mamba is a CLI tool to manage
conda s environments.
If you already know
conda, great, you already know
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 concepts first.
mamba create command creates a new environment.
You can create an environment with the name
nameofmyenv by calling:
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:
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.
conda activate myjlabenv mamba install bqplot # now you can use bqplot in myjlabenv
mambais a drop-in replacement and uses the same commands and configuration options as
mamba install ... mamba create -n ... -c ... ... mamba list
mamba comes with features on top of stock
To efficiently query repositories and query package dependencies you can use
Here are some examples:
# 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
$ 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.
$ 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
-t,--tree flag, you can get the same information in a tree.