Introductory Material

Introduction to Conda


Teaching: 30 min
Exercises: 10 min
  • What is Conda?

  • Why should I use it?

  • explore the benefits of python environments

  • discuss how conda can allow you to make the “perfect python environment”

We will start this tutorial by looking at a picture of the perfect python environment. Perfect Python Environment

Definition of python virtual environment: a self-contained directory tree that contains a Python installation for a particular version of Python, plus a number of additional packages.

Python Environment Discussion

What are the benefits of having a well defined python environment?


  1. Avoid future breakage if any dependencies changes
  2. Allows better collaboration among team
  3. Reliability

Ways to create environments and manage packages in Python

  1. The most classic is with pip as a python package manager, along with virtualenv as the python environment manager.
  2. Next modern classic pipenv as a python package and environment manager.
  3. What we’ll learn, conda.

Review from Preliminary

What is conda?

Flavors of conda

Exercise: Let’s try creating a python environment

Scenerio 1: Bob is a post-doc. He has been programming in Python for a few years now, and he is very comfortable managing his own python environment, previously using pip and virtualenv, but now he’s with the “cool” kids using pipenv. Recently, his studies are shifting more towards a geospatial focus, and he will need python libraries such as gdal, fiona, and netcdf. Let’s see what happens.

Bob’s adventure

# First bob installs the new pipenv
pip install pipenv

# Next he creates a folder for his new geoproject
mkdir geoproject

# Next bob creates a requirements.txt using vim text editor so he can share this later
vi requirements.txt

# In requirements.txt
# ipython
# requests
# fiona
# gdal
# netCDF4

# Now he installs those packages
pipenv install -r requirements.txt

# Bob got an error
    legacy_results = self.get_legacy_dependencies(ireq)
 File "/usr/local/lib/python3.6/site-packages/pipenv/patched/piptools/repositories/", line 335, in get_legacy_dependencies
 File "/usr/local/lib/python3.6/site-packages/pipenv/patched/notpip/_internal/", line 107, in resolve
    self._resolve_one(requirement_set, req)
 File "/usr/local/lib/python3.6/site-packages/pipenv/patched/notpip/_internal/", line 264, in _resolve_one
    abstract_dist = self._get_abstract_dist_for(req_to_install)
 File "/usr/local/lib/python3.6/site-packages/pipenv/patched/notpip/_internal/", line 214, in _get_abstract_dist_for
 File "/usr/local/lib/python3.6/site-packages/pipenv/patched/notpip/_internal/operations/", line 328, in prepare_linked_requirement
    abstract_dist.prep_for_dist(finder, self.build_isolation)
 File "/usr/local/lib/python3.6/site-packages/pipenv/patched/notpip/_internal/operations/", line 155, in prep_for_dist
 File "/usr/local/lib/python3.6/site-packages/pipenv/patched/notpip/_internal/req/", line 486, in run_egg_info
    command_desc='python egg_info')
 File "/usr/local/lib/python3.6/site-packages/pipenv/patched/notpip/_internal/utils/", line 698, in call_subprocess
    % (command_desc, proc.returncode, cwd))
pipenv.patched.notpip._internal.exceptions.InstallationError: Command "python egg_info" failed with error code 1 in /tmp/tmp_5d7wspdbuild/GDAL/

# Bob looked at, but it's still really confusing to set this up... HELP!

Scenerio 2: In the other side of the world, we meet Sandy. She is an advanced undergrad that has attended one of the hackweek at UW eScience. She just started to really program in Python. Her senior thesis project requires her to analyze a geospatial entity. Similar to bob she knows that she will need to use gdal, fiona, and netcdf. Having learned about conda in the hackweek she started following the conda workflow in creating a new project. Let’s see what happens.

Sandy’s adventure

# Sandy has installed conda into her linux machine, so her first step now is to make a new directory for the project
mkdir geoproject

# Next Sandy creates an environment.yml using vim text editor so she can share this later
vi environment.yml

# In environment.yml
# name: geoproj
# channels:  
#   - conda-forge
# dependencies:
#   - python=3.6
#   - ipython
#   - requests
#   - fiona
#   - gdal
#   - netCDF4

# Now she installs those packages
conda env create -f environment.yml

# Sandy suceeded in the install after a few minutes
Preparing transaction: done
Verifying transaction: done
Executing transaction: done
# To activate this environment, use
#     $ conda activate geoproj
# To deactivate an active environment, use
#     $ conda deactivate

# Sandy activated her new geoproj python environment, and check whether gdal works.
conda activate geoproj
gdalinfo --version
GDAL 2.2.4, released 2018/03/19
ogr2ogr --version
GDAL 2.2.4, released 2018/03/19

So, what’s going on? why didn’t pipenv work?

NOTE: Conda can manage pip packages, but pip cannot manage conda packages

Concepts of conda

Before start let’s ensure that you have conda installed either via Miniconda or Anaconda

# Check conda version to make sure it's installed.
conda info

Conda Help and Manual

To see the full documentation for any command, type the command followed by --help. For example, to learn about the conda update command:

$ conda update --help

1. Environments

Conda environments

What is a conda environment?

# List out available environments
conda env list # The starred * environment is the current activate environment

# Create conda environment from command line (Not Best Practice)
conda create --name myenv --channel conda-forge python=3.6

# Activate conda environment
conda activate myenv

# Deactivate conda environment
conda deactivate

# Create conda environment from environment file (Recommended Best Practice)
conda env create --file environment.yml

# Removing conda environments
conda env remove --yes --name myenv

Best practice to share environments

  1. When starting a new environment, always generate it from an environment file rather than the command line.
  2. As you add packages to the environment, be sure to update the environment file.
  3. Unless you have to (i.e. Production Environments), try to avoid specifying the version of each package. This will ensure you have the most up to date version that will work across platform.

If you follow these guidelines, you should be able to give your environment file to anyone, and they will be able to install your packages with no problem.

2. Channels

Conda channels

What is a conda channel?

# List out your channels and priorities
conda config --get channels

# If you have a few trusted channels that you prefer to use, you can pre-configure these so that everytime you are creating an environment, you won’t need to explicitly declare the channel.
conda config --add channels conda-forge

NOTE: The highest priority channel is where your packages will be installed from no matter if another channel has a higer version!

Conda Forge (

Conda forge is a community led collection of recipes, build infrastructure and distributions for the conda package manager.

Watch Filipe’s talk from pycon, one of the conda-forge lead developer, for more info about how to put your packages into the conda-forge channel!

3. Packages

What is a conda package?

You can search for conda packages at or the terminal shown below.

# Look at the packages you have installed
conda list

# Let's search for gdal conda
conda search gdal

# Install a single conda package
conda install -c conda-forge gdal

# Or install multiple packages
conda install -c conda-forge gdal fiona

# Removing a conda package
conda remove -n myenv gdal

4. Recipes

Instruction on how to compile the conda package and its metadata

  name: pandas
  sha256: d9f67bb17f334ad395e01b2339c3756f3e0d0240cb94c094ef711bbfc5c56c80
  number: 0
  script: python install --single-version-externally-managed --record=record.txt
  license: BSD 3-clause
  summary: 'High-performance, easy-to-use data structures and data analysis tools.'
    - jreback
    - jorisvandenbossche
    - TomAugspurger

For official walkthrough go to

Key Points