Creating Python Environments

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Wing Pro can create a number of different kinds of Python environments along with your project: virtualenvs, Poetry envs, pipenvs, Anaconda envs, or Docker containers. These are selected from the drop down menu next to Create New Environment on the second page of the New Project dialog. Wing presents different configuration options for each type of environment, as detailed below.

Creating a Virtualenv

You will be prompted for the name and parent directory of the new virtualenv. The name defaults to the name of the new or existing source directory chosen earlier in the New Project dialog, and the parent directory defaults to a central location inside Wing's Settings Directory or the most recently used directory.

You can use Packages to Install to select any packages you want to install while creating the new environment. This may be done by entering the package specifications or selecting an existing requirements.txt, Pipfile, or Anaconda environment.yml.

Important! Please note that careless package selection may install malware on your computer. Be sure to read and understand Package Security before installing any packages!

The Python Executable is used to select the base Python installation to use with the new virtualenv. This determines the Python version that will be used.

Selecting Upgrade pip causes Wing to upgrade pip, the Python package manager, after setting up the virtualenv. This is recommended since virtualenv usually installs an outdated version of pip.

Checking Inherit global site-packages can be used to allow the virtualenv access to packages that have been installed into the selected base Python installation. This is not recommended because it may defeat the primary purpose of virtualenvs, to provide a uniform replicable environment.

When a new virtualenv environment is created, Wing writes a requirements.txt file for package management into the selected source directory. In Wing Pro, subsequent package installation, removal, upgrade, and inspection is possible through the Packages tool, which will maintain the requirements.txt file on request.

Creating Poetry and pipenv Environments

Poetry and pipenv are tools that automate and simplifie maintenance of a virtualenv and package management in that environment, with focus on the ease of replication of identical package environments for developers working on the same source base. Theyt can be used to create and manage a new virtualenv for either an existing or newly created source directory. Since Poetry and pipenv manage the virtualenv automatically in a hidden area outside of the source directory, there is no option to select the location for the new virtualenv.

Any Packages to Install and Python Executable`` may be entered as described for virtualenv above.

When Poetry creates a new environment, it will write pyproject.toml if not already present and also the poetry.lock file into the selected source directory. These files are used by Poetry to manage package installation, dependencies, and upgrades.

Similarly, pipenv creates Pipfile` and Pipfile.lock in the selected source directory.

Creating an Anaconda Environment

Anaconda is a Python distribution that provides its own package manager.

Somewhat like Poetry and pipenv, the conda package manager can store its environments in a hidden centrally managed location, allowing reference to them by name. To store the environment elsewhere, set the Parent Directory to Selected Directory and enter the full path of the parent directory for the new environment.

Anaconda Installation is used to select the Anaconda base installation to use in creating the new environment.

Packages to Install selects any packages to install in the new environment, as described for virtualenv above.

Creating a Docker Environment

There are two options for creating a new Docker environment along with your new project: (1) You may use an existing already-created Docker container as your Python environment, or (2) you may create a new Docker container along with your project and configure Wing to use it. The former only creates a container configuration that allows Wing to access the Docker container, while the latter also creates a new Docker container.

These options are described in detail in Using Wing Pro with Docker.