* Disable all tests of the NuSVC estimator that use memmap'd data
* build in serial on darwin
Resolves#121988
(cherry picked from commit cb2891b8c88705dfa5092cf992b7f64ae04da781)
The code coverage requirement of 100% was too stringent on Darwin.
Since there is no way that we can address a lack of code coverage
downstream we remove this check.
The darwin build was failing because neither of the ch4backend libraries
build on darwin.
Changes:
* delete unused argument device
* pass the derivation for the ch4backend in directly rather than using
a string to switch between two other arguments. (3 args to 1 arg)
* don't use ch4backend on Darwin
Resolves#121978
There were hydra failures (https://hydra.nixos.org/build/141870744/nixlog/1) for some tests requiring data on github (failing on mac and linux), and tests requiring local network access on mac.
Disable the former and enable the latter.
Importing dask.dataframe in a sandboxed build results in a TypeError like
this:
File "/nix/store/nv60iri29bia4szhhcvsdxgsci4wxvp6-python3.8-dask-2021.03.0/lib/python3.8/site-packages/dask/dataframe/io/csv.py", line 392, in <module>
AUTO_BLOCKSIZE = auto_blocksize(TOTAL_MEM, CPU_COUNT)
File "/nix/store/nv60iri29bia4szhhcvsdxgsci4wxvp6-python3.8-dask-2021.03.0/lib/python3.8/site-packages/dask/dataframe/io/csv.py", line 382, in auto_blocksize
blocksize = int(total_memory // cpu_count / memory_factor)
TypeError: unsupported operand type(s) for //: 'int' and 'NoneType'
This occurs because dask.dataframe has a non-deterministic component which
generates an automatic chunk-size based on system information.
This went unnoticed because the dask tests were disabled.
Changes:
- add a patch making the chunk-size inference more robust
- re-enable the tests
Resolves#120307
Noah D. Brenowitz