django-tree-queries¶
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.
Features and limitations¶
Supports only integer and UUID primary keys (for now).
Allows specifying ordering among siblings.
Uses the correct definition of depth, where root nodes have a depth of zero.
The parent foreign key must be named
"parent"at the moment (but why would you want to name it differently?)The fields added by the common table expression always are
tree_depth,tree_pathandtree_ordering. The names cannot be changed.tree_depthis an integer,tree_pathan array of primary keys representing the path from the root to the current node (including the current node itself), andtree_orderingan array of values used for ordering nodes within their siblings at each level of the tree hierarchy. Note that the contents of thetree_pathandtree_orderingare subject to change. You shouldn’t rely on their contents.Besides adding the fields mentioned above the package only adds queryset methods for ordering siblings and filtering ancestors and descendants. Other features may be useful, but will not be added to the package just because it’s possible to do so.
Little code, and relatively simple when compared to other tree management solutions for Django. No redundant values so the only way to end up with corrupt data is by introducing a loop in the tree structure (making it a graph). The
TreeNodeabstract model class has some protection against this.Supports only trees with max. 50 levels on MySQL/MariaDB, since those databases do not support arrays and require us to provide a maximum length for the
tree_pathandtree_orderingupfront.Performance optimization: The library automatically detects simple cases (single field ordering, no tree filters, no custom tree fields) and uses an optimized CTE that avoids creating a rank table, significantly improving performance for basic tree queries.
Here’s a blog post offering some additional insight (hopefully) into the reasons for django-tree-queries’ existence.
Usage¶
Install
django-tree-queriesusing pip.Extend
tree_queries.models.TreeNodeor build your own queryset and/or manager usingtree_queries.query.TreeQuerySet. TheTreeNodeabstract model already contains aparentforeign key for your convenience and also uses model validation to protect against loops.Call the
with_tree_fields()queryset method if you require the additional fields respectively the CTE.Call the
order_siblings_by("field_name")queryset method if you want to order tree siblings by a specific model field. Note that Django’s standardorder_by()method isn’t supported – nodes are returned according to the depth-first search algorithm.Use
tree_filter()andtree_exclude()for better performance when working with large tables - these filter the base table before building the tree structure.Use
tree_fields()to aggregate ancestor field values into arrays.Create a manager using
TreeQuerySet.as_manager(with_tree_fields=True)if you want to add tree fields to queries by default.Until documentation is more complete I’ll have to refer you to the test suite for additional instructions and usage examples, or check the recipes below.
Recipes¶
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¶
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.
Manual position management:
from tree_queries.models import TreeNode
class Node(TreeNode):
name = models.CharField(max_length=100)
position = models.PositiveIntegerField(default=0)
class Meta:
ordering = ["position"]
Automatic position management:
For automatic position management, use OrderableTreeNode which automatically
assigns sequential position values to new nodes:
from tree_queries.models import OrderableTreeNode
class Category(OrderableTreeNode):
name = models.CharField(max_length=100)
# position field and ordering are inherited from OrderableTreeNode
When creating new nodes without an explicit position, OrderableTreeNode
automatically assigns a position value 10 units higher than the maximum position
among siblings. The increment of 10 (rather than 1) makes it explicit that the
position values themselves have no inherent meaning - they are purely for relative
ordering, not a sibling counter or index.
If you need to customize the Meta class (e.g., to add verbose names or additional
ordering fields), inherit from OrderableTreeNode.Meta:
from tree_queries.models import OrderableTreeNode
class Category(OrderableTreeNode):
name = models.CharField(max_length=100)
class Meta(OrderableTreeNode.Meta):
verbose_name = "category"
verbose_name_plural = "categories"
# ordering = ["position"] is inherited from OrderableTreeNode.Meta
# Create nodes - positions are assigned automatically
root = Category.objects.create(name="Root") # position=10
child1 = Category.objects.create(name="Child 1", parent=root) # position=10
child2 = Category.objects.create(name="Child 2", parent=root) # position=20
child3 = Category.objects.create(name="Child 3", parent=root) # position=30
# Manual reordering is still possible
child3.position = 15 # Move between child1 and child2
child3.save()
This approach is identical to the pattern used in feincms3’s AbstractPage.
Add custom methods to queryset¶
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.
Basic usage¶
# 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()
Understanding tree fields¶
When using with_tree_fields(), each node gets three additional attributes:
``tree_depth``: An integer representing the depth of the node in the tree (root nodes have depth 0)
``tree_path``: An array containing the primary keys of all ancestors plus the current node itself, representing the path from root to current node
``tree_ordering``: An array containing the ordering/ranking values used for sibling ordering at each level of the tree hierarchy
The key difference between tree_path and tree_ordering:
# Example tree structure:
# Root (pk=1, order=0)
# ├── Child A (pk=2, order=10)
# │ └── Grandchild (pk=4, order=5)
# └── Child B (pk=3, order=20)
# For the Grandchild node:
grandchild = Node.objects.with_tree_fields().get(pk=4)
# tree_path shows the route through primary keys: Root -> Child A -> Grandchild
assert grandchild.tree_path == [1, 2, 4] # [root.pk, child_a.pk, grandchild.pk]
# tree_ordering shows ordering values at each level: Root's order, Child A's order, Grandchild's order
assert grandchild.tree_ordering == [0, 10, 5] # [root.order, child_a.order, grandchild.order]
Important note: When not using an explicit ordering (like a position
field), siblings are ordered by their primary key by default. This means
tree_path and tree_ordering will contain the same values. While this
may be fine for your use case consider adding an explicit ordering field:
class Node(TreeNode):
id = models.UUIDField(primary_key=True, default=uuid.uuid4)
name = models.CharField(max_length=100)
position = models.PositiveIntegerField(default=0)
class Meta:
ordering = ["position"]
When are tree fields available?¶
Tree fields (tree_depth, tree_path, tree_ordering) are only available
on objects returned by queries that use with_tree_fields() or a manager
configured with with_tree_fields=True. They are NOT available after
Model.objects.create(), instance.save(), or instance.refresh_from_db().
Why? Tree fields are calculated by the recursive CTE at query time and are not stored in the database. They only exist as annotations on the queryset results.
# Tree fields are NOT available after creation
node = Node.objects.create(name="New Node", parent=root)
# node.tree_depth # AttributeError: 'Node' object has no attribute 'tree_depth'
# refresh_from_db() only updates database fields, not tree fields
node.refresh_from_db()
# node.tree_depth # Still AttributeError
# To get tree fields, re-query the object with with_tree_fields()
node = Node.objects.with_tree_fields().get(pk=node.pk)
print(node.tree_depth) # Now it works! e.g., 1
# Or use a manager with tree fields enabled by default
class Node(TreeNode):
name = models.CharField(max_length=100)
objects = TreeQuerySet.as_manager(with_tree_fields=True)
# Now tree fields are available on all queries automatically
node = Node.objects.get(pk=some_pk)
print(node.tree_depth) # Works!
# But still not after create/save/refresh_from_db
new_node = Node.objects.create(name="Another")
# new_node.tree_depth # Still AttributeError - need to re-query
Common pattern when creating nodes:
# Create a new node
new_node = Node.objects.create(name="New Child", parent=parent_node)
# Re-query to get tree fields if you need them
new_node = Node.objects.with_tree_fields().get(pk=new_node.pk)
# Now you can access tree fields
print(f"Depth: {new_node.tree_depth}")
print(f"Path: {new_node.tree_path}")
Filtering tree subsets¶
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.
# 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.
Limitations and workarounds¶
The tree queryset doesn’t support all types of queries Django supports.
UPDATE queries on tree querysets¶
Updating all descendants directly isn’t supported because the recursive CTE isn’t added to the UPDATE query correctly. Use a subquery workaround instead:
# Doesn't work:
node.descendants().update(is_active=False)
# Use this workaround instead:
Node.objects.filter(pk__in=node.descendants()).update(is_active=False)
Union, intersection, and difference operations¶
Set operations like union(), intersection(), and difference() are not
currently supported with tree querysets due to how Django passes the elide_empty
parameter. Attempting to use these operations will result in errors.
# This doesn't work:
qs1 = Node.objects.with_tree_fields().filter(name__startswith="A")
qs2 = Node.objects.with_tree_fields().filter(name__startswith="B")
combined = qs1.union(qs2) # Will raise an error
Workaround: Use regular Django querysets without tree fields, then add tree fields after the set operation:
# Perform the set operation without tree fields
qs1 = Node.objects.filter(name__startswith="A")
qs2 = Node.objects.filter(name__startswith="B")
combined_ids = qs1.union(qs2).values_list("pk", flat=True)
# Then fetch with tree fields
result = Node.objects.with_tree_fields().filter(pk__in=combined_ids)
For more details and discussion about adding support for these operations, see GitHub issue #55.
Limiting tree depth¶
To limit the depth of the tree returned by a query, use .extra() with a
WHERE clause on the tree_depth field:
# Get only nodes up to depth 2 (root is depth 0)
nodes = Node.objects.with_tree_fields().extra(
where=["__tree.tree_depth <= %s"],
params=[2],
)
# Get nodes within a depth range
nodes = Node.objects.with_tree_fields().extra(
where=["__tree.tree_depth BETWEEN %s AND %s"],
params=[1, 3], # Only depths 1, 2, and 3
)
Limiting children per node¶
To enforce a maximum number of children per node, implement validation in your
model’s clean() method:
from django.core.exceptions import ValidationError
class Node(TreeNode):
def clean(self):
super().clean()
max_children = 10
# Check if this would exceed the limit
if self.parent_id:
sibling_count = (
Node.objects
.filter(parent_id=self.parent_id)
.exclude(pk=self.pk)
.count()
)
if sibling_count >= max_children:
raise ValidationError(
f"Parent already has {sibling_count} children "
f"(maximum {max_children})"
)
Checking tree depth in code¶
If you need to validate or check depth without tree fields:
# Check depth by counting ancestors
depth = node.ancestors().count()
# Or check depth manually by traversing parent chain
def get_depth(node):
depth = 0
current = node
while current.parent_id:
depth += 1
current = current.parent
return depth
Complex aggregations and subqueries¶
The recursive CTE used by django-tree-queries builds the tree top-down from root nodes to descendants. This makes certain operations, like aggregating values bottom-up (from descendants to ancestors) or using tree fields in complex subqueries, difficult or impossible.
# This doesn't work - can't use tree fields in subqueries with OuterRef
Branch.objects.annotate(
descendant_sum=Subquery(
Branch.objects.descendants(of=OuterRef('pk')).aggregate(Sum('amount'))
)
)
Workaround for small trees: Load the tree into memory and compute in Python:
# For small trees, load root nodes and calculate in Python
roots = Branch.objects.filter(parent=None)
for root in roots:
descendants = root.descendants(include_self=True)
total = sum(node.amount for node in descendants)
# Use the total...
For complex query requirements: If you need extensive CTE customization, subqueries with tree fields, or bottom-up aggregations, consider using django-cte which provides more control over recursive CTE construction, or evaluate whether a different tree storage approach (like django-treebeard with nested sets) better fits your needs.
For discussion of this limitation, see GitHub issue #75.
Breadth-first search¶
Nobody wants breadth-first search but if you still want it you can achieve it as follows:
nodes = Node.objects.with_tree_fields().extra(
order_by=["__tree.tree_depth", "__tree.tree_ordering"]
)
Filter by depth¶
If you only want nodes from the top two levels:
nodes = Node.objects.with_tree_fields().extra(
where=["__tree.tree_depth <= %s"],
params=[1],
)
Using tree fields with values()¶
By default, .values() only returns model fields, not tree fields. If you need
tree fields in a .values() call, you can access them using RawSQL:
from django.db.models.expressions import RawSQL
# Include tree fields in values() output
data = Node.objects.with_tree_fields().values(
"name",
tree_depth=RawSQL("tree_depth", ()),
tree_path=RawSQL("tree_path", ()),
)
# Returns: [{'name': 'root', 'tree_depth': 0, 'tree_path': [1]}, ...]
Important caveats:
PostgreSQL only:
tree_pathreturns a proper array only on PostgreSQL. Other databases return the internal string representation used by django-tree-queries (subject to change).Not guaranteed stable: The internal representation of tree fields may change in future versions. Avoid relying on the exact format of these values in application logic.
Performance: Using
.values()with tree fields doesn’t provide performance benefits over regular querysets with tree fields. Use this only when you specifically need dictionary output.
If you need tree field values for application logic, prefer accessing them as
attributes on model instances rather than through .values():
# Preferred approach
nodes = Node.objects.with_tree_fields()
for node in nodes:
depth = node.tree_depth
path = node.tree_path # Consistent across all databases
# Only use RawSQL with values() when you need dictionary output
data = Node.objects.with_tree_fields().values(
"name",
tree_depth=RawSQL("tree_depth", ()),
)
Aggregating ancestor fields¶
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.
# 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:
INSTALLED_APPS = [
# ... other apps
'tree_queries',
]
Then load the template tags in your template:
{% 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.
{% 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:Trueif this node starts a new level,Falseotherwiseclosed_levels: List of levels that close after this nodeancestors: List of ancestor node representations from root to immediate parent
Example showing ancestor information:
{% 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:
{% 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 nodechildren: Rendered HTML of child nodes (from the queryset)is_leaf:Trueif the node has no children in the queryset
Using is_leaf for conditional rendering:
{% 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:
{% 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:
# 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:
recursetreewill only render nodes from the querysetis_leafreflects whether nodes have children in the queryset, not in the full treeNo additional database queries are made
Nodes whose parents aren’t in the queryset are treated as root nodes
Example with depth-limited queryset:
<!-- 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.
Django Admin Integration¶
django-tree-queries includes a TreeAdmin class for Django’s admin interface
that provides an intuitive tree management experience with drag-and-drop style
node moving capabilities.
Installation¶
To use the admin functionality, install with the admin extra:
pip install django-tree-queries[admin]
Usage¶
With automatic position management:
For the best admin experience with proper ordering, use OrderableTreeNode:
from django.contrib import admin
from tree_queries.admin import TreeAdmin
from tree_queries.models import OrderableTreeNode
class Category(OrderableTreeNode):
name = models.CharField(max_length=100)
# position field and ordering are inherited from OrderableTreeNode
@admin.register(Category)
class CategoryAdmin(TreeAdmin):
list_display = [*TreeAdmin.list_display, "name"]
position_field = "position" # Enables sibling ordering controls
With manual position management:
If you prefer to manage positions yourself:
from django.contrib import admin
from django.db.models import Max
from tree_queries.admin import TreeAdmin
from tree_queries.models import TreeNode
class Category(TreeNode):
name = models.CharField(max_length=100)
position = models.PositiveIntegerField(default=0)
class Meta:
ordering = ["position"]
def save(self, *args, **kwargs):
# Custom position logic here
if not self.position:
self.position = (
10
+ (
self.__class__._default_manager.filter(parent_id=self.parent_id)
.order_by()
.aggregate(p=Max("position"))["p"]
or 0
)
)
super().save(*args, **kwargs)
save.alters_data = True
@admin.register(Category)
class CategoryAdmin(TreeAdmin):
list_display = [*TreeAdmin.list_display, "name"]
position_field = "position"
The TreeAdmin provides:
Tree visualization: Nodes are displayed with indentation and visual tree structure
Collapsible nodes: Click to expand/collapse branches for better navigation
Node moving: Cut and paste nodes to reorganize the tree structure
Flexible ordering: Supports both ordered (with position field) and unordered trees
Root moves: Direct “move to root” buttons for trees without sibling ordering
Configuration:
Set
position_fieldto the field name used for positioning siblings (e.g.,"position","order")Leave
position_field = Nonefor trees positioned by other criteria (pk, name, etc.)The admin automatically adapts its interface based on whether positioning is controllable
Required list_display columns:
collapse_column: Shows expand/collapse togglesindented_title: Displays the tree structure with indentationmove_column: Provides move controls (cut, paste, move-to-root)
These are included by default in TreeAdmin.list_display.
Migrating from django-mptt¶
When migrating from django-mptt to django-tree-queries, you’ll need to populate
the position field (or whatever field you use for sibling ordering) based on
the existing MPTT lft values. Here’s an example migration:
def fill_position(apps, schema_editor):
ModelWithMPTT = apps.get_model("your_app", "ModelWithMPTT")
db_alias = schema_editor.connection.alias
position_map = ModelWithMPTT.objects.using(db_alias).annotate(
lft_rank=Window(
expression=RowNumber(),
partition_by=[F("parent_id")],
order_by=["lft"],
),
).in_bulk()
# Update batches of 2000 objects.
batch_size = 2000
qs = ModelWithMPTT.objects.all()
batches = (qs[i : i + batch_size] for i in range(0, qs.count(), batch_size))
for batch in batches:
for obj in batch:
obj.position = position_map[obj.pk].lft_rank
ModelWithMPTT.objects.bulk_update(batch, ["position"])
class Migration(migrations.Migration):
dependencies = [...]
operations = [
migrations.RunPython(
code=fill_position,
reverse_code=migrations.RunPython.noop,
)
]
This migration uses Django’s Window function with RowNumber() to assign
position values based on the original MPTT lft ordering, ensuring that siblings
maintain their relative order after the migration.
Note that the position field is used purely for ordering siblings and is not an index. By default, django-tree-queries’ admin interface starts with a position value of 10 and increments by 10 (10, 20, 30, etc.) to make it explicit that the position values themselves have no inherent meaning - they are purely for relative ordering, not a sibling counter or index.
Replacing add_related_count():
django-mptt’s add_related_count() method for cumulative related object counts
is not directly supported in django-tree-queries. The implementation would be
complex and database-specific. For community-contributed solutions and discussion
of alternative approaches, see mptt-related issues on GitHub.
Change log¶
Next version¶
0.24 (2026-03-25)¶
Breaking changes:
tree_fields()now raisesValueErrorwhen attempting to use the model’s primary key field (previously causedProgrammingErroron PostgreSQL with ambiguous column error). If you were catchingProgrammingErrorfor this case, catchValueErrorinstead.Passing an invalid type as
sibling_ordernow raisesTypeErrorinstead ofValueErrorbecause that’s the more appropriate exception type.
Bug fixes and improvements:
Fixed a bug where the
{% recursetree %}template tag would show stale data on subsequent renders because the children cache was stored on the node instance instead of incontext.render_context.Fixed a bug where
{% recursetree %}inside a{% for %}loop would render only the first queryset’s children for all iterations (#104).Fixed compatibility with Django main (6.1+) which now quotes all SQL identifiers including table aliases; tree querysets used as subqueries (e.g.
filter(pk__in=node.descendants())) no longer fail on PostgreSQL.Added Python 3.14 and Django 6.0 to the CI matrix; dropped intermediate non-LTS versions (Django 4.1, 5.0, 5.1 and Python 3.11) while retaining old-but-still-used versions (Python 3.8, Django 3.2).
Added documentation clarifying when tree fields are available: they are only present on queries using
with_tree_fields()and are NOT available afterModel.objects.create(),instance.save(), orinstance.refresh_from_db().Added documentation on how to access tree fields in
.values()calls usingRawSQL, including caveats about database compatibility and stability.Added documentation clarifying
select_related()support: it works when querying from the tree model but not when querying from related models. Included workarounds usingprefetch_related()and manual fetching.Added note in the django-mptt migration section about
add_related_count()not being directly supported, with a link to mptt-labeled GitHub issues for community-contributed solutions.Added documentation for union, intersection, and difference operations not being supported with tree querysets, with a workaround using regular querysets then adding tree fields.
Added documentation for limiting tree depth using
.extra()and limiting children per node using model validation, with examples for checking depth programmatically.Added documentation about limitations with complex aggregations and subqueries due to top-down CTE construction, with pointers to django-cte for more complex requirements.
0.23 (2025-11-27)¶
Added a new
OrderableTreeNodebase class which includes a position field for ordering among siblings, and started recommending it.
0.22 (2025-11-06)¶
Made the new
tree_queries.adminmodule importable whendjango-js-assetisn’t installed so thatcompilemessagesand other tools automatically importing this module are allowed to work.Added an example migration to the documentation for migrating from django-mptt to django-tree-queries. Thanks to @felixmm for providing this!
Avoided fetching ancestors of nodes without parents. Thanks to @felixmm!
Added a system check which verifies that
"tree_queries"has been added toINSTALLED_APPSif using theTreeAdminmodel admin class.
0.21 (2025-09-16)¶
Added the missing
FieldDoesNotExistimport. Thanks Kircheneer.Fixed all errors reported by pre-commit and started running hooks automatically.
Added
TreeAdminclass for Django admin with intuitive tree management, node moving capabilities, and support for both positioned and unpositioned trees. Requiresdjango-js-assetwhich is included in the newadminextra.
0.20 (2025-06-11)¶
Added Python 3.13, Django 5.1 and 5.2 to the testsuite.
Added tests showing that
.descendants().update(...)doesn’t work, but.filter(pk__in=....descendants()).update(...)does.Added Python 3.13 to the testsuite.
Converted the tests to use pytest.
Added a
tree_infotemplate tag and arecursetreetemplate block.Optimized the performance by avoiding the rank table altogether in the simple case of an ascending ordering on a single field. If that’s not possible, the README now documents using
.tree_filter()and.tree_exclude()to filter the queryset before running the recursive CTE.Improved the test coverage.
0.19 (2024-04-25)¶
Reimplemented the rank table construction using a real queryset; this enables support for pre-filtering the tree queryset using
.tree_filter()and.tree_exclude(). Thanks rhomboss!Added a
.tree_fields()method to allow adding additional columns to the tree queryset, allowing collecting ancestors fields directly when running the initial query. For example,.tree_fields(tree_names="name")will collect allnamefields in atree_fieldsarray on the model instances. For now the code only supports string fields and integer fields.
0.18 (2024-04-03)¶
Fixed broken SQL which was generated when using a tree query with
EXISTS()subqueries.
0.17 (2024-03-26)¶
Preserved the tree ordering even when using
.values()or.values_list(). Thanks Glenn Matthews!Added support for descending sibling ordering, multi-field sibling ordering, and related field sibling ordering. Thanks rhomboss!
0.16 (2023-11-29)¶
Added Python 3.12, Django 5.0.
Fixed a problem where
.values()would return an incorrect mapping. Thanks Glenn Matthews!Started running tests periodically to catch bugs earlier.
0.15 (2023-06-19)¶
Switched to ruff and hatchling.
Dropped Django 4.0.
Added Python 3.11.
Added a
.without_tree_fields()method which calls.with_tree_fields(False)in a way which doesn’t trigger the flake8 boolean trap linter.
0.14 (2023-01-30)¶
Changed the behavior around sibling ordering to warn if using
Meta.orderingwhere ordering contains more than one field.Added Django 4.2a1 to the CI.
Django 5.0 will require Python 3.10 or better, pruned the CI jobs list.
Added quoting to the field name for the ordering between siblings so that fields named
ordercan be used. Thanks Tao Bojlén!Narrowed exception catching when determining whether the ordering field is an integer field or not. Thanks Tao Bojlén.
0.13 (2022-12-08)¶
Made it possible to use tree queries with multiple table inheritance. Thanks Olivier Dalang for the testcases and the initial implementation!
0.12 (2022-11-30)¶
Removed compatibility with Django < 3.2, Python < 3.8.
Added Django 4.1 to the CI.
Fixed
.with_tree_fields().explain()on some databases. Thanks Bryan Culver!
0.11 (2022-06-10)¶
Fixed a crash when running
.with_tree_fields().distinct().count()by 1. avoiding to select tree fields in distinct subqueries and 2. trusting the testsuite.
0.10 (2022-06-07)¶
Fixed ordering by string fields to actually work correctly in the presence of values of varying length.
0.9 (2022-04-01)¶
Added
TreeQuerySet.order_siblings_bywhich allows specifying an ordering for siblings per-query.
0.8 (2022-03-09)¶
Added pre-commit configuration to automatically remove some old-ish code patterns.
Fixed a compatibility problem with the upcoming Django 4.1.
0.7 (2021-10-31)¶
Added a test with a tree node having a UUID as its primary key.
0.6 (2021-07-21)¶
Fixed
TreeQuerySet.ancestorsto support primary keys not namedid.Changed the tree compiler to only post-process its own database results.
Added
**kwargs-passing toTreeQuery.get_compilerfor compatibility with Django 4.0.
0.5 (2021-05-12)¶
Added support for adding tree fields to queries by default. Create a manager using
TreeQuerySet.as_manager(with_tree_fields=True).Ensured the availability of the
with_tree_fieldsconfiguration also on subclassed managers, e.g. those used for traversing reverse relations.Dropped compatibility with Django 1.8 to avoid adding workarounds to the testsuite.
Made it possible to use django-tree-queries in more situations involving JOINs. Thanks Safa Alfulaij for the contribution!
0.4 (2020-09-13)¶
Fixed a grave bug where a position of
110would be sorted before20for obvious reasons.Added a custom
TreeNodeForeignKey.deconstructmethod to avoid migrations because of changing field types.Removed one case of unnecessary fumbling in
Query’s internals making things needlessly harder than they need to be. Made django-tree-queries compatible with Django’s master branch.Removed Python 3.4 from the Travis CI job list.
Dropped the conversion of primary keys to text on PostgreSQL. It’s a documented constraint that django-tree-queries only supports integer primary keys, therefore the conversion wasn’t necessary at all.
Reverted to using integer arrays on PostgreSQL for ordering if possible instead of always converting everything to padded strings.
0.3 (2018-11-15)¶
Added a
label_from_instanceoverride to the form fields.Removed the limitation that nodes can only be ordered using an integer field within their siblings.
Changed the representation of
tree_pathandtree_orderingused on MySQL/MariaDB and sqlite3. Also made it clear that the representation isn’t part of the public interface of this package.
0.2 (2018-10-04)¶
Added an optional argument to
TreeQuerySet.with_tree_fields()to allow reverting to a standard queryset (without tree fields).Added
tree_queries.fields.TreeNodeForeignKey,tree_queries.forms.TreeNodeChoiceFieldandtree_queries.forms.TreeNodeMultipleChoiceFieldwith node depth visualization.Dropped Python 3.4 from the CI.
0.1 (2018-07-30)¶
Initial release!