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Conda install package for python 3 how to#
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Conda install package for python 3 download#

However, our workflows usually specify a small to medium number of pinned dependencies. The results above aren’t close to being a formal benchmark, but are simply representative of the kinds of gains you can make with mamba out of the box. How much faster is Mamba? We took the environmental dependencies of the Medaka project from Bioconda, unpinned their versions (to make it harder for the package manager to solve the problem) and timed how long Miniconda and Mamba took to re-create the environment respectively: m5.12xLarge (48cpus, ~200gigs RAM)Īs we can see, Mamba’s performance is significantly better when dealing with a complex environment like this. Mamba install python=3.8 jupyter -c conda-forge # Or if you don't have anything, use miniforge's mambaforge

Conda install package for python 3 how to#

Here’s how to get started with Mamba: # Again, assuming linuxĬonda install mamba -n base -c conda-forge Mamba is most akin to Miniconda, in that it comes with Python, but doesn’t ship with a whole load of extra software.

This is where Mamba comes in, the fast drop-in replacement for conda, which reimplements the slow bits in in C++.

Conda install package for python 3 download#

Whilst Miniconda is small as compared with full-fat anaconda, the latest Miniconda3 Linux 64-bit Python 3.9 download size is 58.6 MiB, could this be better?

How big will the docker image be? We want to make sure that our images are as small as possible to make it quicker to download for our users.

How long does a CI job take? Conda has a reputation for taking its time when dealing with complex sets of dependencies and we owe it to ourselves to make sure that CI jobs don’t take longer than they need to.

Hence, we need to think about the following: In order to test and distribute our workflows, we have CI (continuous integration) pipelines set-up to automatically build docker images each time a workflow is updated, which can be many times a day for the development version of a given project.

Conda install package for python 3 software#

in research, but when it comes to moving bioinformatics software into production, there are some extra considerations we have to make. Miniconda is great for general purpose use, e.g. To get up and running with Miniconda, the instructions from Bioconda are easy to follow:Ĭonda install python=3.8 jupyter -c conda-forge This makes it ideal for quickly getting a new environment up and running. Miniconda installs Conda and Python, but it doesn’t include all the extra scientific packages.Anaconda includes Conda and is the scientific distribution that comes with many packages pre-installed alongside Python.It’s known as a Python package manager, but really it’s a general purpose system that is also highly portable. Conda is a great choice for installing scientific software, permitting users to manage multiple isolated and reproducible environments.