CLN: move common printing utilties to pandas.io.formats.printing

[jreback]

No description provided.

[jreback]

these are really useful for ExtensionArrays to avoid re-inventing the wheel on repr. IIRC @TomAugspurger this was a sore point in creating IntervalArray.

[jreback]

e.g. get this (truncation, justification and line wrapping) on IntegerArray with no work

In [1]: pd.Series([1,2,np.nan]*20,dtype='Int8').values
Out[1]: 
IntegerArray([1, 2, nan, 1, 2, nan, 1, 2, nan, 1, 2, nan, 1, 2, nan, 1, 2, nan,
              1, 2, nan, 1, 2, nan, 1, 2, nan, 1, 2, nan, 1, 2, nan, 1, 2, nan,
              1, 2, nan, 1, 2, nan, 1, 2, nan, 1, 2, nan, 1, 2, nan, 1, 2, nan,
              1, 2, nan, 1, 2, nan],
             dtype='Int64')

In [2]: pd.Series([1,2,np.nan]*50,dtype='Int8').values
Out[2]: 
IntegerArray([1, 2, nan, 1, 2, nan, 1, 2, nan, 1,
              ...
              nan, 1, 2, nan, 1, 2, nan, 1, 2, nan],
             dtype='Int64', length=150)

with this code (can consider adding this as a function somewhere as well)

    def __repr__(self):
        """
        Return a string representation for this object.

        Invoked by unicode(df) in py2 only. Yields a Unicode String in both
        py2/py3.
        """
        klass = self.__class__.__name__
        data = format_object_summary(self, default_pprint, False, name=klass)
        attrs = format_object_attrs(self)
        space = " "

        prepr = (u(",%s") %
                 space).join(u("%s=%s") % (k, v) for k, v in attrs)

        res = u("%s(%s%s)") % (klass, data, prepr)

        return res

[codecov]

Codecov Report

Merging #21234 into master will decrease coverage by <.01%.
The diff coverage is 97.53%.

@@            Coverage Diff             @@
##           master   #21234      +/-   ##
==========================================
- Coverage   91.84%   91.84%   -0.01%     
==========================================
  Files         153      153              
  Lines       49506    49512       +6     
==========================================
+ Hits        45467    45472       +5     
- Misses       4039     4040       +1

Flag	Coverage Δ
#multiple	90.23% <97.53%> (-0.01%)	⬇️
#single	41.88% <79.01%> (ø)	⬆️

Impacted Files	Coverage Δ
pandas/core/indexes/base.py	96.61% <100%> (-0.08%)	⬇️
pandas/io/formats/printing.py	92.55% <97.33%> (+3.17%)	⬆️

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