Antwort What is the best Python virtual env? Weitere Antworten – Which virtual environment is best for Python
TLDR: There are three main options for creating and managing virtual environments in Python: pipenv , conda and venv . pipenv is superior to venv and conda . Learn to use pipenv first and you will not have to waste time learning the other two.Getting Started
- Create a virtual environment in your current directory for a project with the command: virtualenv my_project. "my_project" is whatever name you would like to give this environment.
- To create a virtual environment with a specific version of python use the command: virtualenv -p /usr/bin/python2.7 my_project.
A virtual environment is a tool that helps to keep dependencies required by different projects separate by creating isolated Python virtual environments for them. This is one of the most important tools that most Python developers use.
Should I use venv or conda : Choosing the right environment management tool depends on your needs. If you need a simple, easy-to-use tool, venv might be the best choice. If you're dealing with complex dependencies, Conda env is the way to go. If you need to switch between different Python versions, consider pyenv or virtualenv.
Which virtual environment is best
- Vanilla venv. You know it. There are to many commands and explicit steps.
- pipenv. This is very near to what I am looking for.
- virtualenv. Faster than venv but also has this extra source step.
- virtualwrapper. Uncomfortable in its usage.
- poetry , conda & Co. Far to much, heavy and powerful for what I try to achieve.
Why is poetry better than Conda : Poetry emerges as a modern and organized solution for Python dependency management, offering improved organization, version control, and flexibility compared to traditional tools like Pip and Conda.
If you're a developer working on multiple Python projects in parallel, you should use distinct virtual environments for each project. This practice makes working on multiple projects more organized and also reduces the risks of code execution errors.
Always use a Virtual Environment
You can have as many venvs as you want. For an additional layer of control over when you update to new versions of Python, you can compile your own Python interpreter and create a virtual environment based on it.
Should I use Python virtual environment
If you're a developer working on multiple Python projects in parallel, you should use distinct virtual environments for each project. This practice makes working on multiple projects more organized and also reduces the risks of code execution errors.Top Python IDEs
- IDLE. IDLE (Integrated Development and Learning Environment) is a default editor that accompanies Python.
- PyCharm. PyCharm is a widely used Python IDE created by JetBrains.
- Visual Studio Code. Visual Studio Code is an open-source (and free) IDE created by Microsoft.
- Sublime Text 3.
- Atom.
- Jupyter.
- Spyder.
- PyDev.
The choice between venv and Anaconda depends on your needs: For minimal environments: If you prefer lightweight, minimal environments, venv is the better choice. For data science projects: If you're working on data science projects and need a wide range of pre-installed packages, Anaconda is more suitable.
Key Differences at a Glance
Scope: Venv is Python-exclusive, while Conda is language-agnostic. Package Management: Venv doesn't handle package dependencies itself, whereas Conda excels in this area.
Why is poetry better than conda : Poetry emerges as a modern and organized solution for Python dependency management, offering improved organization, version control, and flexibility compared to traditional tools like Pip and Conda.
Which is better, venv or virtualenv : These are almost completely interchangeable, the difference being that virtualenv supports older python versions and has a few more minor unique features, while venv is in the standard library.
Why use poetry over venv
Just like virtualenv and venv , Poetry creates isolated environments for projects. However, it also ensures reproducibility by locking dependencies to specific versions, guaranteeing that your project works the same way across different environments.
Not everyone might use Poetry, but since Pip has been around forever, it may be worth the ease of use to just use Pip. But if your project and your workload value the importance of organization and are willing to explore new tools to improve your process, Poetry is a tool you should consider.This command creates a new virtual environment in the specified directory. venv offers several advantages over virtualenv , such as: Faster creation and activation of virtual environments. A more secure and up-to-date implementation.
Should I create virtual environment or Anaconda : The choice between venv and Anaconda depends on your needs: For minimal environments: If you prefer lightweight, minimal environments, venv is the better choice. For data science projects: If you're working on data science projects and need a wide range of pre-installed packages, Anaconda is more suitable.