python projects: app and common. two profiles, dev and prod. it uses the shared library common. during dev, is it a good practice to import the library from common without having it installed in a .venv? is it possible?

When developing Python applications that utilize a shared library — in your case, a library named common — and involve different environments like development (dev) and production (prod), it's pertinent to understand the best practices regarding the importation of libraries, especially when it comes to managing virtual environments.

Understanding Python Virtual Environments

What is a Virtual Environment?

A virtual environment in Python is a self-contained directory that contains a specific Python version and its installed packages. It allows developers to manage dependencies separately for each project, ensuring that libraries and their versions do not conflict between projects. This is a critical practice in Python development due to the potential for dependency version clashes, performance issues, and differences in library behavior across versions.

Importance of Using Virtual Environments

Using a virtual environment is considered a best practice in Python development for several reasons:

• Isolation: Each project remains separate, avoiding conflicts with other projects.
• Reproducibility: You can replicate the development environment easily, which is essential for collaborative projects.
• Security: It minimizes the risk of exposing your global Python packages to vulnerabilities that might be present in individual packages.

According to Python for Engineers, it is strongly emphasized that one should never install Python libraries globally. Each project should maintain its own virtual environment to ensure that all dependencies remain intact and manageable.

Importing Libraries in Development

Importing Without Installation in a .venv

When developing in Python, you might be tempted to import a library (like common) without it being installed in the virtual environment. Technically, this is possible if the library is accessible through your Python path, but it is not recommended for several reasons:

1. Code Stability: If you're importing a library not installed in your virtual environment, you run the risk of encountering import errors during runs, especially if the library is modified or removed. This could lead to an unstable development experience.

2. Production Readiness: Relying on a shared library that is not formally installed can lead to inconsistencies between development and production environments. In production, the library must be installed to ensure proper functionality. If it is missing or has a different version, this may cause your application to fail.

3. Best Practices: Best practices recommend keeping dependencies clearly defined and installed in your environment. This not only helps with current development but also aids in onboarding new team members and maintaining the project's longevity. Many resources advocate always using virtual environments for dependency management, including guides from Stack Overflow and Real Python.

Recommendations

Best Practices for Importing Libraries

1. Install Dependencies: Always install shared libraries in your virtual environment, either through a requirements.txt file or directly using pip. This ensures all developers are working with the same library versions.

2. Use Editable Installs: If you are actively developing the common library, consider using an editable install with the -e option:

   pip install -e /path/to/common
   

   This allows you to import the library while still having access to your local changes.

3. Document Dependencies: Maintain clear documentation on dependencies and their respective versions to ensure consistency across different development and production environments.

Conclusion

In summary, while it is technically possible to import a shared library like common without installing it in your virtual environment, it is not advisable. Doing so can lead to unstable development conditions, potential errors, and inconsistencies between development and production setups. It's best to adhere to best practices by installing all necessary libraries within your virtual environment, ensuring a more robust and reliable development process.

For more detailed guidance on managing Python projects and dependencies, refer to Stuart Ellis and Packaging Python Projects.