The article discusses a data scientist’s transition from Python to Rust, comparing their virtual environment and dependency management aspects. In Python, virtual environments isolate project-specific packages and manage dependencies at runtime, requiring additional tools for capturing complete environment complexity. On the other hand, Rust’s Cargo builds with a single global location, featuring built-in dependency resolution and emphasizing compatibility. This showcases the differences and highlights the strengths of both languages in managing environments and dependencies.
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Python pro to Rust rookie — a data scientist’s transition tale
Embarking on the journey from Python to Rust can feel like swapping a trusty lightsaber for a new kind of blade — exciting but a bit daunting. As a data scientist deeply familiar with Python’s quirks, diving into the Rust world is a thrilling new challenge. In this article, I’ll share my experiences and insights, comparing how these two powerful languages handle a key aspect of software development — particularly focusing on (virtual) environments and dependency management.
1. Single global location for packages
Virtual environments in Python are created with tools like venv, virtualenv, or conda on a per-project basis. Under the hood, these systems create a separate folder which holds the Python distribution and all its packages. Now, when we install a package with pip or conda, the package and all its dependencies are installed in this isolated folder. These virtual environment tools do something that is similar to “chroot”, but for the Python installation.
Rust, on the other hand, has a package manager called cargo which uses a single global location, i.e. no user-specific virtual environments. It can do this because of the cargo build system. When you create a project using cargo it centers around the Cargo.toml file. This is the so-called project file that defines details of the project, including its dependencies with semantic versioning. Using cargo add
2. Built-in dependency resolution
Looking at Python, there is no built-in dependency resolution system. Yes, using pip freeze you can get an overview of the installed packages however, there is no guarantee that it also captures all indirect dependencies. This means that it cannot capture the complete complexity of the environment.
Rust’s Cargo, on the other hand, has built-in dependency resolution through the use of a lock file. When you use cargo build or cargo run, it checks the Cargo.lock file to ensure that the exact versions of all dependencies are used. This lock file captures the entire dependency tree, including transitive dependencies, making it a comprehensive and deterministic representation of the project’s environment.
3. Compatibility of packages and Rust itself
In software engineering, compatibility is a cornerstone that ensures a project functions smoothly across various environments. When we compare Rust’s cargo with Python’s pip, we can clearly see that in Rust this has been carefully thought through while in Python it has grown to what it is now.
Compatibility in Rust is not just a consideration; it’s a cultural commitment. The community places a strong emphasis on maintaining a application programming interface (API) compatibility for major versions. This is clearly reflected with the cargo package manager, which enforces semantic versioning. This results in a reliable and predictable development environment where dependencies are expected to play nicely with each other.
Wrap up
Learning and working with Rust really highlighted the big differences in how each language handles environment and dependency management. Python’s long history has led to the evolution of various tools like venv and Poetry, each addressing the language’s dynamic nature and runtime dependency resolution challenges. Despite their effectiveness, these solutions often feel more like necessary workarounds rather than integrated components of the language.
In contrast, Rust’s streamlined approach with Cargo demonstrates its commitment to a more integrated and user-friendly experience. Cargo’s efficient dependency management, free from the need for external tools or ‘PATH’ manipulations, showcases Rust’s modern approach to software development.
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