell
|
||||
Invoke-Webrequest -URI https://micro.mamba.pm/api/micromamba/win-64/latest -OutFile micromamba.tar.bz2
|
||||
C:\PROGRA~1\7-Zip\7z.exe x micromamba.tar.bz2 -aoa
|
||||
C:\PROGRA~1\7-Zip\7z.exe x micromamba.tar -ttar -aoa -r Library\bin\micromamba.exe
|
||||
|
||||
MOVE -Force Library\bin\micromamba.exe micromamba.exe
|
||||
.\micromamba.exe --help
|
||||
|
||||
# You can use e.g. $HOME\micromambaenv as your base prefix
|
||||
$Env:MAMBA_ROOT_PREFIX="C:\Your\Root\Prefix"
|
||||
|
||||
# Invoke the hook
|
||||
.\micromamba.exe shell hook -s powershell | Out-String | Invoke-Expression
|
||||
|
||||
# ... or initialize the shell
|
||||
.\micromamba.exe shell init -s powershell -p C:\Your\Root\Prefix
|
||||
# and use micromamba directly
|
||||
micromamba create -f ./test/env_win.yaml -y
|
||||
micromamba activate ...
|
||||
```
|
||||
|
||||
## Available commands
|
||||
|
||||
Micromamba supports a subset of all conda commands and implements a command line interface from scratch. You can see all implemented commands with `micromamba --help`:
|
||||
|
||||
```
|
||||
$ micromamba --help
|
||||
|
||||
Subcommands:
|
||||
activate Activate a conda / micromamba environment
|
||||
deactivate Deactivate a conda / micromamba environment
|
||||
shell Generate shell init scripts
|
||||
create Create new environment
|
||||
install Install packages in active environment
|
||||
remove Remove packages from active environment
|
||||
list List packages in active environment
|
||||
constructor Commands to support using micromamba in constructor
|
||||
```
|
||||
|
||||
To activate an environment just call `micromamba activate /path/to/env` or, when it's a named environment in your `$MAMBA_ROOT_PREFIX`, then you can just use `micromamba activate myenv`. Named environments live in `$MAMBA_ROOT_PREFIX/envs/`.
|
||||
|
||||
After activation, the `$CONDA_PREFIX` and `$PATH` environment variables are modified to add the environment to your current bash session. You can then run install to add new packages to the environment.
|
||||
|
||||
```
|
||||
$ micromamba install xtensor -c conda-forge
|
||||
```
|
||||
|
||||
Using create you can also create new virtual environments. Named environments are convenient and easy to use. For example, to create a new environment:
|
||||
|
||||
```
|
||||
$ micromamba create -n xtensor_env xtensor xsimd -c conda-forge
|
||||
__
|
||||
__ ______ ___ ____ _____ ___ / /_ ____ _
|
||||
/ / / / __ `__ \/ __ `/ __ `__ \/ __ \/ __ `/
|
||||
/ /_/ / / / / / / /_/ / / / / / / /_/ / /_/ /
|
||||
/ .___/_/ /_/ /_/\__,_/_/ /_/ /_/_.___/\__,_/
|
||||
/_/
|
||||
|
||||
conda-forge/noarch [====================] (00m:01s) Done
|
||||
conda-forge/linux-64 [====================] (00m:04s) Done
|
||||
|
||||
Transaction
|
||||
|
||||
Prefix: /home/wolfv/miniconda3/envs/xtensor_env
|
||||
|
||||
Updating specs:
|
||||
|
||||
- xtensor
|
||||
- xsimd
|
||||
|
||||
|
||||
Package Version Build Channel Size
|
||||
────────────────────────────────────────────────────────────────────────
|
||||
Install:
|
||||
────────────────────────────────────────────────────────────────────────
|
||||
|
||||
_libgcc_mutex 0.1 conda_forge conda-forge/linux-64 Cached
|
||||
_openmp_mutex 4.5 1_gnu conda-forge/linux-64 Cached
|
||||
libgcc-ng 9.3.0 h5dbcf3e_17 conda-forge/linux-64 Cached
|
||||
libgomp 9.3.0 h5dbcf3e_17 conda-forge/linux-64 Cached
|
||||
libstdcxx-ng 9.3.0 h2ae2ef3_17 conda-forge/linux-64 Cached
|
||||
xsimd 7.4.9 hc9558a2_0 conda-forge/linux-64 102 KB
|
||||
xtensor 0.21.9 h0efe328_0 conda-forge/linux-64 183 KB
|
||||
xtl 0.6.21 h0efe328_0 conda-forge/linux-64 Cached
|
||||
|
||||
Summary:
|
||||
|
||||
Install: 8 packages
|
||||
|
||||
Total download: 285 KB
|
||||
|
||||
────────────────────────────────────────────────────────────────────────
|
||||
|
||||
Confirm changes: [Y/n] ...
|
||||
|
||||
```
|
||||
|
||||
After the installation is finished, the environment can be activated with
|
||||
|
||||
```
|
||||
$ micromamba activate xtensor_env
|
||||
```
|
||||
|
||||
## Environment files
|
||||
|
||||
The create syntax also allows you to use spec- or environment files to easily recreate environments.
|
||||
|
||||
The three supported syntaxes are: yaml, txt and explicit spec files.
|
||||
|
||||
#### Simple text spec files
|
||||
|
||||
The txt file contains _one spec per line_. For example, this could look like:
|
||||
|
||||
```
|
||||
xtensor
|
||||
numpy 1.19
|
||||
xsimd >=7.4
|
||||
```
|
||||
|
||||
To use this file, pass
|
||||
|
||||
```
|
||||
$ micromamba create -n from_file -f spec_file.txt -c conda-forge
|
||||
```
|
||||
|
||||
Note: with spec text files you can pass multiple files by repeating the `-f` argument.
|
||||
|
||||
#### YAML environment files
|
||||
|
||||
More powerful are YAML files like the following, because they already contain a desired environment name and the channels to use.
|
||||
|
||||
```
|
||||
name: testenv
|
||||
channels:
|
||||
- conda-forge
|
||||
dependencies:
|
||||
- python >=3.6,<3.7
|
||||
- ipykernel >=5.1
|
||||
- ipywidgets
|
||||
```
|
||||
|
||||
```
|
||||
$ micromamba create -f env.yml
|
||||
```
|
||||
|
||||
YAML files do not allow multiple files.
|
||||
|
||||
#### Explicit environment specs
|
||||
|
||||
Using conda you can generate _explicit_ environment lock files. For this, create an environment and execute
|
||||
|
||||
```
|
||||
$ conda list --explicit --md5
|
||||
```
|
||||
|
||||
These environment files look like the following and precisely "pin" the desired package + version + build string.
|
||||
|
||||
```
|
||||
# This file may be used to create an environment using:
|
||||
# $ conda create --name <env> --file <this file>
|
||||
# platform: linux-64
|
||||
@EXPLICIT
|
||||
https://conda.anaconda.org/conda-forge/linux-64/_libgcc_mutex-0.1-conda_forge.tar.bz2#d7c89558ba9fa0495403155b64376d81
|
||||
https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-ng-9.3.0-h2ae2ef3_17.tar.bz2#342f3c931d0a3a209ab09a522469d20c
|
||||
https://conda.anaconda.org/conda-forge/linux-64/libgomp-9.3.0-h5dbcf3e_17.tar.bz2#8fd587013b9da8b52050268d50c12305
|
||||
https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-1_gnu.tar.bz2#561e277319a41d4f24f5c05a9ef63c04
|
||||
https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-9.3.0-h5dbcf3e_17.tar.bz2#fc9f5adabc4d55cd4b491332adc413e0
|
||||
https://conda.anaconda.org/conda-forge/linux-64/xtl-0.6.21-h0efe328_0.tar.bz2#9eee90b98fd394db7a049792e67e1659
|
||||
https://conda.anaconda.org/conda-forge/linux-64/xtensor-0.21.8-hc9558a2_0.tar.bz2#1030174db5c183f3afb4181a0a02873d
|
||||
```
|
||||
|
||||
To install such a file with micromamba, just pass the `-f` flag again:
|
||||
|
||||
```
|
||||
$ micromamba create -n xtensor -c conda-forge -f explicit_env.txt
|
||||
```
|
||||
|
|
@ -1,134 +0,0 @@
|
|||
# The Python API of mamba
|
||||
|
||||
The core of mamba is written in C++, but we expose the internals of mamba with a Python API (using pybind11).
|
||||
|
||||
You can import the `mamba_api` using `from mamba import mamba_api`.
|
||||
|
||||
The mamba_api exposes the following objects:
|
||||
|
||||
- `Context`: a singleton configuration object. All global configuration goes through this. From Python you can use the context object like so:
|
||||
```
|
||||
from mamba import mamba_api
|
||||
mamba_api.Context().conda_prefix = "/home/wolfv/conda"
|
||||
ctx = mamba_api.Context()
|
||||
print(ctx.root_prefix)
|
||||
```
|
||||
|
||||
|
||||
|
||||
Here is an example usage of the mamba_api:
|
||||
|
||||
```
|
||||
def get_index(
|
||||
channel_urls=(),
|
||||
prepend=True,
|
||||
platform=None,
|
||||
use_local=False,
|
||||
use_cache=False,
|
||||
unknown=None,
|
||||
prefix=None,
|
||||
repodata_fn="repodata.json",
|
||||
):
|
||||
real_urls = calculate_channel_urls(channel_urls, prepend, platform, use_local)
|
||||
check_whitelist(real_urls)
|
||||
|
||||
dlist = mamba_api.DownloadTargetList()
|
||||
|
||||
index = []
|
||||
for idx, url in enumerate(real_urls):
|
||||
channel = Channel(url)
|
||||
|
||||
full_url = channel.url(with_credentials=True) + "/" + repodata_fn
|
||||
full_path_cache = os.path.join(
|
||||
create_cache_dir(), cache_fn_url(full_url, repodata_fn)
|
||||
)
|
||||
|
||||
# Channels might not have a name.
|
||||
if channel.name is None:
|
||||
name_and_subdir = channel.subdir
|
||||
else:
|
||||
name_and_subdir = channel.name + "/" + channel.subdir
|
||||
sd = mamba_api.SubdirData(name_and_subdir, full_url, full_path_cache)
|
||||
|
||||
sd.load()
|
||||
index.append((sd, channel))
|
||||
dlist.add(sd)
|
||||
|
||||
is_downloaded = dlist.download(True)
|
||||
|
||||
if not is_downloaded:
|
||||
raise RuntimeError("Error downloading repodata.")
|
||||
|
||||
return index
|
||||
|
||||
class MambaSolver:
|
||||
def __init__(self, prefix, channels, platform):
|
||||
|
||||
api_ctx = mamba_api.Context()
|
||||
api_ctx.conda_prefix = prefix
|
||||
|
||||
self.channels = channels
|
||||
self.platform = platform
|
||||
self.index = get_index(channels, platform=platform)
|
||||
self.local_index = []
|
||||
self.pool = mamba_api.Pool()
|
||||
self.repos = []
|
||||
|
||||
start_prio = len(channels)
|
||||
priority = start_prio
|
||||
subpriority = 0 # wrong! :)
|
||||
for subdir, channel in self.index:
|
||||
repo = mamba_api.Repo(
|
||||
self.pool,
|
||||
str(channel),
|
||||
subdir.cache_path(),
|
||||
channel.url(with_credentials=True),
|
||||
)
|
||||
repo.set_priority(start_prio, subpriority)
|
||||
start_prio -= 1
|
||||
self.repos.append(repo)
|
||||
|
||||
self.local_repos = {}
|
||||
|
||||
def solve(self, specs, prefix):
|
||||
"""Solve given a set of specs.
|
||||
Parameters
|
||||
----------
|
||||
specs : list of str
|
||||
A list of package specs. You can use `conda.models.match_spec.MatchSpec`
|
||||
to get them to the right form by calling
|
||||
`MatchSpec(mypec).conda_build_form()`
|
||||
Returns
|
||||
-------
|
||||
solvable : bool
|
||||
True if the set of specs has a solution, False otherwise.
|
||||
"""
|
||||
solver_options = [(mamba_api.SOLVER_FLAG_ALLOW_DOWNGRADE, 1)]
|
||||
api_solver = mamba_api.Solver(self.pool, solver_options)
|
||||
_specs = specs
|
||||
|
||||
api_solver.add_jobs(_specs, mamba_api.SOLVER_INSTALL)
|
||||
success = api_solver.solve()
|
||||
|
||||
if not success:
|
||||
error_string = "Mamba failed to solve:\n"
|
||||
for s in _specs:
|
||||
error_string += f" - {s}\n"
|
||||
error_string += "\nwith channels:\n"
|
||||
for c in self.channels:
|
||||
error_string += f" - {c}\n"
|
||||
pstring = api_solver.problems_to_str()
|
||||
pstring = "\n".join([" " + l for l in pstring.split("\n")])
|
||||
error_string += f"\nThe reported errors are:\n⇟{pstring}"
|
||||
print(error_string)
|
||||
exit(1)
|
||||
|
||||
package_cache = mamba_api.MultiPackageCache(pkgs_dirs)
|
||||
|
||||
t = mamba_api.Transaction(api_solver, package_cache)
|
||||
return t
|
||||
```
|
||||
|
||||
Let's walk through this example:
|
||||
|
||||
We first use the `get_index` method to download repository data from the channels.
|
||||
|
|
@ -0,0 +1,137 @@
|
|||
=======================
|
||||
Python API of ``mamba``
|
||||
=======================
|
||||
|
||||
The core of ``mamba`` is written in C++, but we expose the internals of mamba with a Python API (using ``pybind11``).
|
||||
|
||||
You can import the ``mamba_api`` using ``from mamba import mamba_api``.
|
||||
|
||||
The mamba_api exposes the following objects:
|
||||
|
||||
- ``Context``: a singleton configuration object. All global configuration goes through this. From Python you can use the context object like so:
|
||||
|
||||
.. code::
|
||||
|
||||
from mamba import mamba_api
|
||||
mamba_api.Context().conda_prefix = "/home/wolfv/conda"
|
||||
ctx = mamba_api.Context()
|
||||
print(ctx.root_prefix)
|
||||
|
||||
|
||||
Here is an example usage of the mamba_api:
|
||||
|
||||
.. code::
|
||||
|
||||
def get_index(
|
||||
channel_urls=(),
|
||||
prepend=True,
|
||||
platform=None,
|
||||
use_local=False,
|
||||
use_cache=False,
|
||||
unknown=None,
|
||||
prefix=None,
|
||||
repodata_fn="repodata.json",
|
||||
):
|
||||
real_urls = calculate_channel_urls(channel_urls, prepend, platform, use_local)
|
||||
check_whitelist(real_urls)
|
||||
|
||||
dlist = mamba_api.DownloadTargetList()
|
||||
|
||||
index = []
|
||||
for idx, url in enumerate(real_urls):
|
||||
channel = Channel(url)
|
||||
|
||||
full_url = channel.url(with_credentials=True) + "/" + repodata_fn
|
||||
full_path_cache = os.path.join(
|
||||
create_cache_dir(), cache_fn_url(full_url, repodata_fn)
|
||||
)
|
||||
|
||||
# Channels might not have a name.
|
||||
if channel.name is None:
|
||||
name_and_subdir = channel.subdir
|
||||
else:
|
||||
name_and_subdir = channel.name + "/" + channel.subdir
|
||||
sd = mamba_api.SubdirData(name_and_subdir, full_url, full_path_cache)
|
||||
|
||||
sd.load()
|
||||
index.append((sd, channel))
|
||||
dlist.add(sd)
|
||||
|
||||
is_downloaded = dlist.download(True)
|
||||
|
||||
if not is_downloaded:
|
||||
raise RuntimeError("Error downloading repodata.")
|
||||
|
||||
return index
|
||||
|
||||
class MambaSolver:
|
||||
def __init__(self, prefix, channels, platform):
|
||||
|
||||
api_ctx = mamba_api.Context()
|
||||
api_ctx.conda_prefix = prefix
|
||||
|
||||
self.channels = channels
|
||||
self.platform = platform
|
||||
self.index = get_index(channels, platform=platform)
|
||||
self.local_index = []
|
||||
self.pool = mamba_api.Pool()
|
||||
self.repos = []
|
||||
|
||||
start_prio = len(channels)
|
||||
priority = start_prio
|
||||
subpriority = 0 # wrong! :)
|
||||
for subdir, channel in self.index:
|
||||
repo = mamba_api.Repo(
|
||||
self.pool,
|
||||
str(channel),
|
||||
subdir.cache_path(),
|
||||
channel.url(with_credentials=True),
|
||||
)
|
||||
repo.set_priority(start_prio, subpriority)
|
||||
start_prio -= 1
|
||||
self.repos.append(repo)
|
||||
|
||||
self.local_repos = {}
|
||||
|
||||
def solve(self, specs, prefix):
|
||||
"""Solve given a set of specs.
|
||||
Parameters
|
||||
----------
|
||||
specs : list of str
|
||||
A list of package specs. You can use `conda.models.match_spec.MatchSpec`
|
||||
to get them to the right form by calling
|
||||
`MatchSpec(mypec).conda_build_form()`
|
||||
Returns
|
||||
-------
|
||||
solvable : bool
|
||||
True if the set of specs has a solution, False otherwise.
|
||||
"""
|
||||
solver_options = [(mamba_api.SOLVER_FLAG_ALLOW_DOWNGRADE, 1)]
|
||||
api_solver = mamba_api.Solver(self.pool, solver_options)
|
||||
_specs = specs
|
||||
|
||||
api_solver.add_jobs(_specs, mamba_api.SOLVER_INSTALL)
|
||||
success = api_solver.solve()
|
||||
|
||||
if not success:
|
||||
error_string = "Mamba failed to solve:\n"
|
||||
for s in _specs:
|
||||
error_string += f" - {s}\n"
|
||||
error_string += "\nwith channels:\n"
|
||||
for c in self.channels:
|
||||
error_string += f" - {c}\n"
|
||||
pstring = api_solver.problems_to_str()
|
||||
pstring = "\n".join([" " + l for l in pstring.split("\n")])
|
||||
error_string += f"\nThe reported errors are:\n⇟{pstring}"
|
||||
print(error_string)
|
||||
exit(1)
|
||||
|
||||
package_cache = mamba_api.MultiPackageCache(pkgs_dirs)
|
||||
|
||||
t = mamba_api.Transaction(api_solver, package_cache)
|
||||
return t
|
||||
|
||||
|
||||
Let's walk through this example:
|
||||
|
||||
We first use the ``get_index`` method to download repository data from the channels.
|
||||
|
|
@ -0,0 +1,87 @@
|
|||
.. _concepts:
|
||||
|
||||
Concepts
|
||||
--------
|
||||
|
||||
Few concepts are extensively used in ``Mamba`` and in this documentation as well.
|
||||
You should start by getting familiar with those as a starting point.
|
||||
|
||||
|
||||
.. _prefix:
|
||||
|
||||
Prefix/Environment
|
||||
==================
|
||||
|
||||
|
||||
In Unix-like platforms, installing a software consists in placing files in subdirectories of an "installation prefix":
|
||||
|
||||
.. image:: prefix.png
|
||||
:height: 300
|
||||
:align: center
|
||||
|
||||
- no file is placed outside of the installation *prefix*
|
||||
- dependencies must be installed in the same *prefix* (or standard system prefixes with lower precedence)
|
||||
|
||||
.. note::
|
||||
Examples on Unix: the root of the filesystem, the ``/usr/`` and ``/usr/local/`` directories.
|
||||
|
||||
| A *prefix* is a fully self-contained and portable installation.
|
||||
| To disambiguate with :ref:`root prefix<root-prefix>`, *prefix* is often called *target prefix*. Without explicit *target* or *root* reference, you can assume it points a *target prefix*.
|
||||
|
||||
An *environment* is just another way to call a *target prefix*.
|
||||
|
||||
Mamba's environments are similar to virtual environments known from Python's ``virtualenv`` and similar software, but more powerful since Mamba also manages *native* dependencies and generalizes the virtual environment concept to many programming languages.
|
||||
|
||||
.. _root-prefix:
|
||||
|
||||
Root prefix
|
||||
===========
|
||||
|
||||
When downloading for the first time the index of packages for resolution of the environment, or the packages themselves, a *cache* is generated to speed-up next operations:
|
||||
|
||||
- the index has a :ref:`configurable<configuration>` time-to-live (TTL) during which it will be considered as valid
|
||||
- the packages are preferentially hard-linked to the *cache* location
|
||||
|
||||
This *cache* is shared by all *environments* or *target prefixes* based on the same *root prefix*. Basically, that *cache* directory is a subdirectory located at ``$root_prefix/pkgs/``.
|
||||
|
||||
The *root prefix* also provide a convenient structure to store *environments* ``$root_prefix/envs/``, even if you are free to create an *environment* elsewhere.
|
||||
|
||||
|
||||
.. _base-env:
|
||||
|
||||
Base environment
|
||||
================
|
||||
|
||||
The *base* environment is the environment located at the *root prefix*.
|
||||
|
||||
| This is a legacy *environment* from ``conda`` implementation still heavily used.
|
||||
| The *base* environment contains the ``conda`` and ``mamba`` installation alongside a Python installation (since ``mamba`` and ``conda`` require Python to run)
|
||||
| ``mamba`` and ``conda`` being themselves Python packages, they are installed in *base* environment, making the CLIs available in all *activated* environment *based* on this *base* environement.
|
||||
|
||||
.. note::
|
||||
You can't ``create`` *base* environment because it's already part of the *root prefix* structure, directly ``install`` in *base* instead.
|
||||
|
||||
|
||||
Activation/Deactivation
|
||||
=======================
|
||||
|
||||
.. _activation:
|
||||
|
||||
Activation
|
||||
**********
|
||||
|
||||
The *activation* of an :ref:`environment<prefix>` makes all its contents available to your shell. It mainly adds *target prefix* subdirectories to your ``$PATH`` environment variable.
|
||||
|
||||
.. note::
|
||||
*activation* implementation is platform dependent.
|
||||
|
||||
| When *activating* an environment from another, you can choose to ``stack`` or not upon the currently activated env.
|
||||
| Stacking will result in a new intermediate :ref:`prefix<prefix>`: ``system prefix < base < env1 < env2``.
|
||||
|
||||
|
||||
.. _deactivation:
|
||||
|
||||
Deactivation
|
||||
************
|
||||
|
||||
The *deactivation* is the opposite operation of :ref:`activation<activation>`, removing from your shell what makes the environment content accessible.
|
||||
|
|
@ -0,0 +1,293 @@
|
|||
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
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||||
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xmlns:svg="http://www.w3.org/2000/svg"
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xmlns="http://www.w3.org/2000/svg"
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width="1092.0388mm"
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<dc:title></dc:title>
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.. _configuration:
|
||||
|
||||
Configuration
|
||||
=============
|
||||
|
||||
Overview
|
||||
--------
|
||||
|
||||
While ``mamba`` currently relies on ``conda`` configuration, ``libmamba`` and downstream projects such as ``micromamba`` or ``rhumba``
|
||||
rely on a pure C++ implementation.
|
||||
|
||||
.. note::
|
||||
For ``mamba`` configuration, please refer to `conda documentation <https://conda.io/projects/conda/en/latest/user-guide/configuration/index.html>`_
|
||||
|
||||
The configuration is parsed/read from multiple sources types:
|
||||
|
||||
- **rc file**: a file using `YAML` syntax
|
||||
- **environment variable**: a key/value pair set prior to mamba execution
|
||||
- **CLI**: a parsed argument/option from a CLI interface
|
||||
- **API**: a value set programmatically by a program relying on mamba
|
||||
|
||||
The precedence order between those sources is:
|
||||
|
||||
.. image:: config_srcs.svg
|
||||
:width: 600
|
||||
:align: center
|
||||
|
||||
.. note::
|
||||
`rc` file stands historically for `run commands` which could also translate to `runtime configuration`.
|
||||
It's a convenient way to persist configuration on the filesystem and use it as default.
|
||||
|
||||
|
||||
.. _precedence-resolution:
|
||||
|
||||
Precedence resolution
|
||||
---------------------
|
||||
|
||||
Depending on its type, the resolution of a configuration value between multiple sources is:
|
||||
|
||||
- scalar (boolean, string): value from highest precedence source
|
||||
- sequence (list): appended from highest precedence source to lowest
|
||||
|
||||
Example:
|
||||
|
||||
Running ``micromamba install xtensor -c my-channel`` with 3 sources of configuration:
|
||||
|
||||
- ``channels`` and ``always_yes`` set from rc file located at `~/.mambarc`
|
||||
- ``channels`` set from CLI using `-c` option
|
||||
- ``always_yes`` set from environment variable using `MAMBA_ALWAYS_YES` env var
|
||||
|
||||
.. code::
|
||||
|
||||
$ cat ~/.mambarc
|
||||
channels:
|
||||
- conda-forge
|
||||
always_yes: false
|
||||
|
||||
.. code::
|
||||
|
||||
$ echo $MAMBA_ALWAYS_YES
|
||||
true
|
||||
|
||||
The resulting configuration written using `YAML` syntax is:
|
||||
|
||||
.. code::
|
||||
|
||||
channels:
|
||||
- my-channel # 'CLI'
|
||||
- conda-forge # '~/.mambarc'
|
||||
always_yes: true # 'MAMBA_ALWAYS_YES' > '~/.mambarc'
|
||||
|
||||
|
||||
Multiple rc files
|
||||
-----------------
|
||||
|
||||
A user may have multiple rc files located at different places on his machine.
|
||||
|
||||
It's a convenient way for configuration to apply in given scopes:
|
||||
|
||||
- system wide: all users
|
||||
- root prefix: all environments sharing the same root prefix
|
||||
- current user
|
||||
- target prefix: a specific target prefix | environment
|
||||
- a single use
|
||||
|
||||
Alternatively, ones could also pass one or more rc files to use from the CLI. Other sources are then ignored.
|
||||
|
||||
RC files have their own precedence order and use the same resolution process as other configuration sources:
|
||||
|
||||
.. image:: config_rc_srcs.svg
|
||||
:width: 800
|
||||
:align: center
|
||||
|
||||
.. code::
|
||||
|
||||
// on_unix
|
||||
{
|
||||
"/etc/conda/.condarc",
|
||||
"/etc/conda/condarc",
|
||||
"/etc/conda/condarc.d/",
|
||||
"/etc/conda/.mambarc",
|
||||
"/var/lib/conda/.condarc",
|
||||
"/var/lib/conda/condarc",
|
||||
"/var/lib/conda/condarc.d/",
|
||||
"/var/lib/conda/.mambarc"
|
||||
}
|
||||
// on_win
|
||||
{
|
||||
"C:\\ProgramData\\conda\\.condarc",
|
||||
"C:\\ProgramData\\conda\\condarc",
|
||||
"C:\\ProgramData\\conda\\condarc.d",
|
||||
"C:\\ProgramData\\conda\\.mambarc"
|
||||
}
|
||||
|
||||
{ root_prefix }/.condarc
|
||||
{ root_prefix }/condarc
|
||||
{ root_prefix }/condarc.d
|
||||
{ root_prefix }/.mambarc
|
||||
~/.conda/.condarc
|
||||
~/.conda/condarc
|
||||
~/.conda/condarc.d
|
||||
~/.condarc
|
||||
~/.mambarc
|
||||
{ target_prefix }/.condarc
|
||||
{ target_prefix }/condarc
|
||||
{ target_prefix }/condarc.d
|
||||
{ target_prefix }/.mambarc
|
||||
$CONDARC,
|
||||
$MAMBARC;
|
||||
|
|
@ -0,0 +1,105 @@
|
|||
.. _mamba:
|
||||
|
||||
Mamba
|
||||
-----
|
||||
|
||||
``mamba`` is a CLI tool to manage ``conda`` s environments.
|
||||
|
||||
If you already know ``conda``, great, you already know ``mamba``!
|
||||
|
||||
If you're new to this world, don't panic you will find everything you need in this documentation. We recommend to get familiar with :ref:`concepts<concepts>` first.
|
||||
|
||||
|
||||
Quickstart
|
||||
==========
|
||||
|
||||
The ``mamba create`` command creates a new environment.
|
||||
|
||||
You can create an environment with the name ``nameofmyenv`` by calling:
|
||||
|
||||
.. code::
|
||||
|
||||
mamba create -n nameofmyenv <list of packages>
|
||||
|
||||
|
||||
After this process has finished, you can _activate_ the virtual environment by calling ``conda activate <nameofmyenv>``.
|
||||
For example, to install JupyterLab from the ``conda-forge`` channel and then run it, you could use the following commands:
|
||||
|
||||
.. code::
|
||||
|
||||
mamba create -n myjlabenv jupyterlab -c conda-forge
|
||||
conda activate myjlabenv # activate our environment
|
||||
jupyter lab # this will start up jupyter lab and open a browser
|
||||
|
||||
Once an environment is activated, ``mamba install`` can be used to install further packages into the environment.
|
||||
|
||||
.. code::
|
||||
|
||||
conda activate myjlabenv
|
||||
mamba install bqplot # now you can use bqplot in myjlabenv
|
||||
|
||||
``mamba`` vs ``conda`` CLIs
|
||||
===========================
|
||||
|
||||
| ``mamba`` is a drop-in replacement and uses the same commands and configuration options as ``conda``.
|
||||
| You can swap almost all commands between ``conda`` & ``mamba``:
|
||||
|
||||
.. code::
|
||||
|
||||
mamba install ...
|
||||
mamba create -n ... -c ... ...
|
||||
mamba list
|
||||
|
||||
.. warning::
|
||||
The only difference is that you should still use ``conda`` for :ref:`activation<activation>` and :ref:`deactivation<deactivation>`.
|
||||
|
||||
|
||||
Repoquery
|
||||
=========
|
||||
|
||||
``mamba`` comes with features on top of stock ``conda``.
|
||||
To efficiently query repositories and query package dependencies you can use ``mamba repoquery``.
|
||||
|
||||
Here are some examples:
|
||||
|
||||
.. code::
|
||||
|
||||
# will show you all available xtensor packages.
|
||||
$ mamba repoquery search xtensor
|
||||
|
||||
# you can also specify more constraints on this search query
|
||||
$ mamba repoquery search "xtensor>=0.18"
|
||||
|
||||
# will show you a tree view of the dependencies of xtensor.
|
||||
$ mamba repoquery depends xtensor
|
||||
|
||||
.. code::
|
||||
|
||||
$ mamba repoquery depends xtensor
|
||||
|
||||
xtensor == 0.21.5
|
||||
├─ libgcc-ng [>=7.3.0]
|
||||
│ ├─ _libgcc_mutex [0.1 conda_forge]
|
||||
│ └─ _openmp_mutex [>=4.5]
|
||||
│ ├─ _libgcc_mutex already visited
|
||||
│ └─ libgomp [>=7.3.0]
|
||||
│ └─ _libgcc_mutex already visited
|
||||
├─ libstdcxx-ng [>=7.3.0]
|
||||
└─ xtl [>=0.6.9,<0.7]
|
||||
├─ libgcc-ng already visited
|
||||
└─ libstdcxx-ng already visited
|
||||
|
||||
|
||||
And you can ask for the inverse, which packages depend on some other package (e.g. ``ipython``) using ``whoneeds``.
|
||||
|
||||
.. code::
|
||||
|
||||
$ mamba repoquery whoneeds ipython
|
||||
|
||||
Name Version Build Channel
|
||||
──────────────────────────────────────────────────
|
||||
ipykernel 5.2.1 py37h43977f1_0 installed
|
||||
ipywidgets 7.5.1 py_0 installed
|
||||
jupyter_console 6.1.0 py_1 installed
|
||||
|
||||
With the ``-t,--tree`` flag, you can get the same information in a tree.
|
||||
|
|
@ -0,0 +1,195 @@
|
|||
.. _micromamba:
|
||||
|
||||
==========
|
||||
Micromamba
|
||||
==========
|
||||
|
||||
``micromamba`` is a small, pure-C++ executable with enough functionalities to *bootstrap* fully functional conda-environments.
|
||||
|
||||
Still at early stage, it's main usage is in continous integration pipelines: since it's a single executable, it reduces dramatically bandwidth usage and provide *fast* operations.
|
||||
|
||||
|
||||
Quickstarts
|
||||
===========
|
||||
|
||||
| ``micromamba`` supports a subset of all ``mamba`` or ``conda`` commands and implements a command line interface from scratch.
|
||||
| You can see all implemented commands with ``micromamba --help``:
|
||||
|
||||
.. code::
|
||||
|
||||
$ micromamba --help
|
||||
|
||||
Subcommands:
|
||||
activate Activate a conda / micromamba environment
|
||||
deactivate Deactivate a conda / micromamba environment
|
||||
shell Generate shell init scripts
|
||||
create Create new environment
|
||||
install Install packages in active environment
|
||||
update Update packages in active environment
|
||||
remove Remove packages from active environment
|
||||
list List packages in active environment
|
||||
config Configuration of micromamba
|
||||
info Information about micromamba
|
||||
clean Clean package cache
|
||||
constructor Commands to support using micromamba in constructor
|
||||
env List environments
|
||||
|
||||
To activate an environment just call ``micromamba activate /path/to/env`` or, when it's a named environment in your :ref:`root prefix<root-prefix>`, then you can also use ``micromamba activate myenv``.
|
||||
|
||||
``micromamba`` expects to find the *root prefix* set by ``$MAMBA_ROOT_PREFIX`` environment variable. You can also provide it using CLI option ``-r,--root-prefix``.
|
||||
|
||||
| Named environments then live in ``$MAMBA_ROOT_PREFIX/envs/``.
|
||||
|
||||
For more details, please read about :ref:`configuration<configuration>`.
|
||||
|
||||
After :ref:`activation<activation>`, you can run ``install`` to add new packages to the environment.
|
||||
|
||||
.. code::
|
||||
|
||||
$ micromamba install xtensor -c conda-forge
|
||||
|
||||
|
||||
Using ``create``, you can also create environments:
|
||||
|
||||
.. code::
|
||||
|
||||
$ micromamba create -n xtensor_env xtensor xsimd -c conda-forge
|
||||
__
|
||||
__ ______ ___ ____ _____ ___ / /_ ____ _
|
||||
/ / / / __ `__ \/ __ `/ __ `__ \/ __ \/ __ `/
|
||||
/ /_/ / / / / / / /_/ / / / / / / /_/ / /_/ /
|
||||
/ .___/_/ /_/ /_/\__,_/_/ /_/ /_/_.___/\__,_/
|
||||
/_/
|
||||
|
||||
conda-forge/noarch [====================] (00m:01s) Done
|
||||
conda-forge/linux-64 [====================] (00m:04s) Done
|
||||
|
||||
Transaction
|
||||
|
||||
Prefix: /home/wolfv/miniconda3/envs/xtensor_env
|
||||
|
||||
Updating specs:
|
||||
|
||||
- xtensor
|
||||
- xsimd
|
||||
|
||||
|
||||
Package Version Build Channel Size
|
||||
────────────────────────────────────────────────────────────────────────
|
||||
Install:
|
||||
────────────────────────────────────────────────────────────────────────
|
||||
|
||||
_libgcc_mutex 0.1 conda_forge conda-forge/linux-64 Cached
|
||||
_openmp_mutex 4.5 1_gnu conda-forge/linux-64 Cached
|
||||
libgcc-ng 9.3.0 h5dbcf3e_17 conda-forge/linux-64 Cached
|
||||
libgomp 9.3.0 h5dbcf3e_17 conda-forge/linux-64 Cached
|
||||
libstdcxx-ng 9.3.0 h2ae2ef3_17 conda-forge/linux-64 Cached
|
||||
xsimd 7.4.9 hc9558a2_0 conda-forge/linux-64 102 KB
|
||||
xtensor 0.21.9 h0efe328_0 conda-forge/linux-64 183 KB
|
||||
xtl 0.6.21 h0efe328_0 conda-forge/linux-64 Cached
|
||||
|
||||
Summary:
|
||||
|
||||
Install: 8 packages
|
||||
|
||||
Total download: 285 KB
|
||||
|
||||
────────────────────────────────────────────────────────────────────────
|
||||
|
||||
Confirm changes: [Y/n] ...
|
||||
|
||||
|
||||
After the installation is finished, the environment can be :ref:`activated<activation>` with:
|
||||
|
||||
.. code::
|
||||
|
||||
$ micromamba activate xtensor_env
|
||||
|
||||
|
||||
Specification files
|
||||
===================
|
||||
|
||||
The ``create`` syntax also allows you to use specification or environment files (also called *spec files*) to easily re-create environments.
|
||||
|
||||
The three supported syntaxes are: yaml, txt and explicit spec files.
|
||||
|
||||
Simple text spec files
|
||||
**********************
|
||||
|
||||
The ``txt`` file contains *one spec per line*. For example, this could look like:
|
||||
|
||||
.. code::
|
||||
|
||||
xtensor
|
||||
numpy 1.19
|
||||
xsimd >=7.4
|
||||
|
||||
|
||||
To use this file, pass:
|
||||
|
||||
.. code::
|
||||
|
||||
$ micromamba create -n from_file -f spec_file.txt -c conda-forge
|
||||
|
||||
.. note::
|
||||
You can pass multiple text spec files by repeating the ``-f,--file`` argument.
|
||||
|
||||
|
||||
YAML spec files
|
||||
***************
|
||||
|
||||
More powerful are ``YAML`` files like the following, because they already contain a desired environment name and the channels to use:
|
||||
|
||||
.. code::
|
||||
|
||||
name: testenv
|
||||
channels:
|
||||
- conda-forge
|
||||
dependencies:
|
||||
- python >=3.6,<3.7
|
||||
- ipykernel >=5.1
|
||||
- ipywidgets
|
||||
|
||||
They are used the same way as text files:
|
||||
|
||||
.. code::
|
||||
|
||||
$ micromamba create -f env.yml
|
||||
|
||||
.. note::
|
||||
CLI options will keep :ref:`precedence<precedence-resolution>` over *target prefix* or *channels* specified in spec files.
|
||||
|
||||
.. warning::
|
||||
``YAML`` spec files do not allow multiple files.
|
||||
|
||||
|
||||
Explicit spec files
|
||||
*******************
|
||||
|
||||
Using ``conda`` you can generate *explicit* environment lock files. For this, create an environment and execute:
|
||||
|
||||
.. code::
|
||||
|
||||
$ conda list --explicit --md5
|
||||
|
||||
These environment files look like the following and precisely "pin" the desired package + version + build string:
|
||||
|
||||
.. code::
|
||||
|
||||
# This file may be used to create an environment using:
|
||||
# $ conda create --name <env> --file <this file>
|
||||
# platform: linux-64
|
||||
@EXPLICIT
|
||||
https://conda.anaconda.org/conda-forge/linux-64/_libgcc_mutex-0.1-conda_forge.tar.bz2#d7c89558ba9fa0495403155b64376d81
|
||||
https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-ng-9.3.0-h2ae2ef3_17.tar.bz2#342f3c931d0a3a209ab09a522469d20c
|
||||
https://conda.anaconda.org/conda-forge/linux-64/libgomp-9.3.0-h5dbcf3e_17.tar.bz2#8fd587013b9da8b52050268d50c12305
|
||||
https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-1_gnu.tar.bz2#561e277319a41d4f24f5c05a9ef63c04
|
||||
https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-9.3.0-h5dbcf3e_17.tar.bz2#fc9f5adabc4d55cd4b491332adc413e0
|
||||
https://conda.anaconda.org/conda-forge/linux-64/xtl-0.6.21-h0efe328_0.tar.bz2#9eee90b98fd394db7a049792e67e1659
|
||||
https://conda.anaconda.org/conda-forge/linux-64/xtensor-0.21.8-hc9558a2_0.tar.bz2#1030174db5c183f3afb4181a0a02873d
|
||||
|
||||
To install such a file with ``micromamba``, just pass the ``-f`` flag again:
|
||||
|
||||
.. code::
|
||||
|
||||
$ micromamba create -n xtensor -c conda-forge -f explicit_env.txt
|
||||
Binary file not shown.
|
After Width: | Height: | Size: 32 KiB |
|
|
@ -0,0 +1,18 @@
|
|||
name: mamba-dev
|
||||
channels:
|
||||
- conda-forge
|
||||
dependencies:
|
||||
- yaml-cpp-static
|
||||
- libcurl=7.76.1=*_0
|
||||
- libcurl-static=7.76.1 *_0
|
||||
- xz-static
|
||||
- libssh2-static
|
||||
- libarchive=3.3
|
||||
- krb5-static
|
||||
- libsolv-static
|
||||
- libopenssl-static
|
||||
- zstd-static
|
||||
- libnghttp2-static
|
||||
- lz4-c-static
|
||||
- reproc-static
|
||||
- reproc-cpp-static
|
||||
Loading…
Reference in New Issue