def almost_not_slow():
    CHANNELS = 16
    SAMPLE_LENGTH = CHANNELS // 8
    BUFFER = 256

    vals = {}
    for i in range(2**CHANNELS):
        vals[struct.pack('H', i)] = tuple(b'+1' if e == '1' else b'-1' for e in list("{:016b}".format(i)))

    with open('largefile.dat', 'rb') as f:
        data = f.read()
    size = len(data)
    print("Data size: %d" % size)

    out_file = open('largefile_dump.dat', 'wb')
    out_list = [out_file]*CHANNELS

    samples = ()

    for i in range(0, size, SAMPLE_LENGTH):
        if i % (1024*1024) == 0: print("i = %d" % i)
        samples = samples + (vals[data[i:i+SAMPLE_LENGTH]],)
        if len(samples) == BUFFER:
            for channel in range(CHANNELS):
                s = b'\n'.join(r[channel] for r in samples)
                out_list[channel].write(s)
            samples = ()

    if samples:
        for channel in range(CHANNELS):
            s = b'\n'.join(r[channel] for r in samples)
            out_list[channel].write(s)

    out_file.close()