python virtual environment vs pipenv

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When working on Python projects, managing dependencies and isolating project environments is crucial to avoid conflicts and ensure reproducibility. Two popular tools for creating isolated environments are Python's built-in venv (virtual environment) and pipenv. In this tutorial, we'll explore the differences between them and guide you through using both with practical code examples.
Open your terminal and navigate to your project directory. Run the following commands:
This creates a folder named 'venv' in your project directory containing a standalone Python interpreter and a 'lib' folder.
On Windows:
On Unix or MacOS:
Once activated, your terminal prompt should change, indicating that you are now working within the virtual environment.
Install packages using pip as usual:
To deactivate the virtual environment:
Ensure you have Pipenv installed:
Navigate to your project directory and run:
This creates a 'Pipfile' and 'Pipfile.lock' in your project directory.
Run:
Your terminal prompt should change, indicating that you are now within the Pipenv shell.
Install packages using the pipenv install command:
To exit the Pipenv shell:
venv: Uses requirements.txt to manage dependencies.
Pipenv: Manages dependencies through the 'Pipfile' and 'Pipfile.lock'.
venv: Activated using the activate script.
Pipenv: Activated using the pipenv shell command.
venv: Creates a 'lib' folder and 'pyvenv.cfg' file.
Pipenv: Creates 'Pipfile' and 'Pipfile.lock'.
Both venv and pipenv are powerful tools for managing Python project environments. The choice between them often depends on personal preference and project requirements. Experiment with both to determine which best fits your workflow.
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