Env activate python windows

How to activate virtual environment from Windows 10 command prompt

Use the activate script in the Scripts directory of your virtual environment:

This will activate your virtual environment and your terminal will look like this depending on the directory you’re in:

Using bash I think what you can do is . venv/Scripts/activate Do note that there is a space after the dot.

If you’re using virtualenvwrapper-win , and using the DOS command prompt (as opposed to e.g. Powershell), then new virtualenvs are created using:

You should define the environment variable WORKON_HOME to point to where you want you virtualenvs to reside.

If you’ve installed virtualenvwrapper-win>=1.2.4 then the virtualenvwrapper command will give you a list available commands:

go|c:\srv> virtualenvwrapper virtualenvwrapper is a set of extensions to Ian Bicking's virtualenv tool. The extensions include wrappers for creating and deleting virtual environments and otherwise managing your development workflow, making it easier to work on more than one project at a time without introducing conflicts in their dependencies. virtualenvwrapper-win is a port of Dough Hellman's virtualenvwrapper to Windows batch scripts. Commands available: add2virtualenv: add directory to the import path cdproject: change directory to the active project cdsitepackages: change to the site-packages directory cdvirtualenv: change to the $VIRTUAL_ENV directory lssitepackages: list contents of the site-packages directory lsvirtualenv: list virtualenvs mkproject: create a new project directory and its associated virtualenv mkvirtualenv: Create a new virtualenv in $WORKON_HOME rmvirtualenv: Remove a virtualenv setprojectdir: associate a project directory with a virtualenv toggleglobalsitepackages: turn access to global site-packages on/off virtualenvwrapper: show this help message whereis: return full path to executable on path. workon: list or change working virtualenvs 

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12. Virtual Environments and Packages¶

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 available. If you have multiple versions of Python on your system, you can select a specific Python version by running python3 or whichever version you want.

To create a virtual environment, decide upon a directory where you want to place it, and run the venv module as a script with the directory path:

python -m venv tutorial-env 

This will create the tutorial-env directory if it doesn’t exist, and also create directories inside it containing a copy of the Python interpreter and various supporting files.

A common directory location for a virtual environment is .venv . This name keeps the directory typically hidden in your shell and thus out of the way while giving it a name that explains why the directory exists. It also prevents clashing with .env environment variable definition files that some tooling supports.

Once you’ve created a virtual environment, you may activate it.

tutorial-env\Scripts\activate.bat 

source tutorial-env/bin/activate 

(This script is written for the bash shell. If you use the csh or fish shells, there are alternate activate.csh and activate.fish scripts you should use instead.)

Activating the virtual environment will change your shell’s prompt to show what virtual environment you’re using, and modify the environment so that running python will get you that particular version and installation of Python. For example:

$ source ~/envs/tutorial-env/bin/activate (tutorial-env) $ python Python 3.5.1 (default, May 6 2016, 10:59:36) . >>> import sys >>> sys.path ['', '/usr/local/lib/python35.zip', . '~/envs/tutorial-env/lib/python3.5/site-packages'] >>>

To deactivate a virtual environment, type:

12.3. Managing Packages with pip¶

You can install, upgrade, and remove packages using a program called pip. By default pip will install packages from the Python Package Index. You can browse the Python Package Index by going to it in your web browser.

pip has a number of subcommands: “install”, “uninstall”, “freeze”, etc. (Consult the Installing Python Modules guide for complete documentation for pip .)

You can install the latest version of a package by specifying a package’s name:

(tutorial-env) $ python -m pip install novas Collecting novas Downloading novas-3.1.1.3.tar.gz (136kB) Installing collected packages: novas Running setup.py install for novas Successfully installed novas-3.1.1.3

You can also install a specific version of a package by giving the package name followed by == and the version number:

(tutorial-env) $ python -m pip install requests==2.6.0 Collecting requests==2.6.0 Using cached requests-2.6.0-py2.py3-none-any.whl Installing collected packages: requests Successfully installed requests-2.6.0

If you re-run this command, pip will notice that the requested version is already installed and do nothing. You can supply a different version number to get that version, or you can run python -m pip install —upgrade to upgrade the package to the latest version:

(tutorial-env) $ python -m pip install --upgrade requests Collecting requests Installing collected packages: requests Found existing installation: requests 2.6.0 Uninstalling requests-2.6.0: Successfully uninstalled requests-2.6.0 Successfully installed requests-2.7.0

python -m pip uninstall followed by one or more package names will remove the packages from the virtual environment.

python -m pip show will display information about a particular package:

(tutorial-env) $ python -m pip show requests --- Metadata-Version: 2.0 Name: requests Version: 2.7.0 Summary: Python HTTP for Humans. Home-page: http://python-requests.org Author: Kenneth Reitz Author-email: me@kennethreitz.com License: Apache 2.0 Location: /Users/akuchling/envs/tutorial-env/lib/python3.4/site-packages Requires:

python -m pip list will display all of the packages installed in the virtual environment:

(tutorial-env) $ python -m pip list novas (3.1.1.3) numpy (1.9.2) pip (7.0.3) requests (2.7.0) setuptools (16.0) 

python -m pip freeze will produce a similar list of the installed packages, but the output uses the format that python -m pip install expects. A common convention is to put this list in a requirements.txt file:

(tutorial-env) $ python -m pip freeze > requirements.txt (tutorial-env) $ cat requirements.txt novas==3.1.1.3 numpy==1.9.2 requests==2.7.0

The requirements.txt can then be committed to version control and shipped as part of an application. Users can then install all the necessary packages with install -r :

(tutorial-env) $ python -m pip install -r requirements.txt Collecting novas==3.1.1.3 (from -r requirements.txt (line 1)) . Collecting numpy==1.9.2 (from -r requirements.txt (line 2)) . Collecting requests==2.7.0 (from -r requirements.txt (line 3)) . Installing collected packages: novas, numpy, requests Running setup.py install for novas Successfully installed novas-3.1.1.3 numpy-1.9.2 requests-2.7.0

pip has many more options. Consult the Installing Python Modules guide for complete documentation for pip . When you’ve written a package and want to make it available on the Python Package Index, consult the Distributing Python Modules guide.

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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.

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.

Debian and most other distributions include a python-pip package; if you want to use the Linux distribution-provided versions of pip, see Installing pip/setuptools/wheel with Linux Package Managers .

You can also install pip yourself to ensure you have the latest version. It’s recommended to use the system pip to bootstrap a user installation of pip:

python3 -m pip install --user --upgrade pip python3 -m pip --version

Afterwards, you should have the latest version of pip installed in your user site:

pip 21.1.3 from $HOME/.local/lib/python3.9/site-packages (python 3.9)

The Python installers for Windows include pip. You can make sure that pip is up-to-date by running:

py -m pip install --upgrade pip py -m pip --version

Afterwards, you should have the latest version of pip:

pip 21.1.3 from c:\python39\lib\site-packages (Python 3.9.4)

Installing virtualenv¶

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.

python3 -m pip install --user virtualenv

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 you switch projects, you can simply create a new virtual environment and not have to worry about breaking the packages installed in the other environments. It is always recommended to use a virtual environment while developing Python applications.

To create a virtual environment, go to your project’s directory and run venv. If you are using Python 2, replace venv with virtualenv in the below commands.

The second argument is the location to create the virtual environment. Generally, you can just create this in your project and call it env .

venv will create a virtual Python installation in the env folder.

You should exclude your virtual environment directory from your version control system using .gitignore or similar.

Activating a virtual environment¶

Before you can start installing or using packages in your virtual environment you’ll need to activate it. Activating a virtual environment will put the virtual environment-specific python and pip executables into your shell’s PATH .

You can confirm you’re in the virtual environment by checking the location of your Python interpreter:

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