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Reproducibility in Disguise

Reproducibility has become a big deal. Whether it’s having higher confidence in one’s build or trying to better understand your supply chain for provenance, having an accurate view of your build graph is a must. Tools such as Bazel have picked up mainstream usage from their advocacy by large companies that use it or via similar derivatives such as Buck. These companies write & proclaim how internally it’s solved many of their software development lifecycle problems. They’ve graciously open-sourced these tools for us to use so that we may also reap similar benefits. Sounds great right?

Tools such as Bazel have picked up mainstream usage from their advocacy by large companies that use it or via similar derivatives such as Buck. To illustrate this, let’s walk through an example within the Python ecosystem how one can easily run-amuck with semantic versioning, diamond dependencies and shared libraries. For most of us at the hobbyist level this may not be a problem as thankfully C library developers for popular packages have taken the onerous burden to making them forward and backwards compatible through the use of symbol versioning.

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