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Ivy logo

Anaconda and conda

One feature of Python that makes it a great language for science is its abundance of packages (numpy! scipy! pandas! xarray! landlab!). Package management can be difficult, though, especially when a typical Python installation may contain dozens of packages.

This is where the conda package manager is handy, and a primary reason why CSDMS uses (and we recommend) the Anaconda Distribution.

Learning objectives:

  • Learn what a package manager is, and why it's useful
  • Understand what a virtual environment is
  • Execute basic conda commands to set up a vitual environment

Conda

With conda, you can:

  • install
  • list
  • update
  • remove

packages from a Python installation. conda ensures that the packages work together without conflict.

Because much of our work with Ivy takes place on EarthscapeHub, we don't spend much time on conda here; however, we recommend installing Anaconda on your computer so that you can use all of the CSDMS Ivy course material locally.

Further, to ensure you have all the correct packages needed to use the course material, we ask that you set up a virtual environment, an independent, isolated, Python installation managed by conda. To do so, we'll need an environment file from the Ivy repository.

In a terminal, change to the Ivy repository directory and view the file environment.yaml with cat:

# A conda environment file for the CSDMS Ivy lessons.
#
# This file is used to create the `ivy` environment on Linux, macOS, and
# Windows. See "environment.unix.yaml" for additional packages that aren't
# available on Windows.
#
# Usage:
#   $ conda env create --file environment.yaml
#   $ conda activate ivy

name: ivy
channels:
  - conda-forge
dependencies:
  - python >=3.9
  - bmi-topography
  - bmipy
  - imageio
  - landlab >=2.5
  - matplotlib
  - notebook
  - numpy
  - pandas
  - pip
  - pymt >=1.3
  - pymt_child
  - pymt_hydrotrend
  - rasterio
  - scipy
  - terrainbento
  - tqdm
  - nox
  - pip:
    - git+https://github.com/csdms/bmi-example-python.git

The environment file lists the packages needed to run the course material. If a package has a dependency not explicitly listed (e.g., pymt is built on xarray), conda finds a compatible package version for you.

To create the environment, type:

$ conda env create --file environment.yaml

Once the environment has been created, type

$ conda activate ivy

to make this environment current. (Note on Linux and macOS, you may have to use source instead of conda to activate the environment.)

Some packages used in Ivy aren't built for Windows. These packages have been listed in a second environment file, environment.unix.yaml. To update the ivy environment on Linux or macOS with these packages, type:

$ conda env update --name ivy --file environment.unix.yaml --prune

Later, when finished using the environment, type

$ conda deactivate

to return to the base environment, and

$ conda remove -n ivy --all

to fully remove the environment and all its packages from your Anaconda installation.

Mamba

mamba is a drop-in replacement for conda. It supports most conda commands, and it's typically faster, since it reimplements the slower parts of conda in C++. Learn more about mamba at its GitHub repository and through its documentation.

Summary

While Python is installed with most operating systems, or can be downloaded and installed from source, CSDMS recommends the use of Anaconda because of its conda package management system.

This table summarizes conda concepts covered in this section:

Concept Description
package manager a tool for managing Python packages, ensuring compatibility
environment an independent, isolated Python installation managed by conda
environment file a file specifying the packages that make a conda environment

This table summarizes the conda subcommands used in this section:

Subcommand Description
list lists all packages installed in an environment
create make a new environment from a file
install adds a new package into an environment
remove uninstalls a package from an environment
update gets newer versions of packages in an environment

This table summarizes shell commands used in this section:

Command Description
source runs a script on a Unix-based operating system

Resources