Custom Query (121 matches)
Results (46 - 48 of 121)
| Ticket | Resolution | Summary | Owner | Reporter |
|---|---|---|---|---|
| #92 | worksforme | PyYAML installer for windows with libYAML binding | xi | anonymous |
| Description |
Can anyone create a windows installer for PyYAML with libYAML binding? the current PyYAML installer doesn't have libYAML binding and it is quite slow to load a big YAML file compare to PySyck. |
|||
| #163 | fixed | PyYAML is not installable with Jython | xi | olt@… |
| Description |
Installing PyYaml? with pip install under Jython doesn't work on a system that has a compiler. It checks for libyaml compatibility and then errors: "Compiling extensions is not supported on Jython" Solution: Don't add ext_module for platform.system() == Java. See patch. |
|||
| #12 | fixed | PyYAML is slow | xi | edemaine@… |
| Description |
Here are two simple wall-clock timings comparing PyYAML to PySyck on a Pentium 4 2.8GHz with 1MB cache and 1GB RAM: $ wc file1.yaml 2036 8767 59154 file1 $ test.py file1.yaml 0:00:00.001419 to read the YAML via Syck 0:00:04.029627 to read the YAML via PyYAML $ wc file2.yaml 8949 35105 317342 file2 $ test.py file2.yaml 0:00:00.001564 to read the YAML via Syck 0:00:19.288912 to read the YAML via PyYAML I do not expect PyYAML to be terribly competitive with Syck: the language barrier is big, and PyYAML is written with a higher level of abstraction. But I was surprised to see a factor of 12,000 difference. I wonder if a bit of profiling and tuning might reduce this gap to just a couple of orders of magnitude (100x) instead of four? Personally, 19 seconds to read a 0.3 meg file is too slow for my application, so I'll have to switch back to Syck for now, unfortunately. Just food for thought... |
|||
