ENH: implement Graph.__repr__

[martinfleis]

I quite like when the __repr__ actually says something about the object, so here's a draft of Graph.__repr__. Happy to iterate over if you have ideas what and how should be shown. The info I picked now is very cheap to compute.

In [1]: import numpy as np
   ...: from libpysal import graph
   ...: import geopandas as gpd
   ...: from geodatasets import get_path

In [2]: coords = np.random.random((100_000, 2))

In [5]: delaunay = graph.Graph.build_triangulation(coords)

In [6]: %time r = delaunay.__repr__()
CPU times: user 27 ms, sys: 10.9 ms, total: 37.9 ms
Wall time: 36.9 ms

In [7]: delaunay
Out[7]: 
<Graph of 100000 nodes and 599936 nonzero edges indexed by
 [0, 1, 2, 3, 4, ...]>

In [8]: nybb = gpd.read_file(get_path('nybb')).set_index('BoroName')

In [9]: contig = graph.Graph.build_contiguity(nybb)
   ...: contig
Out[9]: 
<Graph of 5 nodes and 10 nonzero edges indexed by
 ['Staten Island', 'Queens', 'Brooklyn', 'Manhattan', 'Bronx']>

udpated to match the latest formatting

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 85.0%. Comparing base (bcabdbc) to head (07e3c66).
Report is 16 commits behind head on main.

Additional details and impacted files

@@           Coverage Diff           @@
##            main    #711     +/-   ##
=======================================
- Coverage   85.0%   85.0%   -0.0%     
=======================================
  Files        141     145      +4     
  Lines      15203   15381    +178     
=======================================
+ Hits       12924   13068    +144     
- Misses      2279    2313     +34     

Files	Coverage Δ
libpysal/graph/base.py	97.0% <100.0%> (-0.9%)	⬇️
libpysal/graph/tests/test_base.py	100.0% <100.0%> (ø)

... and 5 files with indirect coverage changes