#MINICONDA VS ANACONDA PYTHON INSTALL#
You can install a fresh conda environment by running the following command Besides, conda can install PyPI packages by using pip in an active conda environment. Not only that, but it is language-agnostic too. Unlike conda, both virtualenv and Pipenv are Python environments only.Īs you may note from the introduction, conda manages the environment and the packages, and the dependencies.I want to have the flexibility to install conda packages.However, the main reason I will not consider virtualenv nor the Pipenv as the environment managers are: Pipenv was created to address many shortcomings of virtualenv. You can install conda packages by running conda install package_name in your conda environment. Python libraries can also be packaged using conda, and a popular host for conda packages is Anaconda.
You can install packages from PyPI by running pip install package_name. The most popular Python package repository is the Python Package Index (PyPI), a public repository for many Python libraries. Let’s first list different groups of technologies and highlight few tools In this post, library and package are used interchangeably, and they both refer to the Python package.
Then, we will go over an ideal setup (of course, in my opinion 🙂) suitable for most Python projects using conda and Poetry. This post discusses different available technologies for Python packaging, environment, and dependencies management systems. There are various tools for creating an isolated environment and install the libraries you need for your project. If you work on multiple Python projects at different development stages, you probably have different environments on your system. Most respondents, including myself, seem to be recommending using a standard Python installation with virtual environments and package installations within those environments as required on a per project basis.👉 This article is also published on Towards Data Science blog. My point to you is that you seemed to be comparing IDEs/Editors with Anaconda, which did not make any sense on the grounds that you can configure almost any IDE/Editor to use whatever Python stack virtual environment (keeping in mind that this is what Anaconda is) you wish. In either case, additional modules/packages can be installed (using pip and conda - pip can be used for Anaconda Python if Anaconda does not offer a version of the package but one is available for pip).
#MINICONDA VS ANACONDA PYTHON PC#
Previously I was using vscode as my editor, but that's running off my plain python, not anaconda, so I can't use that when I'm using numpy and pandas without installing those separately or switching environment in vscode.Ĭan't find a clear answer in a bit of searching so my questions are:ġ) is there any reason I shouldn't use anaconda over python for everything Ģ) should I uninstall anaconda and just install the libs I want like numpy into my basic python ģ) is there a way to get my vscode to automatically assign anaconda as my environment for when I want to use numpy etc and default to my plain python otherwise?Īlso, very minor but is there a program wrapper for pc or mac for jupyter? anaconda has the shortcut which is good but in an ideal world I'd rather have a dedicated app for jupyter than have it run in browser A friend of mine recommended I install anaconda separately from my default python to use as my base for when I'm using jupyter etc so that's what I've been doing for now.
So I've been learning python for a little while and I'm starting to use jupyter notebooks.
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