For most Python projects, create a local .venv folder with python -m venv .venv, activate it in your terminal, and install packages using python -m pip. The environment keeps project packages separate from other Python installations; it does not copy the entire Python installation or standard library.
What a Python virtual environment does
A virtual environment gives a project its own package installation area and interpreter context. That lets one project use a dependency version without changing packages used by another project or by the global Python installation. The standard library is shared with the base Python installation rather than duplicated. See the PyPA virtual-environment specification.
Use an environment per project, commonly in a folder named .venv at the project root. This is a practical convention, not a requirement: the environment can be created elsewhere, but keeping it beside the project makes it easier to identify and exclude from version control.
Create an environment
Open a terminal in your project directory and run the command for your platform. The Python command you choose determines which installed base interpreter creates the environment; creating a virtual environment does not install or select a different Python version.
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- Unix or macOS:
python3 -m venv .venv - Windows:
py -m venv .venv
If the project requires a particular Python installation, invoke that interpreter explicitly instead of assuming that python3 or py points to it. The PyPA setup guide documents these basic platform commands.
Activate the environment and verify Python
Activation adjusts the current shell’s PATH so that commands such as python and pip resolve to the environment first. Use the activation command for your shell:
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- Unix or macOS, bash or zsh:
source .venv/bin/activate - Windows Command Prompt or PowerShell:
.venvScriptsactivate
Windows shell configuration can affect how an activation script is invoked. For shell-specific variants and details, consult the CPython venv documentation.
Check that the active python is the one inside your project environment:
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- Unix or macOS: run
which python. - Windows: run
where python.
The resolved path should be inside the project’s .venv directory. This catches a common mismatch: installing a package with one Python’s pip, then running the project with another interpreter.
Install project packages with the intended interpreter
With the environment active, install a package using:
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python -m pip install package-name
Using python -m pip ties pip to the interpreter named by python, avoiding ambiguity about which standalone pip command your shell found. To install dependencies listed in a requirements file, run:
python -m pip install -r requirements.txt
The PyPA package-installation tutorial explains package installation and requirements files. A requirements file helps populate another environment, but a simple list should not be treated as a complete cross-platform lock: dependency resolution can vary with operating system and other conditions.
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Leave, return, and recreate the environment
Run deactivate to leave the environment in the current shell. Closing the shell also ends its activation. In a later shell session, activate the existing environment again; it does not need to be recreated every time.
Do not commit .venv to version control or rely on copying it as a portable project artifact. Exclude it from the repository and recreate it from the project’s declared dependencies. This makes the project easier to set up on another machine and avoids storing environment files that depend on a particular interpreter and system.
Activation is optional for running a program
Activation is a shell convenience, not what creates the environment’s package separation. A program can run in an environment without an activated shell if you invoke that environment’s Python directly, for example .venv/bin/python on Unix-like systems or .venvScriptspython.exe on Windows. The PyPA specification says software should detect whether it is running in a virtual environment using interpreter properties such as sys.prefix and sys.base_prefix, rather than assuming shell activation.
Choose between venv, virtualenv, and pipx
| Tool | Typical purpose | Availability and scope |
|---|---|---|
venv |
Create a project environment for dependencies. | Included in Python’s standard library from Python 3.3 onward; Python 3.4 and later include pip in environments created with venv, according to the PyPA installation tutorial. |
virtualenv |
Create environments when its additional features or compatibility are useful. | A separately installed environment-creation tool; it is not required for the standard-library workflow. |
pipx |
Install a standalone Python command-line application in an isolated environment and expose its command. | A separate tool for application installation, not the default replacement for a project’s dependency environment. |
For an ordinary project, start with venv. Consider virtualenv when a specific feature or compatibility need justifies it. Use pipx when the goal is to install and run an individual command-line application rather than manage a project’s dependencies. The PyPA tool recommendations describe these distinct roles and list tools rather than prescribing one tool for every user.
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Some operating-system or distributor Python installations are marked externally managed. Under the PyPA externally managed environments specification, Python-specific installers should not alter packages in that global installation unless specifically overridden. The suggested path for project packages is to create an environment, for example with python3 -m venv .venv, and install packages there. This keeps project changes separate from packages managed by the operating system or distributor.
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