I’ve just spent the last couple of days trying to get an OpenAI python project to work on a corporate network as well as my personal laptop.
While I was able to get the project working fairly quickly on my personal laptop where I’m a local admin with a custom Python installation. However, getting the code to working on a corporate network with a lot of security was a totally different experience of which I’m still sorting out.
One topic that I really needed to understand was the how the Python packages are distributed. I had no issues with some packages but lots of problems with others.
In some cases, I had to install Visual Studio for C++ to get some to complie and in another a RUST install was required. The learning curve is steep around configuring your Python environment for developing OpenAI solutions.
Python, packages can be distributed in several formats, with the two most common being source distributions and wheel distributions. The distinction between these formats largely comes down to the needs for compilation and ease of installation.
Source Distributions
- What They Are: Source distributions contain the raw source code files of a Python package, including Python scripts and sometimes C or C++ files that require compilation.
- Compilation Requirement: If a package includes components written in C or C++ (common for performance-intensive tasks), these components must be compiled into executable binaries or shared libraries that the Python interpreter can use. This compilation happens on the end user’s machine when they install the package. The user must have the appropriate compiler and any necessary libraries on their system for the compilation to succeed.
- Why Used: Source distributions are universal in that they can be used on any platform, provided the necessary compilation tools are available. They are also necessary when a package contains platform-specific or performance-critical code that benefits from being compiled with the local machine’s specific architecture optimizations.
Wheel Distributions
- What They Are: Wheel files (
.whl) are a built-package format for Python, designed to replace the earlier egg format. They are a packaging standard for Python that allows for faster installations and handles the binary aspect of packages. - No Compilation Required: Wheels are pre-compiled, which means the binary files necessary for the package to run are already created and bundled in the wheel. When you install a wheel, you don’t need to compile anything; the package is simply unpacked to your system, which significantly speeds up the installation process.
- Why Used: Wheels are beneficial because they simplify the installation process and ensure that a user does not need to have a compiler on their system to install a package. This is particularly useful for packages that include platform-specific binary code. Wheels are specific to a platform and Python version, which means a different wheel would be needed for each combination of operating system, Python version, and machine architecture.
Practical Considerations
- Availability: Not all packages are available as wheels. If a package is only available as a source distribution, users need to have the necessary compilers (like GCC for C code). For Python packages that depend on many external libraries and tools (e.g., those used for scientific computing or data analysis), this can sometimes complicate installation.
- Compatibility and Ease: Using wheels can avoid potential incompatibilities and issues arising from the compilation process (e.g., missing or mismatched dependencies). It’s generally easier for end users, especially those who may not be familiar with compiling software from source.
In summary, wheels are generally preferable for ease of use and speed, especially when distributing binary or platform-specific code. Source distributions are necessary when you want to ensure that your package can be installed across all platforms and Python versions, provided the user has the right tools to compile it.
