Dark theme-friendly HTML Dataset and DataArray reprs for jupyter notebooks? #4161
Description
Xarray's HTML Dataset and DataArray reprs are evidently not compatible with "dark" jupyter notebook themes. They seem to work fine with the dark jupyter lab theme, and since jupyter lab is the way of the future perhaps this issue is obsolete, but thought I'd mention it.
The below example is from a jupyter notebook with the "onedork" dark theme from jupyter-themes. It results in black text against a dark background for the section headers (Coordinates, Dimensions, etc.) and DataArray data tables, and a light background for the coordinate and Dataset data tables.
# Dataset repr
import numpy as np
import xarray as xr
ds = xr.Dataset(
{
'temp': (('x', 'y'), np.random.rand(10, 20), {'long_name': 'temperature', 'units': 'degrees_Celsius'}),
'x': ('x', np.arange(10)),
'y': ('y', np.arange(20)),
},
attrs={'description': 'example dataset'}
)
ds
# DataArray repr
ds.temp
Note that, by contrast, the text repr is dark theme friendly:
# Text repr
xr.set_options(display_style='text')
ds
Versions
Jupyter versions
jupyter core : 4.6.3jupyter-notebook : 6.0.3
qtconsole : 4.7.4
ipython : 7.15.0
ipykernel : 5.3.0
jupyter client : 6.1.3
jupyter lab : not installed
nbconvert : 5.6.1
ipywidgets : 7.5.1
nbformat : 5.0.6
traitlets : 4.3.3
Output of xr.show_versions()
INSTALLED VERSIONS
commit: None
python: 3.8.3 | packaged by conda-forge | (default, Jun 1 2020, 17:43:00)
[GCC 7.5.0]
python-bits: 64
OS: Linux
OS-release: 3.10.0-957.27.2.el7.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: en_US.UTF-8
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8
libhdf5: None
libnetcdf: None
xarray: 0.15.1
pandas: 1.0.4
numpy: 1.18.4
scipy: 1.4.1
netCDF4: None
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: None
cftime: None
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: None
dask: 2.17.2
distributed: 2.18.0
matplotlib: 3.2.1
cartopy: 0.18.0
seaborn: None
numbagg: None
setuptools: 47.1.1.post20200529
pip: 20.1.1
conda: 4.8.3
pytest: None
IPython: 7.15.0
sphinx: None