def test_total_in_traffic_and_total_out_traffic_by_shop(elasticsearch_traffic):
# Total in traffic and out traffic by shop id
write_fquery_output(
FQuery(get_search()).values(
Sum(TrafficCount.incoming_traffic),
Sum(TrafficCount.outgoing_traffic),
).group_by(TrafficCount.shop_id, ),
'total_in_traffic_and_total_out_traffic_by_shop',
)
def test_total_in_traffic_and_total_out_traffic(elasticsearch_traffic):
# Total in traffic and out traffic
write_fquery_output(
FQuery(get_search()).values(
Sum(TrafficCount.incoming_traffic),
Sum(TrafficCount.outgoing_traffic),
),
'total_in_traffic_and_total_out_traffic',
)
def test_total_sales_by_payment_type(elasticsearch_sale):
# Total sales by payment type
write_fquery_output(
FQuery(get_search()).values(total_sales=Sum(Sale.price), ).group_by(
Sale.payment_type, ),
'total_sales_by_payment_type',
)
def test_total_sales_by_shop(elasticsearch_sale):
# Total sales by shop
write_fquery_output(
FQuery(get_search()).values(total_sales=Sum(Sale.price), ).group_by(
Sale.shop_id, ),
'total_sales_by_shop',
)
def test_total_sales_by_shop_limited_size(elasticsearch_sale):
# Total sales by shop limited size
write_fquery_output(
FQuery(get_search(),
default_size=2).values(total_sales=Sum(Sale.price), ).group_by(
Sale.shop_id, ),
'total_sales_by_shop_limited_size',
)
def test_total_sales_and_avg_sales(elasticsearch_sale):
# Total sales and avg sales, no aggregations
write_fquery_output(
FQuery(get_search()).values(
total_sales=Sum(Sale.price),
avg_sales=Avg(Sale.price),
),
'total_sales_and_avg_sales',
)
def test_total_sales_by_shop_range_by_payment_type(elasticsearch_sale):
# Total sales by shop range by payment_type
ranges = [[1, 5], [5, 11], [11, 15]]
write_fquery_output(
FQuery(get_search()).values(total_sales=Sum(Sale.price), ).group_by(
FieldWithRanges(Sale.shop_id, ranges=ranges),
Sale.payment_type,
),
'total_sales_by_shop_range_by_payment_type',
)
def test_total_sales_every_four_days(elasticsearch_sale):
# Total sales every four days
write_fquery_output(
FQuery(get_search()).values(total_sales=Sum(Sale.price), ).group_by(
DateHistogram(
Sale.timestamp,
interval='4d',
), ),
'total_sales_every_four_days',
)
def test_total_sales_by_period(elasticsearch_sale, interval, pretty_period):
# Total sales period by period
write_fquery_output(
FQuery(get_search()).values(total_sales=Sum(Sale.price), ).group_by(
DateHistogram(
Sale.timestamp,
interval=interval,
), ),
'total_sales_{}_by_{}'.format(pretty_period, pretty_period),
)
def test_total_sales_by_price_histogram(elasticsearch_sale):
# Total sales by price histogram
write_fquery_output(
FQuery(get_search()).values(total_sales=Sum(Sale.price), ).group_by(
Histogram(
Sale.price,
interval=100,
), ),
'total_sales_by_price_histogram',
)
def test_total_sales_by_day_offset(elasticsearch_sale):
# Total sales by day, with offset
write_fquery_output(
FQuery(get_search()).values(total_sales=Sum(Sale.price), ).group_by(
DateHistogram(
Sale.timestamp,
interval='1d',
offset='+8h',
), ),
'total_sales_by_day_offset_8hours',
)
def test_total_and_avg_sales_by_product_type(elasticsearch_sale):
# Average sale price by product type
write_fquery_output(
FQuery(get_search()).values(
ReverseNested(
Sale,
avg_sales=Avg(Sale.price),
total_sales=Sum(Sale.price),
), ).group_by(Sale.product_type, ),
'total_and_avg_sales_by_product_type',
)
def test_total_sales_by_shop_range(elasticsearch_sale):
# Total sales by shop range
ranges = [{
'from': 1,
'to': 5,
'key': '1 - 5',
}, {
'from': 5,
'key': '5+',
}]
write_fquery_output(
FQuery(get_search()).values(total_sales=Sum(Sale.price), ).group_by(
FieldWithRanges(Sale.shop_id, ranges=ranges), ),
'total_sales_by_shop_range',
)