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. 👉 This article is also published on Towards Data Science blog.
0 kommentar(er)
