#CONDA INSTALL PACKAGE LIST SOFTWARE#
#CONDA INSTALL PACKAGE LIST CODE#

Conda, on the other hand, can install Python packages as well as the Python interpreter. Conda was created specifically to handle this case scenario and can build packages in any language.Д«efore using pip, a Python interpreter must be installed. There are workarounds to create binary packages with some of these tools but the resulting product is strongly platform dependent and is thus not easy shareable. The main problem is that they are focused around Python while scientific codes and libraries are often a mix of Python, Fortran, C or C++, built against some platform dependent libraries. They are all very good environment management systems. You may already be aware of pip, easy_install, and virtualenv. Anaconda is a fairly large download, for people who are conservative about disk space, there is also Miniconda, a smaller distribution that includes only conda and Python. It is very popular in the Science / Data Science communities as it includes the most popular Python, R and Scala packages for data processing and analysis. Anaconda is a high performance open source data science platforms powered by Python and R. Conda PackagesД¬onda is a package, dependency and virtual environment manager that is included in the Anaconda Python distribution. An environment management system such as conda allows us to do so. Sharing a workflow environment is also paramount if we want to make sure that reproducibility can be effectively tested. This requires multiple environment that need to be managed efficiently.

We may do so by testing different libraries or even different version of a code. The very nature of scientific work is to explore and test things.

#CONDA INSTALL PACKAGE LIST CODE#

A normal user should be able to install and run code in a few minutes. This can quickly become a waste of resources. They also provide some degree of isolation: you can discard a container and restart from a fresh and clean system whenever you like.Дocker images/containers are often quite big and pulling a new image often means transferring gigabytes of data. Containers provide a complete environment with all the dependencies needed to run your software. We love docker containers, they are great for deploying services with dedicated functions on large systems such as Amazon cloud, Azure or Google cloud etc. Containers are convenient: users can pull a new Docker image after each release of the software, start a new container and use the code on any machine that can run Docker. The Underworld team has been using Docker Containers for a while. More often than not, users give up and potentially miss out on some very interesting tools. It is time consuming, requires some specific skills and creates unnecessary hurdles in a workflow. Users donвЂ™t want to spend time compiling code on their machine.

#CONDA INSTALL PACKAGE LIST SOFTWARE#

Conda packages are now available for most of the underworldcode suite of software ( Underworld, UWGeodynamics, Lavavu, Stripy) from the geo-down-under conda channel.

Conda install package list