#MINICONDA VS ANACONDA PYTHON INSTALL#
#MINICONDA VS ANACONDA PYTHON MANUAL#
#MINICONDA VS ANACONDA PYTHON FULL#
#MINICONDA VS ANACONDA PYTHON SOFTWARE#

You would be surprised how many excellent professionals, even with 5+ years of experience still struggle with chaotic, corrupted, and barely usable Python installations because of that.

#MINICONDA VS ANACONDA PYTHON FULL#

We also tried other alternatives and always go back to conda because it is the only, let's say, full featured solution on the market.īased on my experience of more than 6 years doing Data Science, conda (and virtual environments in general) is a tool that is often not well understood. We use it for both development and production purposes and we strongly believe that conda stands out from other alternatives like virtualenv, poetry, pyenv or pipenv.

#MINICONDA VS ANACONDA PYTHON INSTALL#

This post is about conda, the tool we use to install and manage Python and its libraries in our systems. This is the first post of the WhiteBox toolkit series, where we will tell you more about the tools we use in our everyday job, in high detail. This means you can save time and effort in building your images.There are two types of Data Scientists, those who took the time to master conda and those who don't (and cry at the corners because of that). Best of all? It’s only ~13 MiB to download. with no dependency on Conda, and that doesn’t include a default Python version making it perfect for setting up fresh environments with as small a footprint as possible. Micromamba is a standalone binary version of Mamba, i.e. This is where Micromamba comes into play!

#MINICONDA VS ANACONDA PYTHON MANUAL#

The download size for the mambaforge package is ~100 MiB, which is a fair bit larger than Miniconda is.įor regular use, this isn’t a big deal, but when you’re trying to create lean docker images in a production environment without requiring lots of space-saving manual intervention, it helps to have as small a download as possible. Because it depends on Conda, either way of installing it means you end up with both package managers on your system. Mamba is definitely faster than Miniconda, but unfortunately it is still quite a wedge to download. This may be important if the computers where your CI jobs are running are particularly weak. In addition, on the smallest instance Miniconda failed to complete its task because it ran out of memory and the process was unceremoniously terminated. This may seem like a significant step down from the massive gains seen previously, but factor this out over a year’s worth of CI runs and one starts to see how this could be beneficial, especially if you’re paying for CI time. In general, even for this relatively small environment, Mamba was approximately half a minute quicker to set everything up. 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++. 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.

#MINICONDA VS ANACONDA PYTHON 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. Conda install python=3.8 jupyter -c conda-forge Workflows in production

Miniconda vs anaconda python