What is virtual environment in python

New in version 3.3. Source code: The venv module supports creating lightweight “virtual environments”, each with their own independent set of Python packages installed in their site directories. A virtual environment is created on top of an existing Python installation, known as the virtual environment’s “base” Python, and may optionally be isolated from the packages in the base environment, so only those explicitly installed in the virtual environment are available. When used from within a virtual environment, common installation tools such as See PEP 405 for more background on Python virtual environments. python - m venv / path / to / new / virtual / environment Running this command creates the target directory (creating any parent directories that don’t exist already) and places a pyvenv.cfg file in it with a home key pointing to the Python installation from which the command was run (a common name for the target directory is .venv). It also creates a bin (or Scripts on Windows) subdirectory containing a copy/symlink of the Python binary/binaries (as appropriate for the platform or arguments used at environment creation time). It also creates an (initially empty) lib/pythonX.Y/site-packages subdirectory (on Windows, this is Lib\site-packages). If an existing directory is specified, it will be re-used. usage: venv [-h] [--system-site-packages] [--symlinks | --copies] [--clear] [--upgrade] [--without-pip] [--prompt PROMPT] [--upgrade-deps] ENV_DIR [ENV_DIR ...] Creates vi...

Python Tutorials → In-depth articles and video courses Learning Paths → Guided study plans for accelerated learning Quizzes → Check your learning progress Browse Topics → Focus on a specific area or skill level Community Chat → Learn with other Pythonistas Office Hours → Live Q&A calls with Python experts Podcast → Hear what’s new in the world of Python Books → Round out your knowledge and learn offline Unlock All Content → • Watch Now This tutorial has a related video course created by the Real Python team. Watch it together with the written tutorial to deepen your understanding: Working With Python Virtual Environments In this tutorial, you’ll learn how to work with venv module to create and manage separate By the end of this tutorial, you’ll know how to: • Create and activate a Python virtual environment • Explain why you want to isolate external dependencies • Visualize what Python does when you create a virtual environment • Customize your virtual environments using optional arguments to venv • Deactivate and remove virtual environments • Choose additional tools for managing your Python versions and virtual environments Virtual environments are a common and effective technique used in Python development. Gaining a better understanding of how they work, why you need them, and what you can do with them will help you master your Python programming workflow. Free Bonus: Throughout the tutorial, you can select code examples for either Windows, Ubuntu Linux, or macOS. Pick ...

By default, every project on your system will use these same directories to store and retrieve site packages (third-party libraries). How does this matter? Now, in the above example of two projects, you have two versions of Django. This is a real problem for Python since it can’t differentiate between versions in the “site-packages” directory. So both v1.9 and v1.10 would reside in the same directory with the same name. This is where virtual environments come into play. To solve this problem, we just need to create two separate virtual environments for both projects. The great thing about this is that there are no limits to the number of environments you can have since they’re just directories containing a few scripts. A virtual Environment should be used whenever you work on any Python-based project. It is generally good to have one new virtual environment for every Python-based project you work on. So the dependencies of every project are isolated from the system and each other. How does a virtual environment work? We use a module named virtualenv which is a tool to create isolated Python environments. virtualenv creates a folder that contains all the necessary executables to use the packages that a Python project would need. Installing virtualenv $ pip install virtualenv Test your installation: $ virtualenv --version Using virtualenv You can create a virtualenv using the following command: $ virtualenv my_name After running this command, a directory named my_name will b...

Installing packages using pip and virtual environments This guide discusses how to install packages using pip and a virtual environment manager: either venv for Python 3 or virtualenv for Python 2. These are the lowest-level tools for managing Python packages and are recommended if higher-level tools do not suit your needs. Note This doc uses the term package to refer to a Distribution Package which is different from an Import Package that which is used to import modules in your Python source code. Installing pip pip is the reference Python package manager. It’s used to install and update packages. You’ll need to make sure you have the latest version of pip installed. Note If you are using Python 3.3 or newer, the venv module is the preferred way to create and manage virtual environments. venv is included in the Python standard library and requires no additional installation. If you are using venv, you may skip this section. virtualenv is used to manage Python packages for different projects. Using virtualenv allows you to avoid installing Python packages globally which could break system tools or other projects. You can install virtualenv using pip. py -m pip install --user virtualenv Creating a virtual environment venv (for Python 3) and virtualenv (for Python 2) allow you to manage separate package installations for different projects. They essentially allow you to create a “virtual” isolated Python installation and install packages into that virtual installation. When ...

When developing software with Python, a basic approach is to install Python on your machine, install all your required libraries via the terminal, write all your code in a single .py file or notebook, and run your Python program in the terminal. This is a common approach for a lot of beginners and many people transitioning from working with Python for data analytics. This works fine for simple Python scripting projects. But in complex software development projects, like building a Python library, an API, or software development kit, often you will be working with multiple files, multiple packages, and dependencies. As a result, you will need to isolate your Python development environment for that particular project. Consider this scenario: you are working on app A, using your system installed Python and you pip install packageX version 1.0 to your global Python library. Then you switch to project B on your local machine, and you install the same packageX but version 2.0, which has some breaking changes between version 1.0 and 2.0. When you go back to run your app A, you get all sorts of errors, and your app does not run. This is a scenario you can run into when building software with Python. And to get around this, we can use virtual environments. This tutorial will cover everything you need to know about virtual environments and how to set one up with Virtualenv. What is a Virtual Environment? Python's official documentation says: "A virtual environment is a Python enviro...

12. Virtual Environments and Packages 12.1. Introduction Python applications will often use packages and modules that don’t come as part of the standard library. Applications will sometimes need a specific version of a library, because the application may require that a particular bug has been fixed or the application may be written using an obsolete version of the library’s interface. This means it may not be possible for one Python installation to meet the requirements of every application. If application A needs version 1.0 of a particular module but application B needs version 2.0, then the requirements are in conflict and installing either version 1.0 or 2.0 will leave one application unable to run. The solution for this problem is to create a virtual environment, a self-contained directory tree that contains a Python installation for a particular version of Python, plus a number of additional packages. Different applications can then use different virtual environments. To resolve the earlier example of conflicting requirements, application A can have its own virtual environment with version 1.0 installed while application B has another virtual environment with version 2.0. If application B requires a library be upgraded to version 3.0, this will not affect application A’s environment. 12.2. Creating Virtual Environments The module used to create and manage virtual environments is called venv. venv will usually install the most recent version of Python that you have a...

• • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • Topics Edit Python environments in VS Code An "environment" in Python is the context in which a Python program runs that consists of an interpreter and any number of installed packages. Note: If you'd like to become more familiar with the Python programming language, review Types of Python environments Global environments By default, any Python interpreter installed runs in its own global environment. For example, if you just run python, python3, or py at a new terminal (depending on how you installed Python), you're running in that interpreter's global environment. Any packages that you install or uninstall affect the global environment and all programs that you run within it. Tip: In Python, it is best practice to create a workspace-specific environment, for example, by using a local environment. Local environments There are two types of environments that you can create for your workspace: virtual and conda. These environments allow you to install packages without affecting other environments, isolating your workspace's package installations. Virtual environments A virtual environ...

In this tutorial, we'll learn about Python virtual environments, the benefits of using virtual environments, and how to work inside virtual environments. After you finish this tutorial, you’ll understand the following: • • • • • If you need to install Python on Mac, refer to the Note: that this tutorial is mainly for macOS and Linux users; however, Windows users should also be able to follow along. What Are Python Virtual Environments? A Python virtual environment consists of two essential components: the Python interpreter that the virtual environment runs on and a folder containing third-party libraries installed in the virtual environment. These virtual environments are isolated from the other virtual environments, which means any changes on dependencies installed in a virtual environment don’t affect the dependencies of the other virtual environments or the system-wide libraries. Thus, we can create multiple virtual environments with different Python versions, plus different libraries or the same libraries in different versions. The figure above illustrates what you have on your system when we create multiple Python virtual environments. As the illustration above shows, a virtual environment is a folder tree containing a specific Python version, third-party libraries, and other scripts; thus, there is no limitation on the number of virtual environments on a system because they are just folders containing some files. Why Are Python Virtual Environments Important? The im...

Python virtual environments allow you to install Python packages in an isolated location from the rest of your system instead of installing them system-wide. Let’s look at how to use the Python venv, short for Python virtual environment, also abbreviated as virtualenv. In this article, you will learn: • The advantages of using virtual environments • How to create a venv • How to activate and deactivate it • Different ways to delete or remove a venv • How a venv works internally Table of Contents • 1 Why you need virtual environments • 2 Virtual environments vs. other options • 3 How to create a Python venv • 4 Python venv activation • 5 How a Python venv works • 6 Deactivate the Python venv • 7 Deleting a Python venv • 8 Follow the course • 9 Learn more • 10 Conclusion Why you need virtual environments There are multiple reasons why virtual environments are a good idea, and this is also why I’m telling you about them before we continue to the part where we start installing 3rd party packages. Let’s go over them one by one. Preventing version conflicts You could argue that installing third-party packages system-wide is very efficient. After all, you only need to install it once and can use the package from multiple Python projects, saving you precious time and disk space. There’s a problem with this approach that may start to unfold weeks or months later, however. Suppose your project, Project A, is written against a specific version of library X. In the future, you might n...