from datetime import datetime
from datetime import timedelta

def queryset_generator(queryset, chunksize=1000):
    """ 
    Iterate over a Django Queryset ordered by the primary key

    This method loads a maximum of chunksize (default: 1000) rows in its
    memory at the same time while django normally would load all rows in its
    memory. Using the iterator() method only causes it to not preload all the
    classes.

    Note that the implementation of the generator does not support ordered query sets.

    """
    last_pk = queryset.order_by('-pk')[0].pk
    queryset = queryset.order_by('pk')
    pk = queryset[0].pk - 1
    while pk < last_pk:
        for row in queryset.filter(pk__gt=pk)[:chunksize]:
            pk = row.pk
            yield row 
        gc.collect()


def queryset_list_generator(queryset, listsize=10000, chunksize=1000):
    """ 
    Iterate over a Django Queryset ordered by the primary key and return a
    list of model objects of the size 'listsize'.
    
    This method loads a maximum of chunksize (default: 1000) rows in its memory
    at the same time while django normally would load all rows in its memory.
    In contrast to the queryset_generator, it doesn't return each row on its own,
    but returns a list of listsize (default: 10000) rows at a time.

    Note that the implementation of the generator does not support ordered query sets.
    
    """
    it = queryset_generator(queryset, chunksize)
    i = 0 
    row_list = []
    for row in it: 
        i += 1
        row_list.append(row)
        if i >= listsize:
            yield row_list
            i = 0 
            row_list = []

def queryset_generator_by_date(queryset, date_field, start_date, end_date, chunksize=7):
    '''
    Takes a queryset and chunks it by date. Useful if sorting by pk isn't 
    needed. For large querysets, such sorting can be very expensive.
    
    date_field is the name of the date field that should be used for chunking.
    This field should have db_index=True in your model.

    Chunksize should be given in days, and start and end dates should be provided
    as strings in the form 2012-03-08.
    '''
    chunksize = timedelta(chunksize)
    end_date = datetime.strptime(end_date, '%Y-%m-%d').date()
    bottom_date = datetime.strptime(start_date, '%Y-%m-%d').date()
    top_date = bottom_date + chunksize - timedelta(1)
    while bottom_date <= end_date:
        if top_date > end_date:
            # Last iteration
            top_date = end_date
        keywords = {'%s__gte' % date_field : bottom_date,
                    '%s__lte' % date_field : top_date}
        bottom_date = bottom_date + chunksize
        top_date = top_date + chunksize
        for row in queryset.filter(**keywords):
            yield row