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Python Virtual Environments

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Creating a comprehensive summary covering Python virtual environments, including 30 paragraphs with all requested details, is a substantial task. However, I'll provide a concise summary that touches on the concept of virtual environments in Python, key tools, their documentation, code examples, main features, popular third-party libraries, and alternatives, focusing on widely used tools like `venv`, `virtualenv`, and others.

==Introduction to Python Virtual Environments Python virtual environments are a feature of the Python ecosystem that allows developers to create isolated environments for different projects. These environments have their own independent set of installed Python packages, which helps in managing dependencies, versions, and permissions.

==Why Use Virtual Environments? Using virtual environments in Python development ensures that projects are isolated from each other, preventing conflicts between package versions and making dependency management more straightforward.

==`venv`: The Standard Library Tool `venv` is a module available in Python 3.3 and later that provides support for creating lightweight “virtual environments” with their own site directories, optionally isolated from system site directories.

==Official Documentation for `venv`

Documentation for `venv` provides guidelines on creating virtual environments using the module: s://docs.python.org/3/library/venv.html(https://docs.python.org/3/library/venv.html).

==`virtualenv`: A Third-party Tool `virtualenv` is a widely used tool for creating virtual environments in Python, offering more flexibility and features than `venv`.

==`virtualenv` GitHub Repository

The source code and documentation for `virtualenv` can be found on GitHub: s://github.com/pypa/virtualenv(https://github.com/pypa/virtualenv).

==Official Website for `virtualenv`

More information and documentation can be found on the official `virtualenv` website: s://virtualenv.pypa.io/(https://virtualenv.pypa.io/).

==Wikipedia on Python Virtual Environments While Wikipedia does not have a page dedicated solely to Python virtual environments, information can be found within broader Python programming language or software development tool articles.

==Creating a Virtual Environment with `venv` ```bash python3 -m venv myenv ```

==Activating a Virtual Environment in Linux/MacOS ```bash source myenv/bin/activate ```

==Activating a Virtual Environment in Windows ```cmd myenv\Scripts\activate.bat ```

==Deactivating a Virtual Environment ```bash deactivate ```

==Creating a Virtual Environment with `virtualenv` ```bash virtualenv myenv ```

==Specifying a Python Interpreter with `virtualenv` ```bash virtualenv -p /usr/bin/python3 myenv ```

==Using `pip` to Install Packages in a Virtual Environment ```bash pip install requests ```

==Freezing Dependencies with `pip` ```bash pip freeze > requirements.txt ```

==Installing Dependencies from a `requirements.txt` File ```bash pip install -r requirements.txt ```

==Main Features of Python Virtual Environments 1. Isolation: Each virtual environment is isolated from others and the global Python installation. 2. Dependency Management: Manage project-specific dependencies without conflicts. 3. Development Consistency: Ensure that all developers working on a project use the same packages and versions. 4. Easy Activation/Deactivation: Simple commands to activate or deactivate environments. 5. Compatibility: Support for both Python 2 and 3, although `venv` is only available in Python 3.

==Popular Third-Party Libraries for Python Development 1. Django: A high-level Python web framework. 2. Flask: A micro web framework for Python. 3. NumPy: A library for numerical computing. 4. Pandas: A library for data manipulation and analysis. 5. Requests: A simple HTTP library.

Competition or Alternatives

While venv and virtualenv are popular, other tools offer virtual environment capabilities: 1. Conda: An open-source package management and environment management system. 2. Pipenv: Automatically creates and manages a virtual environment for projects. 3. Poetry: A tool for dependency management and packaging in Python. 4. pyenv: Allows switching between multiple versions of Python easily. 5. Docker: Provides containerization that can be used to create isolated environments.

==Conclusion Python virtual environments are essential tools for modern Python development, allowing developers to manage project dependencies effectively. Whether using the standard `venv` module, `virtualenv`, or exploring alternatives like `Conda` and `Pipenv`, virtual environments help maintain project consistency and prevent conflicts between different projects' dependencies.

Anaconda

Conda Environment (brew install conda, choco install anaconda) - Anaconda and MiniConda
- conda --help, conda --version

Anaconda: Conda Virtual Environment, Anaconda Installation (Anaconda on Windows, Anaconda on macOS, Anaconda on Rocky, Anaconda on Ubuntu), Anaconda, Inc., Anaconda Products (Anaconda Distribution, Anaconda Professional, Anaconda Business, Anaconda Server, Anaconda Enterprise DS Platform), Conda, Miniconda, Anaconda Navigator, Anaconda Community Portal (Anaconda Cloud / Anaconda Nucleus), Anaconda Packages, List of Anaconda Packages, Anaconda GitHub, Awesome Anaconda. (navbar_anaconda - see also navbar_python_virtual_environments)

Virtualenv

Virtualenv Environment - virtualenv
- virtualenv --help, virtualenv --version

navbar_virtualenv

Pipenv

Pipenv Environment (brew install pipenv) - pipenv
- pipenv --help, pipenv --version

Python Pipenv Environment: pipenv, pipenv Installation (brew install pipenv, choco install pipenv), Python Virtual Environments, pipenv -h, pipenv arguments: (

Usage: pipenv [OPTIONS] COMMAND [ARGS]…

Options:

 --where                         Output project home information.
 --venv                          Output virtualenv information.
 --py                            Output Python interpreter information.
 --envs                          Output Environment Variable options.
 --rm                            Remove the virtualenv.
 --bare                          Minimal output.
 --man                           Display manpage.
 --support                       Output diagnostic information for use in
                                 GitHub issues.
 --site-packages / --no-site-packages
                                 Enable site-packages for the virtualenv.
                                 [env var: PIPENV_SITE_PACKAGES]
 --python TEXT                   Specify which version of Python virtualenv
                                 should use.
 --three                         Use Python 3 when creating virtualenv.
                                 Deprecated
 --clear                         Clears caches (pipenv, pip).  [env var:
                                 PIPENV_CLEAR]
 -q, --quiet                     Quiet mode.
 -v, --verbose                   Verbose mode.
 --pypi-mirror TEXT              Specify a PyPI mirror.
 --version                       Show the version and exit.
 -h, --help                      Show this message and exit.

), pipenv examples:

Create a new project using Python 3.7, specifically:

$ pipenv --python 3.7

Remove project virtualenv (inferred from current directory): $ pipenv --rm

Install all Python dependencies for a project (including dev):

$ pipenv install --dev

  Create a lockfile containing pre-releases:
  $ pipenv lock --pre

  Show a graph of your installed dependencies:
  $ pipenv graph

  Check your installed dependencies for security vulnerabilities:
  $ pipenv check

  Install a local setup.py into your virtual environment/Pipfile:
  $ pipenv install -e .

  Use a lower-level pip command:
  $ pipenv run pip freeze

pipenv Commands: pipenv check, pipenv clean, pipenv graph (Python dependency graph), pipenv install (Python packages, Pipfile), pipenv lock (Pipfile.lock, pipenv open, (Python module, Python editor), pipenv requirements (requirements.txt, Pipfile.lock), pipenv run, pipenv scripts (Python scripts, Python environment config, pipenv shell (Python shell), pipenv sync, pipenv uninstall, pipenv update (pipenv lock + pipenv sync), pipenv verify (Pipfile.lock hash up-to-date), virtualenv; pipenv GitHub. (navbar_pipenv - see also navbar_python_virtual_environments, navbar_python)

navbar_pipenv

Pipx

Pipx Environment (brew install pipx) - pipx
- pipx --help, pipx --version

Python pipx Virtual Environments Install pipx (brew install pipx, Python Virtual Environments, pipx install, pipx inject, pipx upgrade, pipx upgrade-all, pipx uninstall, pipx uninstall-all, pipx reinstall, pipx reinstall-all, pipx list, pipx run, pipx runpip, pipx ensurepath, pipx environment, completion. (navbar_pipx - see also navbar_python_virtual_environments)

navbar_pipx

Poetry

Poetry Environment (brew install poetry) - Python Poetry, Poetry
- poetry --help, poetry --version

navbar_poetry

Windows

Python Virtual Environments on Windows

macOS

Python Virtual Environments on macOS

Linux

Python Virtual Environments on Linux

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Python Virtual Environments: Python Virtual Environment Glossary, Conda Environment (brew install conda, choco install anaconda), Virtualenv Environment, Pipenv Environment (brew install pipenv), Pipx Environment (brew install pipx), Poetry Environment (brew install poetry), Python Global Site Packages, Developer Virtual Environments, Python System Interpreter; Python Virtual Environments GitHub, Python Virtual Environments Topics. (navbar_python_virtual_environments - see also navbar_python, navbar_python_libaries, navbar_python_standard_library)

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