Django-tree

Fast and easy tree structures for Django, maintained inside the database.

django-tree solves the same problem as django-treebeard, django-tree-queries, django-mptt and django-treenode: storing and querying tree (hierarchy) structures with Django. It does it differently: you add a PathField to an ordinary model with a self-referencing ForeignKey, and the hierarchy is maintained by the database — not in your Python code. There is no model, manager or queryset to subclass; an optional TreeModelMixin only adds convenience methods (get_descendants(), get_ancestors(), …).

On PostgreSQL the path is maintained by a PL/pgSQL trigger, so bulk operations, QuerySet.update() and raw SQL all keep the tree consistent. On SQLite, MySQL and Oracle there is no such trigger, so the path is computed in Python on the ORM save cycle (save(), delete(), QuerySet.update(), bulk_create/bulk_update); writes that bypass the ORM (raw SQL) need a manual Model.rebuild_paths().

Table of contents

• Comparison
• Requirements
• Installation
• Quick start
• Usage
• Differences with MPTT and treebeard
• Contributing
• License

Comparison

[!NOTE] django-treebeard ships three interchangeable algorithms — MP (materialized path), NS (nested sets) and AL (adjacency list) — shown as separate columns.

Features

	django-tree	treebeard MP	treebeard NS	treebeard AL	django-mptt	django-tree-queries	django-treenode
Works on any Django database	🟢 PostgreSQL, SQLite, MySQL, Oracle	🟢	🟢	🟢	🟢	🟢	🟢
Drop-in (no model/manager subclassing)	🟢 add one field	🔴 subclass MP_Node	🔴 subclass NS_Node	🔴 subclass AL_Node	🔴 subclass MPTTModel	🔴 subclass TreeNode	🔴 subclass TreeNodeModel
Build & move with plain parent + save()	🟢	🔴 API	🔴 API	🔴 API	🟢	🟢	🟢
Several independent trees per model	🟢 multiple PathFields	🔴 one hierarchy	🔴 one hierarchy	🔴 one hierarchy	🔴 one hierarchy	🔴 one hierarchy	🔴 one hierarchy
Maximum number of siblings	🟢 unlimited	🟠 1.7 M	🟢 1 B	🟢 unlimited	🟢 1 B	🟢 unlimited	🟢 2.1 B
Tree kept correct by the database	🟢 PostgreSQL: SQL trigger

🔴 SQLite, MySQL, Oracle: in Python | 🔴 in Python | 🔴 in Python | 🔴 in Python | 🔴 in Python | 🟢 FK only, nothing denormalized | 🔴 in Python + cache | | Survives bulk writes / update() / raw SQL | 🟢 PostgreSQL

🟡 SQLite, MySQL, Oracle: bulk/update() yes, raw SQL no | 🔴 Python API only | 🔴 Python API only | 🔴 Python API only | 🔴 | 🟢 | 🔴 manual resync | | Tree filters as composable ORM lookups | 🟢 __descendant_of, __child_of | 🟡 manager methods | 🟡 manager methods | 🟡 manager methods | 🟡 manager methods | 🟡 with_tree_fields() | 🟡 cached properties | | Admin integration | 🔴 form field only | 🟢 drag-and-drop | 🟢 drag-and-drop | 🟢 drag-and-drop | 🟢 drag-and-drop | 🟢 cut/paste | 🟢 | | Template tags to render trees | 🔴 | 🟡 | 🟡 | 🟡 | 🟢 {% recursetree %} | 🟢 {% recursetree %} | 🟡 | | Production-ready | 🟢 | 🟢 | 🟢 | 🟢 | 🟡 works, unmaintained | 🟢 | 🟢 |

🟢 yes / good · 🟡 partial or depends on the variant · 🔴 no / poor.

Maximum number of siblings counts how many children a single parent can hold before the encoding runs out (django-tree uses fractional indexing, so it never does; treebeard MP caps at alphabetsteplen = 36⁴; the nested-set ones at the lft/rgt PositiveIntegerField span, ≈1 B; django-treenode at its PositiveIntegerField order, ≈2.1 B): 🟢 over 100 M · 🟠 over 1 M · 🔴 otherwise.

Performance

Absolute latency and disk usage measured on a tree of 3905 rows. Every test runs on every implementation: those lacking a native method use a simple, unofficial ORM equivalent, so the whole grid is comparable. Each cell shows the measurement; below it, the rank in that row (#n) and a marker.

	django-tree	treebeard MP	treebeard NS	treebeard AL	django-mptt	django-tree-queries	django-treenode
Reads · best	77 µs

🟢 #6 | 0.5 µs

🟢 #1 👑 | 0.7 µs

🟢 #3 | 10 µs

🟢 #5 | 1.7 µs

🟢 #4 | 75 µs

🟢 #6 | 0.5 µs

🟢 #1 👑 | | Reads · typical | 511 µs

🟢 #4 | 250 µs

🟢 #1 👑 | 393 µs

🟢 #3 | 1.6 ms

🟢 #6 | 300 µs

🟢 #2 | 1.1 ms

🟢 #5 | 1.9 ms

🟢 #7 | | Reads · worst | 72 ms

🟠 #1 👑 | 344 ms

🔴 #3 | 518 ms

🔴 #4 | 853 ms

🔴 #6 | 118 ms

🔴 #2 | 627 ms

🔴 #5 | 5 min

💩 #7 | | Writes · best | 441 µs

🟢 #6 | 235 µs

🟢 #4 | 205 µs

🟢 #3 | 193 µs

🟢 #2 | 307 µs

🟢 #5 | 183 µs

🟢 #1 👑 | 390 ms

🔴 #7 | | Writes · typical | 2.8 ms

🟢 #3 | 5.7 ms

🟠 #4 | 6.1 ms

🟠 #5 | 969 µs

🟢 #1 👑 | 13 ms

🟠 #6 | 1.0 ms

🟢 #2 | 837 ms

🔴 #7 | | Writes · worst | 2.4 s

💩 #3 | 9.0 s

💩 #4 | 21.8 s

💩 #6 | 926 ms

🔴 #2 | 19.0 s

💩 #5 | 829 ms

🔴 #1 👑 | 25 min

💩 #7 | | Storage | 0.91 MB

🟢 #5 | 0.97 MB

🟢 #6 | 0.79 MB

🟢 #3 | 0.57 MB

🟢 #1 👑 | 0.85 MB

🟢 #4 | 0.57 MB

🟢 #1 👑 | 0.98 MB

🟢 #6 |

Two results within 5 % share a rank. Markers use the same thresholds for reads and writes:

• 👑 best of the row — shown after the rank.
• 🟢 fine · 🟠 laggy (> 3 ms) · 🔴 very laggy (> 100 ms) · 💩 horrible (> 1 s).

See the full benchmark for every test.

In short:

• django-tree keeps the tree correct in the database itself, so on PostgreSQL bulk operations, update() and raw SQL stay safe, with balanced reads and writes — at the cost of being without admin drag-and-drop or tree-rendering template tags yet. On SQLite, MySQL and Oracle the path is maintained in Python on the ORM save cycle instead (raw SQL then needs a manual rebuild).
• treebeard offers three algorithms with the same brittle Python API and no database constraint: MP reads fast, NS writes slowly like MPTT, AL writes fast and is tiny on disk but some reads are catastrophic.
• MPTT stores the tree safely but writes get very slow on large or write-heavy tables and need periodic rebuilds. No longer maintained.
• tree-queries derives the hierarchy from a plain parent FK with recursive CTEs, so nothing can get out of sync and writes and storage are the cheapest and it runs on most databases — at the cost of slow, sometimes very slow, reads.
• treenode keeps denormalized caches of the whole tree, but every write rebuilds them — by far the slowest writes here — and bulk writes need a manual resync.

Requirements

• PostgreSQL 12+, SQLite, MySQL or Oracle 19c+. On PostgreSQL the hierarchy is maintained by a PL/pgSQL trigger using only standard, long-standing features (also under raw SQL; CI runs on PostgreSQL 16); on SQLite, MySQL and Oracle it is maintained in Python on the ORM save cycle, so raw-SQL writes need a manual Model.rebuild_paths(). MySQL stores the path as VARBINARY(768) and Oracle as RAW(2000), capping tree depth.
• Django 4.2+
• Python 3.10+

Installation

Install the package from PyPI:

pip install django-tree

Then add 'tree' to your INSTALLED_APPS.

Quick start

Add a PathField to a model that has a ForeignKey('self') — typically named parent — and add TreeModelMixin for the convenience query methods (get_children(), get_descendants(), …). The mixin order is not important, as its methods do not clash with Django.

from django.db.models import Model, CharField, ForeignKey, BooleanField
from tree.fields import PathField
from tree.models import TreeModelMixin

class YourModel(Model, TreeModelMixin):
    name = CharField(max_length=30)
    parent = ForeignKey('self', null=True, blank=True)
    path = PathField()
    public = BooleanField(default=False)

    class Meta:
        ordering = ['path']
        # Recommended: speeds up child/sibling/level queries.
        indexes = [*PathField.get_indexes('yourmodel', 'path')]

Then create a migration that depends on the latest django-tree migration and adds a CreateTreeTrigger operation — this installs the SQL trigger that keeps path up to date automatically:

from django.db import migrations
from tree.operations import CreateTreeTrigger

class Migration(migrations.Migration):
    dependencies = [
        ('tree', '0003_tree_functions'),
    ]

    operations = [
        CreateTreeTrigger('your_app.YourModel'),
    ]

Once the trigger exists, the field maintains itself — building and moving nodes is just parent + save():

root = YourModel.objects.create(name='root')
child = YourModel.objects.create(name='child', parent=root)
root.get_descendants()   # QuerySet of every node under `root`
child.get_ancestors()    # QuerySet from the root down to `child`'s parent

That's the whole setup. See Usage for the full API, custom child ordering, and adding the trigger to a table that already holds data.

If you have multiple PathFields on the same model, pass the field name as the path_field argument of the method you call. If your self-referencing key is not named parent, pass its name to the parent_field argument of CreateTreeTrigger.

Usage

PathField is automatically filled thanks to CreateTreeTrigger, you don’t need to set, modify, or even see its value once it is installed. But you can use the Path object it stores or the more convenient TreeModelMixin to get tree information about the current instance, or make complex queries on the whole tree structure. Example to show you most of the possibilities:

obj = YourModel.objects.all()[0]
obj.path.get_level()
obj.get_level()  # Shortcut for the previous method, if you use
                    # `TreeModelMixin`. Same for other object methods below.
obj.is_root()
obj.is_leaf()
obj.get_children()
obj.get_children().filter(public=True)
obj.get_ancestors()
obj.get_ancestors(include_self=True)
obj.get_descendants(include_self=True)
obj.get_siblings()
obj.get_prev_sibling()  # Fetches the previous sibling.
obj.get_next_sibling()
# Same as `get_prev_sibling`, except that we get the first public one.
obj.get_prev_siblings().filter(public=True).first()
other = YourModel.objects.all()[1]
obj.is_ancestor_of(other)
obj.is_descendant_of(other, include_self=True)
YourModel.objects.filter_roots()

#
# Advanced usage
# Use the following methods only if you understand exactly what they mean.
#

YourModel.rebuild_paths()  # Rebuilds all paths of this field, useful only
                            # if something is broken, which shouldn’t happen.
YourModel.disable_tree_trigger()  # Disables the SQL trigger.
YourModel.enable_tree_trigger()   # Restores the SQL trigger.
with YourModel.disabled_tree_trigger():
    # What happens inside this context manager is ignored
    # by the SQL trigger.
    # The trigger is restored after that, even if an error occurred.
    pass

[!NOTE] On SQLite, MySQL and Oracle there is no SQL trigger: disable_tree_trigger() / enable_tree_trigger() toggle the Python maintenance instead, and rebuild_paths() is also how you resync the tree after a write that bypasses the ORM (raw SQL, cursor.execute, …), which those backends cannot intercept. On PostgreSQL the trigger keeps everything consistent on its own, so you never need rebuild_paths() in normal use.

There is also a bunch of less useful lookups and transforms available. They will be documented with examples in the future.

Ordering children

By default the children of a same parent are ordered by primary key. Pass order_by to PathField to order them differently — for instance by an explicit position field, falling back to the name:

from django.db.models import (
    Model, CharField, ForeignKey, IntegerField, BooleanField)
from tree.fields import PathField
from tree.models import TreeModelMixin

class YourModel(Model, TreeModelMixin):
    name = CharField(max_length=30)
    parent = ForeignKey('self', null=True, blank=True)
    position = IntegerField(default=1)
    path = PathField(order_by=['position', 'name'])
    public = BooleanField(default=False)

    class Meta:
        ordering = ['path']
        indexes = [*PathField.get_indexes('yourmodel', 'path')]

And the corresponding migration:

from django.db import models, migrations
from tree.operations import CreateTreeTrigger

class Migration(migrations.Migration):
    dependencies = [
        ('tree', '0003_tree_functions'),
    ]

    operations = [
        migrations.AddField('YourModel', 'position',
                            models.IntegerField(default=1)),
        CreateTreeTrigger('YourModel'),
    ]

Adding the trigger to a table that already has data

PathField is always nullable, so existing rows simply start with a NULL path. Create the trigger, then rebuild the paths from the parent FKs:

```python from django.db import migration