github.com/grumpyhome/grumpy@v0.3.1-0.20201208125205-7b775405bdf1/grumpy-runtime-src/third_party/stdlib/unittest_util.py

"""Various utility functions."""
# from collections import namedtuple, OrderedDict

import operator
_itemgetter = operator.itemgetter
_property = property
_tuple = tuple

__unittest = True

_MAX_LENGTH = 80
def safe_repr(obj, short=False):
    try:
        result = repr(obj)
    except Exception:
        result = object.__repr__(obj)
    if not short or len(result) < _MAX_LENGTH:
        return result
    return result[:_MAX_LENGTH] + ' [truncated]...'


def strclass(cls):
    return "%s.%s" % (cls.__module__, cls.__name__)

def sorted_list_difference(expected, actual):
    """Finds elements in only one or the other of two, sorted input lists.

    Returns a two-element tuple of lists.    The first list contains those
    elements in the "expected" list but not in the "actual" list, and the
    second contains those elements in the "actual" list but not in the
    "expected" list.    Duplicate elements in either input list are ignored.
    """
    i = j = 0
    missing = []
    unexpected = []
    while True:
        try:
            e = expected[i]
            a = actual[j]
            if e < a:
                missing.append(e)
                i += 1
                while expected[i] == e:
                    i += 1
            elif e > a:
                unexpected.append(a)
                j += 1
                while actual[j] == a:
                    j += 1
            else:
                i += 1
                try:
                    while expected[i] == e:
                        i += 1
                finally:
                    j += 1
                    while actual[j] == a:
                        j += 1
        except IndexError:
            missing.extend(expected[i:])
            unexpected.extend(actual[j:])
            break
    return missing, unexpected


def unorderable_list_difference(expected, actual, ignore_duplicate=False):
    """Same behavior as sorted_list_difference but
    for lists of unorderable items (like dicts).

    As it does a linear search per item (remove) it
    has O(n*n) performance.
    """
    missing = []
    unexpected = []
    while expected:
        item = expected.pop()
        try:
            actual.remove(item)
        except ValueError:
            missing.append(item)
        if ignore_duplicate:
            for lst in expected, actual:
                try:
                    while True:
                        lst.remove(item)
                except ValueError:
                    pass
    if ignore_duplicate:
        while actual:
            item = actual.pop()
            unexpected.append(item)
            try:
                while True:
                    actual.remove(item)
            except ValueError:
                pass
        return missing, unexpected

    # anything left in actual is unexpected
    return missing, actual

# _Mismatch = namedtuple('Mismatch', 'actual expected value')
class _Mismatch(tuple):
    'Mismatch(actual, expected, value)'

    __slots__ = ()

    _fields = ('actual', 'expected', 'value')

    def __new__(_cls, actual, expected, value):
        'Create new instance of Mismatch(actual, expected, value)'
        return _tuple.__new__(_cls, (actual, expected, value))

    # @classmethod
    def _make(cls, iterable, new=tuple.__new__, len=len):
        'Make a new Mismatch object from a sequence or iterable'
        result = new(cls, iterable)
        if len(result) != 3:
            raise TypeError('Expected 3 arguments, got %d' % len(result))
        return result
    _make = classmethod(_make)

    def __repr__(self):
        'Return a nicely formatted representation string'
        return 'Mismatch(actual=%r, expected=%r, value=%r)' % self

    def _asdict(self):
        'Return a new OrderedDict which maps field names to their values'
        # return OrderedDict(zip(self._fields, self))
        return dict(zip(self._fields, self))

    def _replace(_self, **kwds):
        'Return a new Mismatch object replacing specified fields with new values'
        result = _self._make(map(kwds.pop, ('actual', 'expected', 'value'), _self))
        if kwds:
            raise ValueError('Got unexpected field names: %r' % kwds.keys())
        return result

    def __getnewargs__(self):
        'Return self as a plain tuple.  Used by copy and pickle.'
        return tuple(self)

    __dict__ = _property(_asdict)

    def __getstate__(self):
        'Exclude the OrderedDict from pickling'
        pass

    actual = _property(_itemgetter(0), doc='Alias for field number 0')

    expected = _property(_itemgetter(1), doc='Alias for field number 1')

    value = _property(_itemgetter(2), doc='Alias for field number 2')

def _count_diff_all_purpose(actual, expected):
    'Returns list of (cnt_act, cnt_exp, elem) triples where the counts differ'
    # elements need not be hashable
    s, t = list(actual), list(expected)
    m, n = len(s), len(t)
    NULL = object()
    result = []
    for i, elem in enumerate(s):
        if elem is NULL:
            continue
        cnt_s = cnt_t = 0
        for j in range(i, m):
            if s[j] == elem:
                cnt_s += 1
                s[j] = NULL
        for j, other_elem in enumerate(t):
            if other_elem == elem:
                cnt_t += 1
                t[j] = NULL
        if cnt_s != cnt_t:
            diff = _Mismatch(cnt_s, cnt_t, elem)
            result.append(diff)

    for i, elem in enumerate(t):
        if elem is NULL:
            continue
        cnt_t = 0
        for j in range(i, n):
            if t[j] == elem:
                cnt_t += 1
                t[j] = NULL
        diff = _Mismatch(0, cnt_t, elem)
        result.append(diff)
    return result

def _ordered_count(iterable):
    'Return dict of element counts, in the order they were first seen'
    c = {} #OrderedDict()
    for elem in iterable:
        c[elem] = c.get(elem, 0) + 1
    return c

def _count_diff_hashable(actual, expected):
    'Returns list of (cnt_act, cnt_exp, elem) triples where the counts differ'
    # elements must be hashable
    s, t = _ordered_count(actual), _ordered_count(expected)
    result = []
    for elem, cnt_s in s.items():
        cnt_t = t.get(elem, 0)
        if cnt_s != cnt_t:
            diff = _Mismatch(cnt_s, cnt_t, elem)
            result.append(diff)
    for elem, cnt_t in t.items():
        if elem not in s:
            diff = _Mismatch(0, cnt_t, elem)
            result.append(diff)
    return result