#!/usr/bin/env python
# coding: utf-8

# In[1]:


import numpy as np
import xarray as xr
ds = xr.tutorial.open_dataset('rasm')


# Set to classic repr by default for now so that we can merge and keep ironing out oddities:

# In[2]:


ds


# ## New repr

# In[3]:


xr.set_options(display_style="html");


# Before the data are loaded, the preview won't show up. After the data are loaded below, the preview will be populated.

# In[4]:


ds.load()


# In[5]:


ds.Tair


# ## Check sizes

# In[6]:


c = ds.__repr__()
h = ds._repr_html_()


# In[7]:


import sys
print(f'classic: {round(sys.getsizeof(c)/1000)}kb\nhtml: {round(sys.getsizeof(h)/1000)}kb')


# ## Long var names

# In[8]:


xr.Dataset({
    'fdhskafhdjsafdsafhldsa;fjkld;sajkfdsla;fdjksa': ds.Tair,
    'wuildjklsahjdklsahfjkdshafjkldsahjfkdslafhdsja': ds.Tair})


# ## `MultiIndex`

# In[9]:


array = xr.DataArray(np.random.randn(2, 3),
                     coords=[('x', ['a', 'b']), ('y', [0, 1, 2])])
stacked = array.stack(z=('x', 'y'))
stacked


# ## Dask

# In[10]:


ds = xr.tutorial.open_dataset('air_temperature',
                              chunks={'lat': 25, 'lon': 25, 'time': -1})
ds


# We can use panel to see what the dataset looks like at smaller widths

# In[11]:


import panel as pn; pn.extension()
xr.set_options(display_style="html");


# In[12]:


dataset = pn.pane.HTML(ds, width=400, background="#ddffff")
width = pn.widgets.IntSlider( value=dataset.width, start=300, end=700, width=150, name='width')
width.jslink(dataset, value='width')

pn.Row(width, dataset)


# In[ ]: