Ejemplo n.º 1
0
def make_db(db, amount=100):
    total = 0
    for chunk in chunked(enumerate(gather_documents(amount), total + 1), 10, trail=True):
        with db as session:
            indexed = Indexed(session)
            for total, document in chunk:
                if len(document):
                    session.add(document)
                    indexed.add(document)
                    print(total, ":", repr(document))
    return total
Ejemplo n.º 2
0
def simultaneously (function, iterable, max_workers=4) :
    ''' This runs the given function over the iterable concurrently, in a similar fashion to the built-in <map>
        function. The output's order is not guaranteed to correspond the order of the input iterable. Therefor the
        output order should be treated as undefined. The <max_workers> argument denotes the amount of worker threads to
        use. '''

    if max_workers < 1 :
        raise ValueError('<simultaneously> requires at least one worker thread.')

    with ThreadPoolExecutor(max_workers=max_workers) as executor :

        futures = (executor.submit(function, item)
                   for item in iterable)

        for chunk in chunked(futures, max_workers, trail=True) :
            for future in as_completed(chunk) :
                yield future.result()
Ejemplo n.º 3
0
def plot(
    iterable, key=lambda item: item, sample_size=1, depth=1, colors=_plot_colors, basecase=_plot_basecase, _show=True
):
    """ This function can be used for plotting an iterable graphically. If matplotlib isn't installed, this will only
        throw a warning, and no GUI will be launched.. """

    try:
        pyplot
    except NameError:
        warnings.warn("matplotlib must be installed in order to see the plot graphic.", Warning)
    else:
        for i, iterable in enumerate(flattened(iterable, basecase)):
            xs, ys = zip(
                *(
                    (i, math.avg(key(item) for item in sample))
                    for i, sample in enumerate(iterate.chunked(iterable, sample_size, trail=True))
                )
            )

            pyplot.plot(xs, ys, linewidth=1.0, color=colors[i % len(colors)])

        if _show:
            pyplot.show()
Ejemplo n.º 4
0
 def matching (self, strings, cls=Seq, chunk_size=100) :
     for chunked_strings in chunked(strings, chunk_size, trail=True) :
         for match in self.session._sqlalchemy_session.query(cls).filter(cls.string.in_(chunked_strings)).all() :
             yield match