CODEWITHSUNDEEP
pythonpipanacondaconda
Ehsan Sh
Ehsan Sh

Reputation: 237

Conflict resolution in pip vs. conda

I assume both pip and conda, despite differences, are package managers and check for consistency of packages installed in an environment! In my case though, I have a list of requirements.txt, on top of python=3.6. In my conda virtual environment, I installed them one-by-one. The strange thing is that when locating some packages in anaconda.org channels and installing them with conda install, conda complains! An example is when I tried to install statistics=1.0.3.5, and I got this message on terminal:

UnsatisfiableError: The following specifications were found
to be incompatible with the existing python installation in your environment:

Specifications:

  - statistics=1.0.3.5 -> python[version='2.7.*|<3|>=2.7,<2.8.0a0']

Your python: python=3.6

However, when I did it with pip, it worked!

Why is that?

Am I going to bump into a problem down the road with this package?

I read this Stackoverflow post about the difference between pip and conda and tried to understand it from the doc (Although not that successful).

Upvotes: 1

Views: 1783

Answers (1)

Peter
Peter

Reputation: 12295

When working with conda virtual environments, installing packages with pip should be the last resort. If a package isn't available through the default channel, try installing from conda-forge first.

The difference between conda and pip is huge (not to mention virtual environments): Conda aims to install a consistent set of packages - which results in an optimization problem - while pip just installs dependencies, no matter if that is in conflict with any previously installed package.

However, since you are writing unit tests with your code you'll immediatly realize if you bump into a problem.

Upvotes: 1

Related Questions