In February 2025, a detailed exploration unveils Python’s vast ecosystem through PyPi’s half-million open source projects. To visualize this complex network, an API and BigQuery data were utilized to extract metadata on dependencies between packages. After filtering irrelevant entries and focusing on significant connections, the resulting dataset contained around 100K valid records.
To illustrate these relationships visually, Gephi software was employed with Force Atlas 2 algorithm proving effective in graph layouts. The interactive map revealed a somewhat unexpected structure: while some tightly connected clusters existed centered around popular packages like numpy, other areas contained suspicious dependencies or copied templates from malicious origins.
Organizations such as Triton and Odoo stood out due to their extensive number of Python projects released under their umbrella. Additionally, recognizable semantic neighborhoods emerged when examining energy-based layouts – regions like cryptography remained less familiar but equally intriguing for further exploration within this vast dataset.
Future enhancements could involve improving visualization techniques for recursive dependencies and adding search functionality to better navigate the immense repository of Python packages available on PyPi. The accompanying GitHub repository offers resources for anyone interested in replicating these findings themselves.\
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