Software reproducibility is important for re-usability and the
cumulative progress of research. An important manifestation of
unreproducible software is the changed outcome of software builds over
time. While enhancing code reuse, the use of open-source dependency
packages hosted on centralized repositories such as PyPI can
have adverse effects on build reproducibility. Frequent updates to
these packages often cause their latest versions to have breaking
changes for applications using them. Large Python applications risk
their historical builds becoming unreproducible due to the widespread
usage of Python dependencies, and the lack of uniform practices for
dependency version specification. Manually fixing dependency errors
requires expensive developer time and effort, while automated
approaches face challenges of parsing unstructured build logs, finding
transitive dependencies, and exploring an exponential search space of
dependency versions. In this paper, we investigate how open-source
Python projects specify dependency versions, and how their
reproducibility is impacted by dependency packages. We propose a tool
PyDFix to detect and fix unreproducibility in Python builds caused by
dependency errors. PyDFix is evaluated on two bug datasets BugSwarm
and BugsInPy, both of which are built from real-world open-source
projects. PyDFix analyzes a total of 2,702 builds, identifying 1,921
(71.1%) of them to be unreproducible due to dependency errors. From
these, PyDFix provides a complete fix for 859 (44.7%) builds, and
partial fixes for an additional 632 (32.9%) builds.