This post explores the challenges of generating deterministic random numbers and using cosine within Nix expressions. It highlights that Nix's purity, while beneficial for reproducibility, makes tasks like generating unique identifiers difficult without resorting to external dependencies or impure functions. The author demonstrates various approaches, including using the derivation name as a seed for a pseudo-random number generator (PRNG) and leveraging builtins.currentTime as a less deterministic but readily available alternative. The post also delves into the lack of a built-in cosine function in Nix and presents workarounds, like writing a custom implementation or relying on a pre-built library, showcasing the trade-offs between self-sufficiency and convenience.
This blog post explores the intricacies of generating random numbers and calculating the cosine of an angle within the Nix functional package manager, a tool used for building and deploying software. The author begins by highlighting the deterministic nature of Nix, emphasizing that even seemingly random operations must be reproducible given the same inputs. This presents a challenge for incorporating randomness, which by definition is non-deterministic. The post then details how Nix addresses this by using a derivations feature for introducing controlled randomness. Derivations are pure functions that produce build instructions, and they can include a special randomSeed attribute. This seed acts as the starting point for a pseudorandom number generator (PRNG), ensuring consistent results for a given derivation. The author demonstrates this with a practical example, showcasing how to generate a random floating-point number between 0 and 1 within a derivation. This is achieved using the lib.randomFloat function from Nixpkgs, which internally utilizes the Xoshiro256** PRNG. The author further elaborates on how one might seed the derivation with a specific value to reproduce the same "random" result across different builds or machines, illustrating the predictable nature of pseudorandomness.
Moving beyond simple random number generation, the post then tackles the seemingly unrelated topic of calculating the cosine of an angle. The author explains that Nix, prioritizing purity and reproducibility, does not directly offer a cos function in its standard library. Instead, the approach involves leveraging the stdenv.mkDerivation function to build a small C++ program that calculates the cosine. This C++ program utilizes the standard cmath library for the cosine calculation and outputs the result. The Nix derivation packages this process, ensuring that the compilation and execution steps are captured and reproducible. The post provides a detailed example of how to construct this derivation, including the necessary C++ code and Nix expressions. This illustrates how Nix can incorporate external tools and libraries for computations that aren't directly available within its core functionality, while still maintaining its core principles of determinism and reproducibility. The author emphasizes the advantages of this approach: by encapsulating the cosine calculation within a derivation, Nix ensures that the result is always consistent for a given input angle, regardless of the build environment. The post concludes by showcasing how to combine these two concepts – random number generation and cosine calculation – to generate a random point on the unit circle, demonstrating the power and flexibility of Nix derivations for managing complex computations within a reproducible framework.
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https://news.ycombinator.com/item?id=43669057
Hacker News users discussed the blog post about reproducible random number generation in Nix. Several commenters appreciated the clear explanation of the problem and the proposed solution using a cosine function to distribute builds across build machines. Some questioned the practicality and efficiency of the cosine approach, suggesting alternatives like hashing or simpler modulo operations, especially given potential performance implications and the inherent limitations of pseudo-random number generators. Others pointed out the complexities of truly distributed builds in Nix and the need to consider factors like caching and rebuild triggers. A few commenters expressed interest in exploring the cosine method further, acknowledging its novelty and potential benefits in certain scenarios. The discussion also touched upon the broader challenges of achieving determinism in build systems and the trade-offs involved.
The Hacker News post titled "RNG and Cosine in Nix" sparked a discussion with several interesting comments.
One commenter questioned the practicality of the approach, pointing out that using a hash function directly would likely be simpler and more efficient than the proposed cosine-based method. They also expressed concern about potential bias introduced by using cosine and suggested that a more rigorous statistical analysis would be necessary to validate the randomness quality.
Another commenter echoed this sentiment, emphasizing the importance of proper statistical testing for random number generation. They recommended using established test suites like TestU01 to thoroughly evaluate the randomness properties of the generated sequence.
One user focused on the security implications, warning that the proposed method might not be suitable for cryptographic purposes due to potential predictability. They advised against using custom RNG solutions in security-sensitive contexts and recommended relying on well-vetted cryptographic libraries instead.
A further commenter offered a different perspective, suggesting that the approach might be useful for generating deterministic random values based on a seed. They envisioned applications in procedural generation, where consistent results are desirable.
Another individual highlighted the importance of understanding the underlying distribution of the generated random numbers. They noted that different applications may require different distributions (uniform, normal, etc.) and that simply generating seemingly random numbers without considering the distribution could lead to incorrect results.
Several commenters discussed the mathematical properties of the cosine function and its suitability for RNG. Some expressed skepticism, while others defended its potential, albeit with the caveat that careful analysis and testing are crucial.
Finally, some comments touched on the specific use case within Nix, the package manager mentioned in the title. They speculated about the potential benefits and drawbacks of using this method for generating unique identifiers or other random values within the Nix ecosystem. However, no definitive conclusions were drawn regarding its practical application in Nix.