A walk through

Update

You can now go to https://django-slick-reporting for a better and practical guidance on the types of reports and what you can do.

Given that you have a model where there are data stored which you want to generate reports on. Consider below SalesOrder model example.

order_date	product_id	client_id	quantity	price	value
2019-01-01	1	1	5	15	75
2019-02-15	2	2	7	20	140
2019-02-20	2	1	5	20	100
2019-03-14	1	2	3	15	45

Slick Reporting help us answer some questions, like:

• To start: Wouldn’t it be nice if we have a view page where we can filter the data based on date , client(s) and or product(s)

• How much each product was sold or How much each Client bought? Filter by date range / client(s) / product(s)

• How well each product sales is doing, monthly?

• How client 1 compared with client 2, compared with the rest of clients, on each product sales ?

• How many orders were created a day ?

To answer those question, We can identify basic kind of alteration / calculation on the data

1. Basic filtering

Start small, A ReportView like the below

# in your urls.py
path("path-to-report", TransactionsReport.as_view())

# in your views.py
from slick_reporting.views import ReportView


class TransactionsReport(ReportView):
    report_model = MySalesItem
    columns = [
        "order_date",
        "product__name",
        "client__name",
        "quantity",
        "price",
        "value",
    ]

will yield a Page with a nice filter form with A report where it displays the data as is but with filters however we can apply date and other filters

order_date	Product Name	Client Name	quantity	price	value
2019-01-01	Product 1	Client 1	5	15	75
2019-02-15	Product 2	Client 2	7	20	140
2019-02-20	Product 2	Client 1	5	20	100
2019-03-14	Product 1	Client 2	3	15	45

2. Group By report

Where we can group by product -for example- and sum the quantity, or value sold.

Product	Total Quantity	Total Value
Product 1	8	120
Product 2	13	240

which can be written like this:

class TotalQuanAndValueReport(ReportView):
    report_model = MySalesItem
    group_by = "product"
    columns = ["name", "__total_quantity__", "__total__"]

3. Time Series report

where we can say how much sum of the quantity sold over a chunks of time periods (like weekly, monthly, … )

Product Name	SKU	Total Quantity in Jan 20	Total Quantity in Feb 20	Total Quantity in …	Total Quantity in December 20
Product 1	<from product model>	5	0	…	14
Product 2	<from product model>	0	13	…	12
Product 3	<from product model>	17	12	…	17

can be written like this

class TotalQuantityMonthly(ReportView):
    report_model = MySalesItem
    group_by = "product"
    columns = ["name", "sku"]

    time_series_pattern = "monthly"
    time_series_columns = ["__total_quantity__"]

4. Cross tab report

Where we can cross product sold over client for example

Product Name	SKU	Client 1 Total value	Client 2 Total Value	Client (n)	The Reminder
Product 1	<from product model>	10	15	…	14
Product 2	<from product model>	11	12	…	12
Product 3	<from product model>	17	12	…	17

Which can be written like this

class CrosstabProductClientValue(ReportView):
    report_model = MySalesItem
    group_by = "product"
    columns = ["name", "sku"]

    crosstab_model = "client"
    crosstab_columns = ["__total_value__"]
    crosstab_ids = [client1.pk, client2.pk, client3.pk]
    crosstab_compute_remainder = True

5. Time series - Cross tab

(#2 & #3 together) Not support at the time.. but soon we hope.