Utility function taking care of the internal changes between RestrictedPython v3
and v5, keeping support for both (instead of having multiple if statements).

* Emtpy parameter.
* No argument.

Pandas 0.20.0 introduced a bug fix [1] which changed the behaviour of
'DataFrame.to_records()', so that the resulting Record objects dtype names are
unicodes if the data frames column names were unicode. Before this bug fix
the dtype names were str, no matter whether the column names were str or unicode.

Unfortunately np unpickle breaks if dtype names are unicode [2]. Since
many of our data frame columns are unicode, loading arrays often
fails. In python3 this isn't a problem anymore, so until then we fix
this by introducing a simple monkey patch to pandas, which basically
reverts the mentioned bug fix.

[1] https://github.com/pandas-dev/pandas/issues/11879
[2] Small example to reproduce this error:

''
import os

import numpy as np
import pandas as pd

r = pd.DataFrame({u'A':[1,2,3]}).to_records()
a = np.ndarray(shape=r.shape, dtype=r.dtype.fields)
p = "t"

try:
  os.remove(p)
except:
  pass

with open(p, 'wb') as f:
  np.save(f, a)
with open(p, 'rb') as f:
  np.load(f)
''

/reviewed-on nexedi/erp5!1738
/reviewed-by @jerome @klaus

Add test which verifies that we can un/pickle 'pd.DataFrame' which were
converted to 'np.recarray' via the '.to_records()' method.

This test is necessary because it turns out that the combination of
pandas >= 0.20.x + python2 doesn't support this functionality by
default if the data frames column names are unicodes.

Please see !1738 (comment 179298) for
additional context.

/reviewed-on !1738
/reviewed-by @jerome @klaus

There are newer pandas versions which still support python2. The latest
one which still supports py2 (0.24.x) has initially been released in 2019
and should therefore be quite stable and better supported. We should
therefore prepare ERP5 so that it support those newer versions.

This patch mostly fixes movements within the internal pandas structure.
The patch still supports old object locations of previous pandas versions.

/reviewed-on nexedi/erp5!1738
/reviewed-by @jerome @klaus