Use Postgres' generate_series to create sequences with Django's ORM
Project description
django-generate-series
Use Postgres' generate_series to create sequences with Django's ORM
https://django-generate-series.readthedocs.io/
Goals
When using Postgres, the set-returning functions allow us to easily create sequences of numbers, dates, datetimes, etc. Unfortunately, this functionality is not currently available within the Django ORM.
This project makes it possible to create such sequences, which can then be used with Django QuerySets. For instance, assuming you have an Order model, you can create a set of sequential dates and then annotate each with the number of orders placed on that date. This will ensure you have no date gaps in the resulting QuerySet. To get the same effect without this package, additional post-processing of the QuerySet with Python would be required.
Terminology
Although this packages is named django-generate-series based on Postgres' generate_series
set-returning function, mathematically we are creating a sequence rather than a series.
-
sequence: Formally, "a list of objects (or events) which have been ordered in a sequential fashion; such that each member either comes before, or after, every other member."
In django-generate-series, we can generate sequences of integers, decimals, dates, datetimes, as well as the equivalent ranges of each of these types.
-
term: The nth item in the sequence, where 'nth' can be found using the id of the model instance.
This is the name of the field in the model which contains the term value.
API
The package includes a generate_series
function from which you can create your own series-generating QuerySets. The field type passed into the function as output_field
determines the resulting type of series that can be created. (Thanks, @adamchainz for the format suggestion!)
generate_series arguments
- start - The value at which the sequence should begin (required)
- stop - The value at which the sequence should end. For range types, this is the lower value of the final term (required)
- step - How many values to step from one term to the next. For range types, this is the step from the lower value of one term to the next. (required for non-integer types)
- span - For range types other than date and datetime, this determines the span of the lower value of a term and its upper value (optional, defaults to 1 if neeeded in the query)
- output_field - A django model field class, one of BigIntegerField, IntegerField, DecimalField, DateField, DateTimeField, BigIntegerRangeField, IntegerRangeField, DecimalRangeField, DateRangeField, or DateTimeRangeField. (required)
- include_id - If set to True, an auto-incrementing
id
field will be added to the QuerySet. - max_digits - For decimal types, specifies the maximum digits
- decimal_places - For decimal types, specifies the number of decimal places
- default_bounds - In Django 4.1+, allows specifying bounds for list and tuple inputs. See Django docs
Basic Examples
# Create a bunch of sequential integers
integer_sequence_queryset = generate_series(
0, 1000, output_field=models.IntegerField,
)
for item in integer_sequence_queryset:
print(item.term)
Result:
term
----
0
1
2
3
4
5
6
7
8
9
10
...
1000
# Create a sequence of dates from now until a year from now
now = timezone.now().date()
later = (now + timezone.timedelta(days=365))
date_sequence_queryset = generate_series(
now, later, "1 days", output_field=models.DateField,
)
for item in date_sequence_queryset:
print(item.term)
Result:
term
----
2022-04-27
2022-04-28
2022-04-29
2022-04-30
2022-05-01
2022-05-02
2022-05-03
...
2023-04-27
Note: See the docs and the example project in the tests directory for further examples of usage.
Usage with partial
If you often need sequences of a given field type or with certain args, you can use partial.
Example with default include_id
and output_field
values:
from functools import partial
int_and_id_series = partial(generate_series, include_id=True, output_field=BigIntegerField)
qs = int_and_id_series(1, 100)
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file django_generate_series-0.5.0.tar.gz
.
File metadata
- Download URL: django_generate_series-0.5.0.tar.gz
- Upload date:
- Size: 13.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.2.2 CPython/3.10.6 Linux/5.15.0-56-generic
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 8cced6473ba75aed5e1e2ecd6f5426d11d33926e86d2630dabe9c424b7a6da8a |
|
MD5 | 7dd47ebb1d56ff29cbb2fe9bf317b9f2 |
|
BLAKE2b-256 | d35248f0d808f22742e91f13f36292709b070bd4ee5948db80b5ef8489c31164 |
File details
Details for the file django_generate_series-0.5.0-py3-none-any.whl
.
File metadata
- Download URL: django_generate_series-0.5.0-py3-none-any.whl
- Upload date:
- Size: 11.4 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.2.2 CPython/3.10.6 Linux/5.15.0-56-generic
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 54e33e5aba69be75f591bda970421dee9f1c5feeb84c20d8cee634bcc0e249bc |
|
MD5 | 256c206220fe67b5ea37ac7ee6a137b1 |
|
BLAKE2b-256 | 7fa6e046d514139eec2b0d534a499a5bee5eb735e45b528113bf5cd7cdf87a2d |