Python itertools.ifilter() Examples

def __and__(self, other):
                ''' Intersection is the minimum of corresponding counts.

                >>> Counter('abbb') & Counter('bcc')
                Counter({'b': 1})

                '''
                if not isinstance(other, Counter):
                    return NotImplemented
                _min = min
                result = Counter()
                if len(self) < len(other):
                    self, other = other, self
                for elem in ifilter(self.__contains__, other):
                    newcount = _min(self[elem], other[elem])
                    if newcount > 0:
                        result[elem] = newcount
                return result 

def wallclock_for_operation(results, operation):
    """
    Calculate the wallclock time for a process running in a particular
    scenario.

    :param results: Results to extract values from.
    :param operation: Operation name to calculate wallclock results for.

    :return: The mean wallclock time observed.
    """
    operation_results = itertools.ifilter(
        lambda r: r['metric']['type'] == 'wallclock' and
        r['operation']['type'] == operation,
        results
    )
    values = [r['value'] for r in operation_results]
    return mean(values) 

def __and__(self, other):
        ''' Intersection is the minimum of corresponding counts.

        >>> Counter('abbb') & Counter('bcc')
        Counter({'b': 1})

        '''
        if not isinstance(other, Counter):
            return NotImplemented
        _min = min
        result = Counter()
        if len(self) < len(other):
            self, other = other, self
        for elem in ifilter(self.__contains__, other):
            newcount = _min(self[elem], other[elem])
            if newcount > 0:
                result[elem] = newcount
        return result 

def countByValueAndWindow(self, windowDuration, slideDuration, numPartitions=None):
        """
        Return a new DStream in which each RDD contains the count of distinct elements in
        RDDs in a sliding window over this DStream.

        @param windowDuration: width of the window; must be a multiple of this DStream's
                              batching interval
        @param slideDuration:  sliding interval of the window (i.e., the interval after which
                              the new DStream will generate RDDs); must be a multiple of this
                              DStream's batching interval
        @param numPartitions:  number of partitions of each RDD in the new DStream.
        """
        keyed = self.map(lambda x: (x, 1))
        counted = keyed.reduceByKeyAndWindow(operator.add, operator.sub,
                                             windowDuration, slideDuration, numPartitions)
        return counted.filter(lambda kv: kv[1] > 0) 

def lookup(self, key):
        """
        Return the list of values in the RDD for key `key`. This operation
        is done efficiently if the RDD has a known partitioner by only
        searching the partition that the key maps to.

        >>> l = range(1000)
        >>> rdd = sc.parallelize(zip(l, l), 10)
        >>> rdd.lookup(42)  # slow
        [42]
        >>> sorted = rdd.sortByKey()
        >>> sorted.lookup(42)  # fast
        [42]
        >>> sorted.lookup(1024)
        []
        >>> rdd2 = sc.parallelize([(('a', 'b'), 'c')]).groupByKey()
        >>> list(rdd2.lookup(('a', 'b'))[0])
        ['c']
        """
        values = self.filter(lambda kv: kv[0] == key).values()

        if self.partitioner is not None:
            return self.ctx.runJob(values, lambda x: x, [self.partitioner(key)])

        return values.collect() 

def __and__(self, other):
        ''' Intersection is the minimum of corresponding counts.

        >>> Counter('abbb') & Counter('bcc')
        Counter({'b': 1})

        '''
        if not isinstance(other, Counter):
            return NotImplemented
        _min = min
        result = Counter()
        if len(self) < len(other):
            self, other = other, self
        for elem in ifilter(self.__contains__, other):
            newcount = _min(self[elem], other[elem])
            if newcount > 0:
                result[elem] = newcount
        return result 

def __define_optimizer(self, learning_rate, weight_decay,
                           lr_drop_factor, lr_drop_patience, optimizer='Adam'):
        assert optimizer in ['RMSprop', 'Adam', 'Adadelta', 'SGD']

        parameters = ifilter(lambda p: p.requires_grad,
                             self.model.parameters())

        if optimizer == 'RMSprop':
            self.optimizer = optim.RMSprop(
                parameters, lr=learning_rate, weight_decay=weight_decay)
        elif optimizer == 'Adadelta':
            self.optimizer = optim.Adadelta(
                parameters, lr=learning_rate, weight_decay=weight_decay)
        elif optimizer == 'Adam':
            self.optimizer = optim.Adam(
                parameters, lr=learning_rate, weight_decay=weight_decay)
        elif optimizer == 'SGD':
            self.optimizer = optim.SGD(
                parameters, lr=learning_rate, momentum=0.9,
                weight_decay=weight_decay)

        self.lr_scheduler = ReduceLROnPlateau(
            self.optimizer, mode='min', factor=lr_drop_factor,
            patience=lr_drop_patience, verbose=True) 

def iteritems(self):
            definitions = type(self).configuration_setting_definitions
            version = self.command.protocol_version
            return ifilter(
                lambda (name, value): value is not None, imap(
                    lambda setting: (setting.name, setting.__get__(self)), ifilter(
                        lambda setting: setting.is_supported_by_protocol(version), definitions))) 

def iteritems(self):
            iteritems = SearchCommand.ConfigurationSettings.iteritems(self)
            version = self.command.protocol_version
            if version == 1:
                if self.required_fields is None:
                    iteritems = ifilter(lambda (name, value): name != 'clear_required_fields', iteritems)
            else:
                iteritems = ifilter(lambda (name, value): name != 'distributed', iteritems)
                if self.distributed:
                    iteritems = imap(
                        lambda (name, value): (name, 'stateful') if name == 'type' else (name, value), iteritems)
            return iteritems

        # endregion 

def iteritems(self):
            iteritems = SearchCommand.ConfigurationSettings.iteritems(self)
            version = self.command.protocol_version
            if version == 2:
                iteritems = ifilter(lambda (name, value): name != 'distributed', iteritems)
                if self.distributed and self.type == 'streaming':
                    iteritems = imap(
                        lambda (name, value): (name, 'stateful') if name == 'type' else (name, value), iteritems)
            return iteritems 

def _compile_object(self, schema):
        """Validate an object.

        Has the same behavior as dictionary validator but work with object
        attributes.

        For example:

            >>> class Structure(object):
            ...     def __init__(self, one=None, three=None):
            ...         self.one = one
            ...         self.three = three
            ...
            >>> validate = Schema(Object({'one': 'two', 'three': 'four'}, cls=Structure))
            >>> with raises(MultipleInvalid, "not a valid value for object value @ data['one']"):
            ...   validate(Structure(one='three'))

        """
        base_validate = self._compile_mapping(
            schema, invalid_msg='object value')

        def validate_object(path, data):
            if (schema.cls is not UNDEFINED
                    and not isinstance(data, schema.cls)):
                raise ObjectInvalid('expected a {0!r}'.format(schema.cls), path)
            iterable = _iterate_object(data)
            iterable = ifilter(lambda item: item[1] is not None, iterable)
            out = base_validate(path, iterable, {})
            return type(data)(**out)

        return validate_object 

def phase1(self): # Compute common names
        a = dict(izip(imap(os.path.normcase, self.left_list), self.left_list))
        b = dict(izip(imap(os.path.normcase, self.right_list), self.right_list))
        self.common = map(a.__getitem__, ifilter(b.__contains__, a))
        self.left_only = map(a.__getitem__, ifilterfalse(b.__contains__, a))
        self.right_only = map(b.__getitem__, ifilterfalse(a.__contains__, b)) 

def intersection(self, other):
        """Return the intersection of two sets as a new set.

        (I.e. all elements that are in both sets.)
        """
        if not isinstance(other, BaseSet):
            other = Set(other)
        if len(self) <= len(other):
            little, big = self, other
        else:
            little, big = other, self
        common = ifilter(big._data.__contains__, little)
        return self.__class__(common) 

def difference_update(self, other):
        """Remove all elements of another set from this set."""
        data = self._data
        if not isinstance(other, BaseSet):
            other = Set(other)
        if self is other:
            self.clear()
        for elt in ifilter(data.__contains__, other):
            del data[elt]

    # Python dict-like mass mutations: update, clear 

def phase1(self): # Compute common names
        a = dict(izip(imap(os.path.normcase, self.left_list), self.left_list))
        b = dict(izip(imap(os.path.normcase, self.right_list), self.right_list))
        self.common = map(a.__getitem__, ifilter(b.__contains__, a))
        self.left_only = map(a.__getitem__, ifilterfalse(b.__contains__, a))
        self.right_only = map(b.__getitem__, ifilterfalse(a.__contains__, b)) 

def intersection(self, other):
        """Return the intersection of two sets as a new set.

        (I.e. all elements that are in both sets.)
        """
        if not isinstance(other, BaseSet):
            other = Set(other)
        if len(self) <= len(other):
            little, big = self, other
        else:
            little, big = other, self
        common = ifilter(big._data.__contains__, little)
        return self.__class__(common) 

def difference_update(self, other):
        """Remove all elements of another set from this set."""
        data = self._data
        if not isinstance(other, BaseSet):
            other = Set(other)
        if self is other:
            self.clear()
        for elt in ifilter(data.__contains__, other):
            del data[elt]

    # Python dict-like mass mutations: update, clear 

def test_itertools(self):
        from itertools import imap, izip, ifilter
        # We will assume that the itertools functions work, so provided
        # that we've got identical coppies, we will work!
        self.assertEqual(map, imap)
        self.assertEqual(zip, izip)
        self.assertEqual(filter, ifilter)
        # Testing that filter(None, stuff) raises a warning lives in
        # test_py3kwarn.py 

def first(condition, seq):
    try:
        return next(ifilter(condition, seq))
    except StopIteration:
        return None 

def _compile_object(self, schema):
        """Validate an object.

        Has the same behavior as dictionary validator but work with object
        attributes.

        For example:

            >>> class Structure(object):
            ...     def __init__(self, one=None, three=None):
            ...         self.one = one
            ...         self.three = three
            ...
            >>> validate = Schema(Object({'one': 'two', 'three': 'four'}, cls=Structure))
            >>> with raises(MultipleInvalid, "not a valid value for object value @ data['one']"):
            ...   validate(Structure(one='three'))

        """
        base_validate = self._compile_mapping(schema,
            invalid_msg='for object value')

        def validate_object(path, data):
            if schema.cls is not UNDEFINED and not isinstance(data, schema.cls):
                raise Invalid('expected a {0!r}'.format(schema.cls), path)
            iterable = _iterate_object(data)
            iterable = ifilter(lambda item: item[1] is not None, iterable)
            out = base_validate(path, iterable, {})
            return type(data)(**out)

        return validate_object 

def _IsFunctionLiteralBlock(block_context):
  """Check if a context is a function literal block (without parameters).

  Example function literal block: 'function() {}'

  Args:
    block_context: An EcmaContext of type block.

  Returns:
    Whether this context is a function literal block.
  """

  previous_code_tokens_iter = itertools.ifilter(
      lambda token: token not in JavaScriptTokenType.NON_CODE_TYPES,
      reversed(block_context.start_token))

  # Ignore the current token
  next(previous_code_tokens_iter, None)

  # Grab the previous three tokens and put them in correct order.
  previous_code_tokens = list(itertools.islice(previous_code_tokens_iter, 3))
  previous_code_tokens.reverse()

  # There aren't three previous tokens.
  if len(previous_code_tokens) is not 3:
    return False

  # Check that the previous three code tokens are "function ()"
  previous_code_token_types = [token.type for token in previous_code_tokens]
  if (previous_code_token_types == [
      JavaScriptTokenType.FUNCTION_DECLARATION,
      JavaScriptTokenType.START_PARAMETERS,
      JavaScriptTokenType.END_PARAMETERS]):
    return True

  return False 

def phase1(self): # Compute common names
        a = dict(izip(imap(os.path.normcase, self.left_list), self.left_list))
        b = dict(izip(imap(os.path.normcase, self.right_list), self.right_list))
        self.common = map(a.__getitem__, ifilter(b.__contains__, a))
        self.left_only = map(a.__getitem__, ifilterfalse(b.__contains__, a))
        self.right_only = map(b.__getitem__, ifilterfalse(a.__contains__, b)) 

def intersection(self, other):
        """Return the intersection of two sets as a new set.

        (I.e. all elements that are in both sets.)
        """
        if not isinstance(other, BaseSet):
            other = Set(other)
        if len(self) <= len(other):
            little, big = self, other
        else:
            little, big = other, self
        common = ifilter(big._data.__contains__, little)
        return self.__class__(common) 

def difference_update(self, other):
        """Remove all elements of another set from this set."""
        data = self._data
        if not isinstance(other, BaseSet):
            other = Set(other)
        if self is other:
            self.clear()
        for elt in ifilter(data.__contains__, other):
            del data[elt]

    # Python dict-like mass mutations: update, clear 

def test_itertools(self):
        from itertools import imap, izip, ifilter
        # We will assume that the itertools functions work, so provided
        # that we've got identical coppies, we will work!
        self.assertEqual(map, imap)
        self.assertEqual(zip, izip)
        self.assertEqual(filter, ifilter)
        # Testing that filter(None, stuff) raises a warning lives in
        # test_py3kwarn.py 

def formatException(self, ei, strip_newlines=True):
        lines = traceback.format_exception(*ei)
        if strip_newlines:
            lines = [itertools.ifilter(
                lambda x: x,
                line.rstrip().splitlines()) for line in lines]
            lines = list(itertools.chain(*lines))
        return lines 

def phase1(self): # Compute common names
        a = dict(izip(imap(os.path.normcase, self.left_list), self.left_list))
        b = dict(izip(imap(os.path.normcase, self.right_list), self.right_list))
        self.common = map(a.__getitem__, ifilter(b.__contains__, a))
        self.left_only = map(a.__getitem__, ifilterfalse(b.__contains__, a))
        self.right_only = map(b.__getitem__, ifilterfalse(a.__contains__, b)) 

def approximate_match(word_re, lines, fuzziness='e<=1'):
        logger = logging.getLogger(__name__)
        logger.debug('Looking for %s with fuzziness: %s' % (word_re, fuzziness))
        best_partial_matches = []
        search = re.compile(
            ur'(' + word_re + '){' + fuzziness + '}',
            flags=re.BESTMATCH | re.IGNORECASE).search
        for m in ifilter(None, imap(search, lines)):
            logger.debug('%s %s' % (m.span(), m[0]))
            best_partial_matches.append(m[0])
        return best_partial_matches 

def phase1(self): # Compute common names
        a = dict(izip(imap(os.path.normcase, self.left_list), self.left_list))
        b = dict(izip(imap(os.path.normcase, self.right_list), self.right_list))
        self.common = map(a.__getitem__, ifilter(b.__contains__, a))
        self.left_only = map(a.__getitem__, ifilterfalse(b.__contains__, a))
        self.right_only = map(b.__getitem__, ifilterfalse(a.__contains__, b)) 

def intersection(self, other):
        """Return the intersection of two sets as a new set.

        (I.e. all elements that are in both sets.)
        """
        if not isinstance(other, BaseSet):
            other = Set(other)
        if len(self) <= len(other):
            little, big = self, other
        else:
            little, big = other, self
        common = ifilter(big._data.__contains__, little)
        return self.__class__(common)