pronunciation. It is not named after the city in Uganda. 10.2 How fast is it? We really hate benchmarks especially since they don’t reflect much. The performance of a template depends on many factors factors and you would have to benchmark different engines in different situations. The benchmarks from the testsuite show that Jinja2 has a similar performance to Mako and is between 10 and 20 times faster than than Django’s template engine or Genshi. These numbers should be taken with tons of salt as the benchmarks that took these numbers only test a few performance related situations such as looping. Generally

ionice(psutil.IOPRIO_CLASS_RT, value=7) ● hot cache ● set highest CPU and disk I/O priority Benchmarks shutil.copyfile(): Python 3.7 vs. 3.8 Size Linux Windows macOS 128K +3% +27% +8% 8M +15% +45%

specs have no candidates at all after running through get_reduced_index. This has been faster in benchmarks, but we welcome further data from your use cases about whether this was a good change. (#8741) compatibility shims (#7606) • user-agent context refactor (#7630) • solver performance improvements with benchmarks in common.logic (#7676) • enable fuzzy-not-equal version constraint for pip interop (#7711) •

specs have no candidates at all after running through get_reduced_index. This has been faster in benchmarks, but we welcome further data from your use cases about whether this was a good change. (#8741) compatibility shims (#7606) • user-agent context refactor (#7630) • solver performance improvements with benchmarks in common.logic (#7676) • enable fuzzy-not-equal version constraint for pip interop (#7711) •

compatibility shims (#7606) • user-agent context refactor (#7630) • solver performance improvements with benchmarks in common.logic (#7676) • enable fuzzy-not-equal version constraint for pip interop (#7711) •

compatibility shims (#7606) • user-agent context refactor (#7630) • solver performance improvements with benchmarks in common.logic (#7676) • enable fuzzy-not-equal version constraint for pip interop (#7711) •

performance improvement should provide benchmarks showing the before and after impact of the patch and sharing the commands for reviewers to reproduce. django-asv benchmarks django-asv monitors the performance performance of Django code over time. These benchmarks can be run on a pull request by labeling the pull request with benchmark. Adding to these benchmarks is highly encouraged. Contribution checklist Use optimizations, should provide benchmarks and commands for the ticket triager to reproduce. See the django-asv benchmarks for more details of Django’s existing benchmarks. How we make decisions Whenever

performance improvement should provide benchmarks showing the before and after impact of the patch and sharing the commands for reviewers to reproduce. django-asv benchmarks django-asv [https://github.com/django/django-asv/] performance of Django code over time. These benchmarks can be run on a pull request by labeling the pull request with benchmark. Adding to these benchmarks is highly encouraged. Contribution checklist optimizations, should provide benchmarks and commands for the ticket triager to reproduce. See the django-asv benchmarks for more details of Django’s existing benchmarks. How we make decisions Whenever

performance improvement should provide benchmarks showing the before and after impact of the patch and sharing the commands for reviewers to reproduce. django-asv benchmarks django-asv monitors the performance performance of Django code over time. These benchmarks can be run on a pull request by labeling the pull request with benchmark. Adding to these benchmarks is highly encouraged. Contribution checklist Use optimizations, should provide benchmarks and commands for the ticket triager to reproduce. See the django-asv benchmarks for more details of Django’s existing benchmarks. How we make decisions Whenever

performance improvement should provide benchmarks showing the before and after impact of the patch and sharing the commands for reviewers to reproduce. django-asv benchmarks django-asv [https://github.com/django/django-asv/] performance of Django code over time. These benchmarks can be run on a pull request by labeling the pull request with benchmark. Adding to these benchmarks is highly encouraged. Contribution checklist optimizations, should provide benchmarks and commands for the ticket triager to reproduce. See the django-asv benchmarks for more details of Django’s existing benchmarks. How we make decisions Whenever