A django package for creating stats from a query. This package should be compatible with all Django versions > 3.x
You can use something like this:
class TravelStats(StatSet):
total = QueryAggregateSingleStat(label='Total')
amount = QueryAggregateSingleStat(label='Total amount', method='sum')
port__name = QueryAggregateStat(label='By port', )to get something like this:
Install it from pip:
pip install django-simple-stats
or the latest version from git:
pip install git+https://github.com/spapas/django-simple-stats
No other installation is needed.
- The
query_aggregate_single/QueryAggregateSingleStatwill run the aggregate function on a field and return a single value. For example you can get the total number of rows of your query or the sum of all fields. - The
query_aggregate/QueryAggregateStatwill run the aggregate function on a field and return the list of values. You can run the aggregate function on a different field by passingaggr_field(so you can group by a field and return the sum of another field for each group). This is mainly useful for foreign keys and if you've got distinct values in your queries. For example count the number of rows per user. Also it is useful for booleans for example to get the number of rows that have a flag turned on and off. - The
choice_aggregate/ChoiceAggregateStatis similar to thequery_aggregatebut will use achoicesattribute to return better looking values. This will not return Null values - The
choice_aggregate_with_null/ChoiceAggregateNullStatis the same aschoice_aggregatebut will return Null values (so you can add a(None, "Empty")choice to your choices) - The
query_aggregate_date/QueryAggregateDateStatis similar to thequery_aggregatebut will return the aggregates on a specific date field; usewhatto passyear,month,day. - The
query_aggregate_datetime/QueryAggregateDateTimeStatis similar to thequery_aggregate_datebut will return the aggregates on time also. - The
query_aggregate_extract_date/QueryAggregateExtractDateStatis similar toquery_aggregate_datebut will useExtractfor the date instead ofTrunc. This is useful if you want to group by the month/day/hour etc as a specific value, i.e this will group all rows of June on the same row whilequery_aggregate_datewill differntiate between June 21 and June 22 and June 23. - Finally, the
query_aggregate_buckets//QueryAggregateBucketsStatis used to create buckets of values. You'll pass the list of buckets and the query will return the results that belong in each bucket. The stats module will run individual queries withfield__gtefor each value. So for example if you pass[100, 50, 10]and you have a fieldpriceit will runprice__gte=100,price__gte=50,price__gte=10and return the results.
Both a declarative (similar to how Django models/forms work) and a functional API can be used.
For the declarative API, you need to declare a class inheriting from simple_stats.StatSet and
declare the stats fields in it using the corresponding stats classes like simple_stats.QueryAggregateStat.
Then you'll initialize this class in your Django view passing it the query. For example:
from simple_stats import StatSet, QueryAggregateSingleStat
class MyStats(StatSet):
id = QueryAggregateSingleStat(label='Total number')
# Then in your view
stats = MyStats(query=MyModel.objects.all())The stats classes take the following initialization parameters:
- field (optional): The field that the aggreate will run on; use
__for joins i.efiedld1__field2 - label (optional): The textual description of this statistic (will be filled with the field if not passed)
- method (optional): The aggregate method. Can be one of
count,sum,max,min,avg. Default is count - what (optional): Only required for
query_aggregate_date, it is eithedyear,month,day - choices (optional): Only required for
choice_aggregateandchoice_aggregate_with_null, it must be a django choices list - buckets (optional): Only required for
query_aggregate_buckets. Must be a list from the biggest to the lowest value. - aggr_field (optional): This field is optional and can be used for
query_aggregate,query_aggregate_date,choice_aggregateandchoice_aggregate_with_null. It denotes a field that would run the aggregate function on. - formatter (optional): A callback that can be used to format the value, it should get a value and return a rendered value (i.e
lambda v: "${}".format(v))
Please notice that if you don't pass the field parameter then the name of the attribute will be used (i.e. it will be
field=id in the example above).
The StatSet instance will be an enumerable returning a list of dictionaries with the following attributes:
- label: Same as the label in the configuration
- value: Will have a value if you use the query_aggregate_single, else will be None
- values: Will be empty for query_aggregate_single else will be a list of tuples. Each tuple will have two elements,
(label, value)
On the other hand, the only supported method in the functional API the simple_stats.get_stats.
It expects a django query and the stats configuration (list of dicts).
Each element of the configuration list is a dictionary that has the same attributes as the init parameters
for the class. There are only two differences:
- The field is now required
- We must pass the kind of aggregate we need (similar to the class we used on the declarative API). Choices here are:
query_aggregate_single,query_aggregate,choice_aggregate,choice_aggregate_with_null,query_aggregate_date,query_aggregate_buckets.
See below for a complete example.
The response will be a list of dictionaries with the same attributes as the StatSet instance.
Please notice that the declarative api will create a dictionary and actually call the get_stats
function so in both cases the result will be exactly the same.
Please remember in the example below that if you don't pass the field parameter then the name of the
attribute will be used. Also by default the method is count.
from simple_stats import from simple_stats import (
StatSet,
QueryAggregateStat,
QueryAggregateSingleStat,
ChoiceAggregateStat,
QueryAggregateDateStat,
QueryAggregateBucketsStat,
)
class MyStats(StatSet):
id = QueryAggregateSingleStat(label='Total number')
price = QueryAggregateSingleStat(label='Total price', method='sum')
pilot_authority__name = QueryAggregateStat(label='Per authority')
pilot_authority__name = QueryAggregateStat(label='Per authority by price', aggr_field='price')
status = ChoiceAggregateStat(label='Per status', choices=MyModel.STATUS_CHOICES)
status_price = ChoiceAggregateStat(
label='Per status by price',
choices=MyModel.STATUS_CHOICES,
field='status',
aggr_field='price'
formatter=lambda v: "€ {}".format(v) if v else '-'
)
year = QueryAggregateDateStat(label='Per year', what='year', field='created_on')
year_price = QueryAggregateDateStat(label='Per year by price', what='year', aggr_field='price', field='created_on')
buckets = QueryAggregateBucketsStat(label='Buckets', buckets=[100, 50, 10])
def my_view(request):
qs = TestModel.objects.all()
stats = MyStats(qs)
return render(request, 'my_template.html', {'stats': stats})the stats result will be an enumerable similar to this one:
[
{'label': 'Total', 'values': [], 'value': 1216},
{'label': 'Total price', 'values': [], 'value': 323.16},
{'label': 'Per authority', 'values': [('Authority 1', 200), ('Authority 2', 9), ], 'value': None},
{'label': 'Per authority by price', 'values': [('Authority 1', 123.23), ('Authority 2', 42.12), ], 'value': None},
{'label': 'Per status', 'values': [('New', 200), ('Cancel', 0)], 'value': None},
{'label': 'Per status by price', 'values': [('New', '€ 32.01'), ('Cancel', '€ 44.23')], 'value': None},
{'label': 'Per year', 'values': [(2021, 582), (2022, 634)], 'value': None}
{'label': 'Per year by price', 'values': [(2021, 5.82), (2022, 6.34)], 'value': None}
{'label': 'Per price', 'values': [('> 5000', 1), ('> 1000', 29), ('> 500', 86), ('> 0', 305)], 'value': None}
]You can display this in your template using something like this (using bootstrap):
<div class='row'>
{% for s in stats %}
<div class='col-md-4 mb-5' style='max-height: 500px; overflow: auto;'>
<h4>{{ s.label }}</h4>
{% if s.values %}
<table class='table table-condensed table-striped small table-sm'>
{% for v in s.values %}
<tr>
<td>{{ v.0 }}</td>
<td>{{ v.1 }}</td>
</tr>
{% endfor %}
</table>
{% else %}
<b>{{ s.value }}</b>
{% endif %}
</div>
{% endfor %}
</div>from simple_stats import get_stats
STATS_CFG = cfg = [
{
'kind': 'query_aggregate_single',
'label': 'Total',
'field': 'id',
}, {
'kind': 'query_aggregate_single',
'label': 'Total price',
'method': 'sum',
'field': 'price',
}, {
'kind': 'query_aggregate',
'label': 'Per authority',
'field': 'pilot_authority__name',
}, {
'kind': 'query_aggregate',
'label': 'Per authority by price',
'field': 'pilot_authority__name',
'aggr_field': 'price',
'formatter': lambda v: "€ {}".format(v) if v else '-'
}, {
'kind': 'choice_aggregate',
'label': 'Per status',
'field': 'status',
'choices': models.STATUS_CHOICES,
}, {
'kind': 'choice_aggregate',
'label': 'Per status by price',
'field': 'status',
'aggr_field': 'price',
'choices': models.STATUS_CHOICES,
}, {
'kind': 'query_aggregate_date',
'label': 'Per year',
'field': 'created_on',
'what': 'year',
}, {
'kind': 'query_aggregate_date',
'label': 'Per year by price',
'field': 'created_on',
'what': 'year',
'aggr_field': 'price',
}, {
'kind': 'query_aggregate_buckets',
'label': 'Per price',
'field': 'price',
'buckets': [100_00, 50_00, 1_000, 500, 0]
}
]
def my_view(request):
qs = TestModel.objects.all()
stats = get_stats(qs, STATS_CFG)
return render(request, 'my_template.html', {'stats': stats})The stats will be an array of dictionaries, similar to the declarative example.
You can easily export these stats in xls using the xlwt (https://pypi.org/project/xlwt/) library and this function:
import xlwt
def create_xls_resp(stats, response):
context = self.get_context_data()
import xlwt
wb = xlwt.Workbook(encoding="utf-8")
for stat in stats:
ws = wb.add_sheet(stat["label"][:31])
ws.write(0,0,stat["label"], xlwt.easyxf('font: name Calibri, bold on', ))
if stat["value"]:
ws.write(0,1,stat["value"], xlwt.easyxf('font: name Calibri, bold on', ))
for i, val in enumerate(stat["values"], start=2):
for j,v in enumerate(val, start=0):
ws.write(i,j,v)
wb.save(response)Now you can call it like this from your view:
from django.http import HttpResponse
def my_export_view(request):
qs = TestModel.objects.all()
stats = get_stats(qs, STATS_CFG)
response = HttpResponse(content_type="application/ms-excel")
response["Content-Disposition"] = "attachment; filename=export.xls"
create_xls_resp(response)
return response- v.0.7.0: Add
query_aggregate_extract_dateandQueryAggregateExtractDateStat - v.0.6.0: Add tests!
- v.0.5.1: Allow adding a formatter for the values
- v.0.5.0: Add declarative API
- v.0.4.0: Allow the aggregate function to run on a different field using
aggr_field - v.0.3.1: Fix small bug with
choice_aggregate_with_null - v.0.3.0: Add
choice_aggregate_with_nulland throw if stat kind is not found - v.0.2.1: Fix small bug with column aliases
- v.0.2.0: Changed API; use
query_aggregate_datetimefor a datetime field andquery_aggregate_datefor a date field - v.0.1.0: Initial version