I would like to use the data to correlate with openSUSE package names, which use the 'real' name supplied in setup.py, i.e. not-normalised.
I've been doing a bit of research at https://github.com/hugovk/top-pypi-packages/issues/4, and the raw data from bigquery can include this, with a very small perf hit, or it can be added afterwards by doing lookups against PyPI directly, which would be a significant extra work.
I'm putting in the effort - I want to know where I should put the effort, here or somewhere else. If here, would you prefer it coming from bigquery, or added afterwards from PyPI. The latter makes sense if there are other details from PyPI that you believe are needed in this project which cant be obtained from the bigquery dataset.
I would like to use the data to correlate with openSUSE package names, which use the 'real' name supplied in setup.py, i.e. not-normalised.
I've been doing a bit of research at https://github.com/hugovk/top-pypi-packages/issues/4, and the raw data from bigquery can include this, with a very small perf hit, or it can be added afterwards by doing lookups against PyPI directly, which would be a significant extra work.
I'm putting in the effort - I want to know where I should put the effort, here or somewhere else. If here, would you prefer it coming from bigquery, or added afterwards from PyPI. The latter makes sense if there are other details from PyPI that you believe are needed in this project which cant be obtained from the bigquery dataset.