Does Conda replace the need for virtualenv?

Question

I recently discovered Conda after I was having trouble installing SciPy, specifically on a Heroku app that I am developing.

With Conda you create environments, very

Answer 1

Virtual Environments and pip

I will add that creating and removing conda environments is simple with Anaconda.

> conda create --name  python= 

> conda remove --name  --all 

In an activated environment, install packages via conda or pip:

(envname)> conda install 

(envname)> pip install 

These environments are strongly tied to conda's pip-like package management, so it is simple to create environments and install both Python and non-Python packages.

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Jupyter

In addition, installing ipykernel in an environment adds a new listing in the Kernels dropdown menu of Jupyter notebooks, extending reproducible environments to notebooks. As of Anaconda 4.1, nbextensions were added, adding extensions to notebooks more easily.

Reliability

In my experience, conda is faster and more reliable at installing large libraries such as numpy and pandas. Moreover, if you wish to transfer your the preserved state of an environment, you can do so by sharing or cloning an env.