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Python How Tos

Anaconda Environment Management

This page goes over the basics of Environment Management through the Anaconda Python distribution.

Why Anaconda Environments?

That’s a great question! An important part of science, especially computational science, is reproducibility. Being able to do an experiment on your own is great but it’s important to be able to regenerate figures, expand upon existing experiments in the future, and make the tools available to the broader research community. A major barrier to reproducibility in the world of computational science is package dependencies. Packages used within computer code can change over time and old code can break or the behavior can be modified in negative ways thanks to those changes. When sharing code, we want to be able to setup a computer ecosystem that is exactly the same as when we were developing the code. To do this, we use ‘environments.’ Anaconda is the most popular Python distribution for data science and is a great tool for environment management. Note: Environments are meant to serve as a way to ensure that Python package installations on separate systems are the same. Environments are not like GitHub repositories in the sense that they take a “snapshot” of the folder you are working in. If you accidentally delete a file that is not version controlled through software like Git, you can’t recover it with environments!

Installing Anaconda

Installing Anaconda is really simple. Go to the link, https://www.anaconda.com/distribution/#windows, and download the “Python 3.7 version.” Accept all default settings. Additionally, I find the Spyder IDE (Integrated Development Environment) to be helpful, although I do most of my code prototyping in the Jupyter Notebooks already installed with Anaconda. This can be installed by opening the Anaconda Navigation program and clicking the install button under the Sypder icon.

Getting Started with Environments

This section covers what you need to know to get up and running with Anaconda environments. An important note: Anaconda begins in the “base” environment. This environment is the one that is packaged with the Anaconda installation. However, you’ll want to create an environment for your specific project/repository.

Using an Existing Environment

If you are not starting an environment from scratch and are instead wishing to use an existing environment, follow these instructions.

Installing Existing Environment From Scratch

If you are installing the existing environment from scratch, meaning that you have not worked with this environment before, then follow these instructions:

  • Find the environment.yml file located in the repository that you are wishing to work with.
  • Open an Anaconda prompt
    • One way is
      • open Anaconda Navigator
      • switch to the Environments tab (left-hand side)
      • click on the arrow next to base (root)
      • open terminal
  • change directory to the folder containing the environment.yml file
  • type conda env create -f environment.yml in the prompt
    • Anaconda will handle the download and installation of all dependencies.
  • Start working with your up-to-date repository!

Updating Existing Environment

If you are updating your Anaconda Environment because someone has added a dependency to it, then follow these instructions:

  1. Find the environment.yml file located in the repository that you are wishing to update.
  2. Launch the Anaconda Prompt and activate the Anaconda Environment that you wish to update with conda activate myenv where myenv is the name of the Environment.
  3. Update the myenv environment with the environment.yml file that you located in step 1 by typing conda env update -f environment.yml into the Anaconda Prompt and hitting Enter.

Creating an Environment from Scratch

If you would like to create an environment from scratch, follow the instructions found at, https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html. The general workflow is as follows:

  1. Create environment by typing, conda create --name myenv where myenv is the name of the environment you would like to create, in the Anaconda Prompt.
  2. Activate the environment with conda activate myenv in the Anaconda Prompt.
  3. Develop code and install the requisite packages for the code as you go, using either the conda install --name myenv <package> or pip install <package> functionality, where <package> is the name of the python package you wish to install.

Using Environments

This section covers how to actually use environments.

General Workflow

The general workflow for using an environment is to:

  1. Create the environment, either from scratch or based off an existing environment.
  2. Activate the environment, either using the command line approach described in Via Command Line or using the Anaconda Navigator graphical user interface described in Via Anaconda Navigator. Anaconda begins in the base environment, but you’ll want to activate an environment for your specific project/repository.
  3. Do whatever you would like to do with Python.
  4. Either close the programs you were working on and the Anaconda programs or deactivate the environment with conda deactivate.

Executing Python (.py) Files

Python files can be executed in several ways with Anaconda.

Via Command Line

  1. Open the Anaconda Prompt.
  2. Create an environment or use an existing one, explained in Getting Started with Environments.
  3. Activate the environment using conda activate myenv where myenv is the name of your environment. If you choose not to do this step, you will be executing in the base environment that comes with Anaconda, not the specific environment for your project/repository.
  4. Run the python file as normal. This could look like python myfile.py, python3 myfile.py, etc. The procedure for running files should be well documented in the README of the repository you are working with.

Via Spyder IDE

Python files can also be run via the Spyder IDE. To do so:

  1. Follow the instructions found in Via Anaconda Navigator to open Spyder.
  2. Open the desired python file using Spyder.
  3. Click the green triangle “play” button to run the script.

Executing Applications

Anaconda has all sorts of applications that aid in developing Python. For example, Jupyter notebooks are incredibly helpful for prototyping and rapid development of Python code and Spyder is a great integrated development environment. To launch these applications, follow the instructions below.

Via Anaconda Navigator

  1. Open the Anaconda Navigator.
  2. Switch to the desired environment by clicking the drop-down menu next to the “Applications on” text. If you choose not to do this step, you will be executing in the base environment that comes with Anaconda, not the specific environment for your project/repository.
  3. Select the desired application from the list of applications.

Using Jupyter Notebooks

Jupyter notebooks are really helpful for prototyping code. To run one, do the following:

  1. Follow the instructions under Via Anaconda Navigator to open the Jupyter Notebook application. This should open a browser displaying the files on your system.
  2. Navigate to the repository you are wanting to work with by clicking through the file structure.
  3. Click on the notebook (.ipynb) you are wanting to run to open a new browser tab of your notebook.

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