
Security News
Browserslist-rs Gets Major Refactor, Cutting Binary Size by Over 1MB
Browserslist-rs now uses static data to reduce binary size by over 1MB, improving memory use and performance for Rust-based frontend tools.
.. image:: https://github.com/matthiask/django-tree-queries/actions/workflows/test.yml/badge.svg :target: https://github.com/matthiask/django-tree-queries/ :alt: CI Status
Query Django model trees using adjacency lists and recursive common
table expressions. Supports PostgreSQL, sqlite3 (3.8.3 or higher) and
MariaDB (10.2.2 or higher) and MySQL (8.0 or higher, if running without
ONLY_FULL_GROUP_BY
).
Supports Django 3.2 or better, Python 3.8 or better. See the GitHub actions build for more details.
"parent"
at the moment (but
why would you want to name it differently?)tree_depth
, tree_path
and tree_ordering
. The names cannot
be changed. tree_depth
is an integer, tree_path
an array of
primary keys and tree_ordering
an array of values used for
ordering nodes within their siblings. Note that the contents of the
tree_path
and tree_ordering
are subject to change. You shouldn't rely
on their contents.TreeNode
abstract model class
has some protection against this.tree_path
and tree_ordering
upfront.Here's a blog post offering some additional insight (hopefully) into the
reasons for django-tree-queries' existence <https://406.ch/writing/django-tree-queries/>
_.
django-tree-queries
using pip.tree_queries.models.TreeNode
or build your own queryset
and/or manager using tree_queries.query.TreeQuerySet
. The
TreeNode
abstract model already contains a parent
foreign key
for your convenience and also uses model validation to protect against
loops.with_tree_fields()
queryset method if you require the
additional fields respectively the CTE.order_siblings_by("field_name")
queryset method if you want to
order tree siblings by a specific model field. Note that Django's standard
order_by()
method isn't supported -- nodes are returned according to the
depth-first search algorithm <https://en.wikipedia.org/wiki/Depth-first_search>
__.tree_filter()
and tree_exclude()
for better performance when
working with large tables - these filter the base table before building
the tree structure.tree_fields()
to aggregate ancestor field values into arrays.TreeQuerySet.as_manager(with_tree_fields=True)
if you want to add
tree fields to queries by default.test suite <https://github.com/matthiask/django-tree-queries/blob/main/tests/testapp/test_queries.py>
_
for additional instructions and usage examples, or check the recipes below.Basic models
The following two examples both extend the ``TreeNode`` which offers a few
agreeable utilities and a model validation method that prevents loops in the
tree structure. The common table expression could be hardened against such
loops but this would involve a performance hit which we don't want -- this is a
documented limitation (non-goal) of the library after all.
Basic tree node
---------------
.. code-block:: python
from tree_queries.models import TreeNode
class Node(TreeNode):
name = models.CharField(max_length=100)
Tree node with ordering among siblings
--------------------------------------
Nodes with the same parent may be ordered among themselves. The default is to
order siblings by their primary key but that's not always very useful.
.. code-block:: python
from tree_queries.models import TreeNode
class Node(TreeNode):
name = models.CharField(max_length=100)
position = models.PositiveIntegerField(default=0)
class Meta:
ordering = ["position"]
Add custom methods to queryset
------------------------------
.. code-block:: python
from tree_queries.models import TreeNode
from tree_queries.query import TreeQuerySet
class NodeQuerySet(TreeQuerySet):
def active(self):
return self.filter(is_active=True)
class Node(TreeNode):
is_active = models.BooleanField(default=True)
objects = NodeQuerySet.as_manager()
Querying the tree
All examples assume the Node
class from above.
.. code-block:: python
# Basic usage, disregards the tree structure completely.
nodes = Node.objects.all()
# Fetch nodes in depth-first search order. All nodes will have the
# tree_path, tree_ordering and tree_depth attributes.
nodes = Node.objects.with_tree_fields()
# Fetch any node.
node = Node.objects.order_by("?").first()
# Fetch direct children and include tree fields. (The parent ForeignKey
# specifies related_name="children")
children = node.children.with_tree_fields()
# Fetch all ancestors starting from the root.
ancestors = node.ancestors()
# Fetch all ancestors including self, starting from the root.
ancestors_including_self = node.ancestors(include_self=True)
# Fetch all ancestors starting with the node itself.
ancestry = node.ancestors(include_self=True).reverse()
# Fetch all descendants in depth-first search order, including self.
descendants = node.descendants(include_self=True)
# Temporarily override the ordering by siblings.
nodes = Node.objects.order_siblings_by("id")
# Revert to a queryset without tree fields (improves performance).
nodes = Node.objects.with_tree_fields().without_tree_fields()
IMPORTANT: For large tables, always use tree_filter()
or tree_exclude()
to limit which nodes are processed by the recursive CTE. Without these filters,
the database evaluates the entire table, which can be extremely slow.
.. code-block:: python
# Get a specific tree from a forest by filtering on root category
product_tree = Node.objects.with_tree_fields().tree_filter(category="products")
# Get organizational chart for a specific department
engineering_tree = Node.objects.with_tree_fields().tree_filter(department="engineering")
# Exclude entire trees/sections you don't need
content_trees = Node.objects.with_tree_fields().tree_exclude(category="archived")
# Chain multiple tree filters for more specific trees
recent_products = (Node.objects.with_tree_fields()
.tree_filter(category="products")
.tree_filter(created_date__gte=datetime.date.today()))
# Get descendants within a filtered tree subset
product_descendants = (Node.objects.with_tree_fields()
.tree_filter(category="products")
.descendants(some_product_node))
# Filter by site/tenant in multi-tenant applications
site_content = Node.objects.with_tree_fields().tree_filter(site_id=request.site.id)
Performance note: tree_filter()
and tree_exclude()
filter the base table
before the recursive CTE processes relationships, dramatically improving performance
for large datasets compared to using regular filter()
after with_tree_fields()
.
Best used for selecting complete trees or tree sections rather than scattered nodes.
Note that the tree queryset doesn't support all types of queries Django supports. For example, updating all descendants directly isn't supported. The reason for that is that the recursive CTE isn't added to the UPDATE query correctly. Workarounds often include moving the tree query into a subquery:
.. code-block:: python
# Doesn't work:
node.descendants().update(is_active=False)
# Use this workaround instead:
Node.objects.filter(pk__in=node.descendants()).update(is_active=False)
Nobody wants breadth-first search but if you still want it you can achieve it as follows:
.. code-block:: python
nodes = Node.objects.with_tree_fields().extra(
order_by=["__tree.tree_depth", "__tree.tree_ordering"]
)
If you only want nodes from the top two levels:
.. code-block:: python
nodes = Node.objects.with_tree_fields().extra(
where=["__tree.tree_depth <= %s"],
params=[1],
)
Use tree_fields()
to aggregate values from ancestor nodes into arrays. This is
useful for collecting paths, permissions, categories, or any field that should be
inherited down the tree hierarchy.
.. code-block:: python
# Aggregate names from all ancestors into an array
nodes = Node.objects.with_tree_fields().tree_fields(
tree_names="name",
)
# Each node now has a tree_names attribute: ['root', 'parent', 'current']
# Aggregate multiple fields
nodes = Node.objects.with_tree_fields().tree_fields(
tree_names="name",
tree_categories="category",
tree_permissions="permission_level",
)
# Build a full path string from ancestor names
nodes = Node.objects.with_tree_fields().tree_fields(tree_names="name")
for node in nodes:
full_path = " > ".join(node.tree_names) # "Root > Section > Subsection"
# Combine with tree filtering for better performance
active_nodes = (Node.objects.with_tree_fields()
.tree_filter(is_active=True)
.tree_fields(tree_names="name"))
The aggregated fields contain values from all ancestors (root to current node) in hierarchical order, including the current node itself.
Form fields
django-tree-queries ships a model field and some form fields which augment the
default foreign key field and the choice fields with a version where the tree
structure is visualized using dashes etc. Those fields are
``tree_queries.fields.TreeNodeForeignKey``,
``tree_queries.forms.TreeNodeChoiceField``,
``tree_queries.forms.TreeNodeMultipleChoiceField``.
Templates
~~~~~~~~~
django-tree-queries includes template tags to help render tree structures in
Django templates. These template tags are designed to work efficiently with
tree querysets and respect queryset boundaries.
Setup
-----
Add ``tree_queries`` to your ``INSTALLED_APPS`` setting:
.. code-block:: python
INSTALLED_APPS = [
# ... other apps
'tree_queries',
]
Then load the template tags in your template:
.. code-block:: html
{% load tree_queries %}
tree_info filter
----------------
The ``tree_info`` filter provides detailed information about each node's
position in the tree structure. It's useful when you need fine control over
the tree rendering.
.. code-block:: html
{% load tree_queries %}
<ul>
{% for node, structure in nodes|tree_info %}
{% if structure.new_level %}<ul><li>{% else %}</li><li>{% endif %}
{{ node.name }}
{% for level in structure.closed_levels %}</li></ul>{% endfor %}
{% endfor %}
</ul>
The filter returns tuples of ``(node, structure_info)`` where ``structure_info``
contains:
- ``new_level``: ``True`` if this node starts a new level, ``False`` otherwise
- ``closed_levels``: List of levels that close after this node
- ``ancestors``: List of ancestor node representations from root to immediate parent
Example showing ancestor information:
.. code-block:: html
{% for node, structure in nodes|tree_info %}
{{ node.name }}
{% if structure.ancestors %}
(Path: {% for ancestor in structure.ancestors %}{{ ancestor }}{% if not forloop.last %} > {% endif %}{% endfor %})
{% endif %}
{% endfor %}
recursetree tag
---------------
The ``recursetree`` tag provides recursive rendering similar to django-mptt's
``recursetree`` tag, but optimized for django-tree-queries. It only considers
nodes within the provided queryset and doesn't make additional database queries.
Basic usage:
.. code-block:: html
{% load tree_queries %}
<ul>
{% recursetree nodes %}
<li>
{{ node.name }}
{% if children %}
<ul>{{ children }}</ul>
{% endif %}
</li>
{% endrecursetree %}
</ul>
The ``recursetree`` tag provides these context variables within the template:
- ``node``: The current tree node
- ``children``: Rendered HTML of child nodes (from the queryset)
- ``is_leaf``: ``True`` if the node has no children in the queryset
Using ``is_leaf`` for conditional rendering:
.. code-block:: html
{% recursetree nodes %}
<div class="{% if is_leaf %}leaf-node{% else %}branch-node{% endif %}">
<span class="node-name">{{ node.name }}</span>
{% if children %}
<div class="children">{{ children }}</div>
{% elif is_leaf %}
<span class="leaf-indicator">🍃</span>
{% endif %}
</div>
{% endrecursetree %}
Advanced example with depth information:
.. code-block:: html
{% recursetree nodes %}
<div class="node depth-{{ node.tree_depth }}"
data-id="{{ node.pk }}"
data-has-children="{{ children|yesno:'true,false' }}">
<h{{ node.tree_depth|add:1 }}>{{ node.name }}</h{{ node.tree_depth|add:1 }}>
{% if children %}
<div class="node-children">{{ children }}</div>
{% endif %}
</div>
{% endrecursetree %}
Working with limited querysets
-------------------------------
Both template tags respect queryset boundaries and work efficiently with
filtered or limited querysets:
.. code-block:: python
# Only nodes up to depth 2
limited_nodes = Node.objects.with_tree_fields().extra(
where=["__tree.tree_depth <= %s"], params=[2]
)
# Only specific branches
branch_nodes = Node.objects.descendants(some_node, include_self=True)
When using these limited querysets:
- ``recursetree`` will only render nodes from the queryset
- ``is_leaf`` reflects whether nodes have children *in the queryset*, not in the full tree
- No additional database queries are made
- Nodes whose parents aren't in the queryset are treated as root nodes
Example with depth-limited queryset:
.. code-block:: html
<!-- Template -->
{% recursetree limited_nodes %}
<li>
{{ node.name }}
{% if is_leaf %}
<small>(leaf in limited view)</small>
{% endif %}
{{ children }}
</li>
{% endrecursetree %}
This is particularly useful for creating expandable tree interfaces or
rendering only portions of large trees for performance.
FAQs
Tree queries with explicit opt-in, without configurability
We found that django-tree-queries demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 2 open source maintainers collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Security News
Browserslist-rs now uses static data to reduce binary size by over 1MB, improving memory use and performance for Rust-based frontend tools.
Research
Security News
Eight new malicious Firefox extensions impersonate games, steal OAuth tokens, hijack sessions, and exploit browser permissions to spy on users.
Security News
The official Go SDK for the Model Context Protocol is in development, with a stable, production-ready release expected by August 2025.