Пример #1
0
def parser(stream, objconf, tuples, **kwargs):
    """ Parses the pipe content

    Args:
        stream (Iter[dict]): The source. Note: this shares the `tuples`
            iterator, so consuming it will consume `tuples` as well.

        objconf (obj): the item independent configuration (an Objectify
            instance).

        tuples (Iter[(dict, obj)]): Iterable of tuples of (item, objconf)
            `item` is an element in the source stream and `objconf` is the item
            configuration (an Objectify instance). Note: this shares the
            `stream` iterator, so consuming it will consume `stream` as well.

        kwargs (dict): Keyword arguments.

    Kwargs:
        others (List[Iter(dict)]): List of streams to join

    Returns:
        Iter(dict): The output stream

    Examples:
        >>> from itertools import repeat
        >>>
        >>> stream = ({'x': x} for x in range(5))
        >>> other1 = ({'x': x + 5} for x in range(5))
        >>> other2 = ({'x': x + 10} for x in range(5))
        >>> kwargs = {'others': [other1, other2]}
        >>> tuples = zip(stream, repeat(None))
        >>> len(list(parser(stream, None, tuples, **kwargs)))
        15
    """
    return chain(stream, multiplex(kwargs['others']))
Пример #2
0
def parser(stream, objconf, tuples, **kwargs):
    """ Parses the pipe content

    Args:
        stream (Iter[dict]): The source. Note: this shares the `tuples`
            iterator, so consuming it will consume `tuples` as well.

        objconf (obj): the item independent configuration (an Objectify
            instance).

        tuples (Iter[(dict, obj)]): Iterable of tuples of (item, objconf)
            `item` is an element in the source stream and `objconf` is the item
            configuration (an Objectify instance). Note: this shares the
            `stream` iterator, so consuming it will consume `stream` as well.

        kwargs (dict): Keyword arguments.

    Kwargs:
        others (List[Iter(dict)]): List of streams to join

    Returns:
        Iter(dict): The output stream

    Examples:
        >>> from itertools import repeat
        >>>
        >>> stream = ({'x': x} for x in range(5))
        >>> other1 = ({'x': x + 5} for x in range(5))
        >>> other2 = ({'x': x + 10} for x in range(5))
        >>> kwargs = {'others': [other1, other2]}
        >>> tuples = zip(stream, repeat(None))
        >>> len(list(parser(stream, None, tuples, **kwargs)))
        15
    """
    return chain(stream, multiplex(kwargs['others']))
Пример #3
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    def output(self):
        source = yield self.source
        async_pipeline = partial(self.async_pipe, **self.kwargs)

        if self.mapify:
            args = (async_pipeline, source, self.connections)
            mapped = yield ait.async_map(*args)
            output = multiplex(mapped)
        else:
            output = yield async_pipeline(source)

        return_value(output)
Пример #4
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    def output(self):
        source = yield self.source
        async_pipeline = partial(self.async_pipe, **self.kwargs)

        if self.mapify:
            args = (async_pipeline, source, self.connections)
            mapped = yield ait.async_map(*args)
            output = multiplex(mapped)
        else:
            output = yield async_pipeline(source)

        return_value(output)
Пример #5
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    def output(self):
        pipeline = partial(self.pipe, **self.kwargs)

        if self.parallelize:
            zipped = zip(self.source, repeat(pipeline))
            mapped = self.map(listpipe, zipped, chunksize=self.chunksize)
        elif self.mapify:
            mapped = self.map(pipeline, self.source)

        if self.parallelize and not self.reuse_pool:
            self.pool.close()
            self.pool.join()

        return multiplex(mapped) if self.mapify else pipeline(self.source)
Пример #6
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    def output(self):
        pipeline = partial(self.pipe, **self.kwargs)

        if self.parallelize:
            zipped = zip(self.source, repeat(pipeline))
            mapped = self.map(listpipe, zipped, chunksize=self.chunksize)
        elif self.mapify:
            mapped = self.map(pipeline, self.source)

        if self.parallelize and not self.reuse_pool:
            self.pool.close()
            self.pool.join()

        return multiplex(mapped) if self.mapify else pipeline(self.source)
Пример #7
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        def wrapper(items=None, **kwargs):
            module_name = wrapper.__module__.split('.')[-1]
            wrapper.__dict__['name'] = module_name

            defaults = {
                'dictize': True, 'ftype': 'pass', 'ptype': 'pass',
                'objectify': True, 'emit': True, 'assign': module_name}

            combined = cdicts(self.defaults, defaults, self.opts, kwargs)
            extracted = 'extract' in combined
            pdictize = combined.get('listize') if extracted else True

            combined.setdefault('pdictize', pdictize)
            conf = {k: combined[k] for k in self.defaults}
            conf.update(kwargs.get('conf', {}))
            combined.update({'conf': conf})

            # replace conf with dictized version so we can access its
            # attributes even if we already extracted a value
            updates = {'conf': DotDict(conf), 'assign': combined.get('assign')}
            kwargs.update(updates)

            items = items or iter([])
            _INPUT = map(DotDict, items) if combined.get('dictize') else items
            bfuncs = get_broadcast_funcs(**combined)
            types = {combined['ftype'], combined['ptype']}

            if types.difference({'pass', 'none'}):
                dfuncs = get_dispatch_funcs(**combined)
            else:
                dfuncs = None

            pairs = (dispatch(item, bfuncs, dfuncs=dfuncs) for item in _INPUT)
            parsed, _ = dispatch(DotDict(), bfuncs, dfuncs=dfuncs)

            # - operators can't skip items
            # - purposely setting both variables to maps of the same iterable
            #   since only one is intended to be used at any given time
            # - `tuples` is an iterator of tuples of the first two `parsed`
            #   elements
            tuples = ((p[0][0], p[0][1]) for p in pairs)
            orig_stream = (p[0][0] for p in pairs)
            objconf = parsed[1]

            if self.async:
                stream = yield pipe(orig_stream, objconf, tuples, **kwargs)
            else:
                stream = pipe(orig_stream, objconf, tuples, **kwargs)

            sub_type = 'aggregator' if hasattr(stream, 'keys') else 'composer'
            wrapper.__dict__['sub_type'] = sub_type

            # operators can only assign one value per item and can't skip items
            _, assignment = get_assignment(stream, False, **combined)

            if combined.get('emit'):
                stream = assignment
            else:
                singles = (iter([v]) for v in assignment)
                key = combined.get('assign')
                assigned = (assign({}, s, key, one=True) for s in singles)
                stream = utils.multiplex(assigned)

            if self.async:
                return_value(stream)
            else:
                for s in stream:
                    yield s
Пример #8
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 def fetch(self):
     """Fetch all source urls"""
     kwargs = {'chunksize': self.chunksize} if self.parallel else {}
     mapped = self.map(getpipe, self.zargs, **kwargs)
     return multiplex(mapped)
Пример #9
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 def async_fetch(self):
     """Fetch all source urls"""
     args = (async_get_pipe, self.zargs, self.connections)
     mapped = yield ait.async_map(*args)
     return_value(multiplex(mapped))
Пример #10
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 def async_fetch(self):
     """Fetch all source urls"""
     args = (async_get_pipe, self.zargs, self.connections)
     mapped = yield ait.async_map(*args)
     return_value(multiplex(mapped))
Пример #11
0
        def wrapper(items=None, **kwargs):
            module_name = wrapper.__module__.split('.')[-1]
            wrapper.__dict__['name'] = module_name

            defaults = {
                'dictize': True,
                'ftype': 'pass',
                'ptype': 'pass',
                'objectify': True,
                'emit': True,
                'assign': module_name
            }

            combined = cdicts(self.defaults, defaults, self.opts, kwargs)
            extracted = 'extract' in combined
            pdictize = combined.get('listize') if extracted else True

            combined.setdefault('pdictize', pdictize)
            conf = {k: combined[k] for k in self.defaults}
            conf.update(kwargs.get('conf', {}))
            combined.update({'conf': conf})

            # replace conf with dictized version so we can access its
            # attributes even if we already extracted a value
            updates = {'conf': DotDict(conf), 'assign': combined.get('assign')}
            kwargs.update(updates)

            items = items or iter([])
            _INPUT = map(DotDict, items) if combined.get('dictize') else items
            bfuncs = get_broadcast_funcs(**combined)
            types = {combined['ftype'], combined['ptype']}

            if types.difference({'pass', 'none'}):
                dfuncs = get_dispatch_funcs(**combined)
            else:
                dfuncs = None

            pairs = (dispatch(item, bfuncs, dfuncs=dfuncs) for item in _INPUT)
            parsed, _ = dispatch(DotDict(), bfuncs, dfuncs=dfuncs)

            # - operators can't skip items
            # - purposely setting both variables to maps of the same iterable
            #   since only one is intended to be used at any given time
            # - `tuples` is an iterator of tuples of the first two `parsed`
            #   elements
            tuples = ((p[0][0], p[0][1]) for p in pairs)
            orig_stream = (p[0][0] for p in pairs)
            objconf = parsed[1]

            if self. async:
                stream = yield pipe(orig_stream, objconf, tuples, **kwargs)
            else:
                stream = pipe(orig_stream, objconf, tuples, **kwargs)

            sub_type = 'aggregator' if hasattr(stream, 'keys') else 'composer'
            wrapper.__dict__['sub_type'] = sub_type

            # operators can only assign one value per item and can't skip items
            _, assignment = get_assignment(stream, False, **combined)

            if combined.get('emit'):
                stream = assignment
            else:
                singles = (iter([v]) for v in assignment)
                key = combined.get('assign')
                assigned = (assign({}, s, key, one=True) for s in singles)
                stream = utils.multiplex(assigned)

            if self. async:
                return_value(stream)
            else:
                for s in stream:
                    yield s
Пример #12
0
 def fetch(self):
     """Fetch all source urls"""
     kwargs = {'chunksize': self.chunksize} if self.parallel else {}
     mapped = self.map(getpipe, self.zargs, **kwargs)
     return multiplex(mapped)