This base image ships with Conda pre-installed, but we’re not relying on any existing Python install, we’re installing a new one in the new environment. Here’s what the pip requirements.txt would look like:įROM continuumio/miniconda3 COPY environment.yml.
#Conda python versions install
Conda packages include Python libraries (NumPy or matplotlib), C libraries ( libjpeg), and executables (like C compilers, and even the Python interpreter itself).įor example, let’s say you want to install Python 3.9 with NumPy, Pandas, and the gnuplot rendering tool, a tool that is unrelated to Python.Pip packages are Python libraries like NumPy or matplotlib.The fundamental difference between pip and Conda packaging is what they put in packages. The starting point: which kind of dependencies? Focusing on the Conda-Forge package repository Conda has multiple package repositories, or “channels”.īy the end you should understand why Conda exists, when you might want to use it, and the tradeoffs between choosing each one.Linux, including running on Docker, though with some mention of macOS and Windows.Python only Conda has support for other languages but I won’t go into that.While it’s not possible to answer this question for every situation, in this article you will learn the basic differences, constrained to: What are the tradeoffs between the two?.
If you’re using Python in the world of data science or scientific computing, you will soon discover that Python has two different packaging systems: pip and Conda.
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