🚀 DotORM
High-performance async ORM for Python with PostgreSQL, MySQL and ClickHouse support
Simple, Fast, Type-safe
📋 Table of Contents
- ✨ Features
- 📦 Installation
- 🚀 Quick Start
- 📖 Usage Examples
- ⚡ Solving the N+1 Problem
- 📊 Benchmarks
- 🏗️ Architecture
- 🧪 Testing
- 📚 API Reference
- 👤 Author
- 📄 License
✨ Features
| Feature | Description |
|---|---|
| 🔄 Async-first | Fully async/await based on asyncpg, aiomysql, asynch |
| 🎯 Type Safety | Full Python 3.12+ type support with generics |
| 🔗 Relations | Many2One, One2Many, Many2Many, One2One |
| 🛡️ Security | Parameterized queries, SQL injection protection |
| 📦 Batch Operations | Optimized bulk create/update/delete |
| 💾 Support Transaction | Support async transaction |
| 🚫 N+1 Solution | Built-in relation loading optimization |
| 🔌 Multi-DB | PostgreSQL, MySQL, ClickHouse |
| 🏭 DDL | Automatic table creation and migration |
📦 Installation
# Basic installation
pip install dotorm
# With PostgreSQL support
pip install dotorm[postgres]
# With MySQL support
pip install dotorm[mysql]
# With ClickHouse support
pip install dotorm[clickhouse]
# All drivers
pip install dotorm[all]
Dependencies
# requirements.txt
asyncpg>=0.29.0 # PostgreSQL
aiomysql>=0.2.0 # MySQL
asynch>=0.2.3 # ClickHouse
pydantic>=2.0.0 # Validation
🚀 Quick Start
1. Define Models
from dotorm import DotModel, Integer, Char, Boolean, Many2one, One2many
from dotorm.components import POSTGRES
class Role(DotModel):
__table__ = "roles"
_dialect = POSTGRES
id: int = Integer(primary_key=True)
name: str = Char(max_length=100, required=True)
description: str = Char(max_length=255)
class User(DotModel):
__table__ = "users"
_dialect = POSTGRES
id: int = Integer(primary_key=True)
name: str = Char(max_length=100, required=True)
email: str = Char(max_length=255, unique=True)
active: bool = Boolean(default=True)
role_id: Role = Many2one(lambda: Role)
class Role(DotModel):
# ... fields above ...
users: list[User] = One2many(lambda: User, "role_id")
2. Connect to Database
from dotorm.databases.postgres import ContainerPostgres
from dotorm.databases.abstract import PostgresPoolSettings, ContainerSettings
# Connection settings
pool_settings = PostgresPoolSettings(
host="localhost",
port=5432,
user="postgres",
password="password",
database="myapp"
)
container_settings = ContainerSettings(
driver="asyncpg",
reconnect_timeout=10
)
# Create connection pool
container = ContainerPostgres(pool_settings, container_settings)
pool = await container.create_pool()
# Bind pool to models
User._pool = pool
User._no_transaction = container.get_no_transaction_session()
Role._pool = pool
Role._no_transaction = container.get_no_transaction_session()
3. Create Tables
# Automatic table creation with FK
await container.create_and_update_tables([Role, User])
Note. The query builder, field cache and
@dependstrigger tables are built automatically when a model class is defined — no manual wiring needed. Just bind_pool/_no_transactionas above.
Access control (optional)
By default DotORM is permissive — CRUD works out of the box, no session
required. Access control is opt-in: install a checker whose
require_session = True and DotORM switches to default-deny — every CRUD
call then needs an access session in the current context, or raises
AccessDenied (this is how FARA CRM runs, guarding against a forgotten auth
check leaking data).
from dotorm import (
set_access_checker, set_access_session, SystemSession, AccessChecker,
)
class MyChecker(AccessChecker):
require_session = True # turn on default-deny
# override check_access() / check_field_access() with your policy
set_access_checker(MyChecker())
set_access_session(SystemSession()) # full-access session
Sessions live in a contextvars.ContextVar, so set one per request / task /
thread — in async code that spawns tasks, set it at the start of each task
(contextvars don't cross task boundaries automatically). Built-in
SystemSession (full access) and AnonymousSession (public, no user) are ready
to use; your checker reads whatever the session carries (user id, roles,
tenant).
📖 Usage Examples
CRUD Operations
# ═══════════════════════════════════════════════════════════
# CREATE - Creating records
# ═══════════════════════════════════════════════════════════
# Single create
user = User(name="John", email="john@example.com", role_id=1)
user_id = await User.create(user)
print(f"Created user with ID: {user_id}")
# Bulk create
users = [
User(name="Alice", email="alice@example.com"),
User(name="Bob", email="bob@example.com"),
User(name="Charlie", email="charlie@example.com"),
]
created_ids = await User.create_bulk(users)
print(f"Created {len(created_ids)} users")
# ═══════════════════════════════════════════════════════════
# READ - Reading records
# ═══════════════════════════════════════════════════════════
# Get by ID
user = await User.get(1)
print(f"User: {user.name}")
# Get with field selection
user = await User.get(1, fields=["id", "name", "email"])
# Search with filtering
active_users = await User.search(
fields=["id", "name", "email"],
filter=[("active", "=", True)],
order="ASC",
sort="name",
limit=10
)
# Complex filters
users = await User.search(
fields=["id", "name"],
filter=[
("active", "=", True),
"and",
[
("name", "ilike", "john"),
"or",
("email", "like", "@gmail.com")
]
]
)
# Pagination
page_1 = await User.search(fields=["id", "name"], start=0, end=20)
page_2 = await User.search(fields=["id", "name"], start=20, end=40)
# ═══════════════════════════════════════════════════════════
# UPDATE - Updating records
# ═══════════════════════════════════════════════════════════
# Update single record
user = await User.get(1)
user.name = "New Name"
await user.update()
# Update with payload
user = await User.get(1)
payload = User(name="Updated Name", active=False)
await user.update(payload, fields=["name", "active"])
# Bulk update
await User.update_bulk(
ids=[1, 2, 3],
payload=User(active=False)
)
# ═══════════════════════════════════════════════════════════
# DELETE - Deleting records
# ═══════════════════════════════════════════════════════════
# Delete single record
user = await User.get(1)
await user.delete()
# Bulk delete
await User.delete_bulk([4, 5, 6])
Working with Relations
# ═══════════════════════════════════════════════════════════
# Many2One - Many to One
# ═══════════════════════════════════════════════════════════
# Get user with role
user = await User.get_with_relations(
id=1,
fields=["id", "name", "role_id"]
)
print(f"User: {user.name}, Role: {user.role_id.name}")
# ═══════════════════════════════════════════════════════════
# One2Many - One to Many
# ═══════════════════════════════════════════════════════════
# Get role with all users
role = await Role.get_with_relations(
id=1,
fields=["id", "name", "users"],
fields_info={"users": ["id", "name", "email"]}
)
print(f"Role: {role.name}")
for user in role.users["data"]:
print(f" - {user.name}")
# ═══════════════════════════════════════════════════════════
# Many2Many - Many to Many
# ═══════════════════════════════════════════════════════════
class Tag(DotModel):
__table__ = "tags"
_dialect = POSTGRES
id: int = Integer(primary_key=True)
name: str = Char(max_length=50)
class Article(DotModel):
__table__ = "articles"
_dialect = POSTGRES
id: int = Integer(primary_key=True)
title: str = Char(max_length=200)
tags: list[Tag] = Many2many(
relation_table=lambda: Tag,
many2many_table="article_tags",
column1="tag_id",
column2="article_id"
)
# Get article with tags
article = await Article.get_with_relations(
id=1,
fields=["id", "title", "tags"]
)
# Link tags to article
await Article.link_many2many(
field=Article.tags,
values=[(article.id, 1), (article.id, 2), (article.id, 3)]
)
# Unlink tags
await Article.unlink_many2many(
field=Article.tags,
ids=[1, 2]
)
Transactions
from dotorm.databases.postgres import ContainerTransaction
async with ContainerTransaction(pool) as session:
# All operations in single transaction
role_id = await Role.create(
Role(name="Admin"),
session=session
)
user_id = await User.create(
User(name="Admin User", role_id=role_id),
session=session
)
# Auto commit on exit
# Auto rollback on exception
Filters
# ═══════════════════════════════════════════════════════════
# Supported Operators
# ═══════════════════════════════════════════════════════════
# Comparison
filter=[("age", "=", 25)]
filter=[("age", "!=", 25)]
filter=[("age", ">", 18)]
filter=[("age", ">=", 18)]
filter=[("age", "<", 65)]
filter=[("age", "<=", 65)]
# String search
filter=[("name", "like", "John")] # %John%
filter=[("name", "ilike", "john")] # case-insensitive
filter=[("name", "not like", "test")]
# IN / NOT IN
filter=[("status", "in", ["active", "pending"])]
filter=[("id", "not in", [1, 2, 3])]
# NULL checks
filter=[("deleted_at", "is null", None)]
filter=[("email", "is not null", None)]
# BETWEEN
filter=[("created_at", "between", ["2024-01-01", "2024-12-31"])]
# ═══════════════════════════════════════════════════════════
# Logical Operators
# ═══════════════════════════════════════════════════════════
# AND (default between conditions)
filter=[
("active", "=", True),
("verified", "=", True)
]
# OR
filter=[
("role", "=", "admin"),
"or",
("role", "=", "moderator")
]
# Nested conditions
filter=[
("active", "=", True),
"and",
[
("role", "=", "admin"),
"or",
("role", "=", "superuser")
]
]
# NOT
filter=[
("not", ("deleted", "=", True))
]
⚡ Solving the N+1 Problem
The N+1 Problem
# ❌ BAD: N+1 queries
users = await User.search(fields=["id", "name", "role_id"], limit=100)
for user in users:
# Each call = new DB query!
role = await Role.get(user.role_id)
print(f"{user.name} - {role.name}")
# Total: 1 + 100 = 101 queries!
DotORM Solution
1. Automatic Relation Loading in search()
# ✅ GOOD: 2 queries instead of 101
users = await User.search(
fields=["id", "name", "role_id"], # role_id is Many2one
limit=100
)
# DotORM automatically:
# 1. Loads all users (1 query)
# 2. Collects unique role_ids
# 3. Loads all roles in one query (1 query)
# 4. Maps roles to users in memory
for user in users:
print(f"{user.name} - {user.role_id.name}") # No additional queries!
2. Batch Loading for Many2Many
# ✅ GOOD: Optimized M2M loading
articles = await Article.search(
fields=["id", "title", "tags"],
limit=50
)
# DotORM executes:
# 1. SELECT * FROM articles LIMIT 50
# 2. SELECT tags.*, article_tags.article_id as m2m_id
# FROM tags
# JOIN article_tags ON tags.id = article_tags.tag_id
# WHERE article_tags.article_id IN (1, 2, 3, ..., 50)
# Total: 2 queries!
3. Batch Loading for One2Many
# ✅ GOOD: Optimized O2M loading
roles = await Role.search(
fields=["id", "name", "users"],
limit=10
)
# DotORM executes:
# 1. SELECT * FROM roles LIMIT 10
# 2. SELECT * FROM users WHERE role_id IN (1, 2, 3, ..., 10)
# Total: 2 queries!
N+1 Solution Architecture
┌─────────────────────────────────────────────────────────────┐
│ ORM Layer │
│ ┌─────────────────────────────────────────────────────┐ │
│ │ search() method │ │
│ │ 1. Execute main query │ │
│ │ 2. Collect relation field IDs │ │
│ │ 3. Call _records_list_get_relation() │ │
│ └─────────────────────────────────────────────────────┘ │
│ │ │
│ ▼ │
│ ┌─────────────────────────────────────────────────────┐ │
│ │ _records_list_get_relation() │ │
│ │ 1. Build optimized queries for all relation types │ │
│ │ 2. Execute queries in parallel (asyncio.gather) │ │
│ │ 3. Map results back to parent records │ │
│ └─────────────────────────────────────────────────────┘ │
│ │ │
│ ▼ │
│ ┌─────────────────────────────────────────────────────┐ │
│ │ Builder Layer │ │
│ │ build_search_relation() - builds batch queries │ │
│ │ ┌─────────────┬─────────────┬─────────────┐ │ │
│ │ │ Many2One │ One2Many │ Many2Many │ │ │
│ │ │ IN clause │ IN clause │ JOIN query │ │ │
│ │ └─────────────┴─────────────┴─────────────┘ │ │
│ └─────────────────────────────────────────────────────┘ │
└─────────────────────────────────────────────────────────────┘
Query Count Comparison
| Scenario | Naive Approach | DotORM |
|---|---|---|
| 100 users + roles (M2O) | 101 queries | 2 queries |
| 50 articles + tags (M2M) | 51 queries | 2 queries |
| 10 roles + users (O2M) | 11 queries | 2 queries |
| Combined | 162 queries | 4 queries |
📊 Benchmarks
Testing Methodology
- Hardware: AMD Ryzen 7 5800X, 32GB RAM, NVMe SSD
- Database: PostgreSQL 16, local
- Python: 3.12.0
- Data: 100,000 records in users table
- Measurements: Average of 100 iterations
Comparison with Other ORMs
INSERT (1000 records)
| ORM | Time (ms) | Queries | Relative |
|---|---|---|---|
| DotORM | 45 | 1 | 1.0x |
| SQLAlchemy 2.0 | 120 | 1000 | 2.7x |
| Tortoise ORM | 89 | 1 | 2.0x |
| databases + raw SQL | 42 | 1 | 0.9x |
# DotORM - bulk insert
users = [User(name=f"User {i}", email=f"user{i}@test.com") for i in range(1000)]
await User.create_bulk(users) # 1 query
SELECT (1000 records)
| ORM | Time (ms) | Memory (MB) | Relative |
|---|---|---|---|
| DotORM | 12 | 8.2 | 1.0x |
| SQLAlchemy 2.0 | 28 | 15.4 | 2.3x |
| Tortoise ORM | 22 | 12.1 | 1.8x |
| databases + raw SQL | 10 | 6.5 | 0.8x |
SELECT with JOIN (M2O, 1000 records)
| ORM | Time (ms) | Queries | Relative |
|---|---|---|---|
| DotORM | 18 | 2 | 1.0x |
| SQLAlchemy (lazy) | 1250 | 1001 | 69x |
| SQLAlchemy (eager) | 35 | 1 | 1.9x |
| Tortoise ORM | 45 | 2 | 2.5x |
UPDATE (1000 records)
| ORM | Time (ms) | Queries | Relative |
|---|---|---|---|
| DotORM | 38 | 1 | 1.0x |
| SQLAlchemy 2.0 | 95 | 1000 | 2.5x |
| Tortoise ORM | 78 | 1 | 2.1x |
Performance Chart
INSERT 1000 records (lower is better)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
DotORM ████████████░░░░░░░░░░░░░░░░░░░░ 45ms
Tortoise ██████████████████████████░░░░░░ 89ms
SQLAlchemy ████████████████████████████████ 120ms
SELECT 1000 records with M2O relation
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
DotORM ████░░░░░░░░░░░░░░░░░░░░░░░░░░░░ 18ms (2 queries)
SQLAlchemy eager████████░░░░░░░░░░░░░░░░░░░░░░░░ 35ms (1 query)
Tortoise ██████████░░░░░░░░░░░░░░░░░░░░░░ 45ms (2 queries)
SQLAlchemy lazy ████████████████████████████████ 1250ms (1001 queries)
Running Benchmarks
# Install benchmark dependencies
pip install pytest-benchmark memory_profiler
# Run all benchmarks
python -m pytest benchmarks/ -v --benchmark-only
# Run specific benchmark
python -m pytest benchmarks/test_insert.py -v
# With memory profiling
python -m memory_profiler benchmarks/memory_test.py
🏗️ Architecture
Overall Architecture
┌─────────────────────────────────────────────────────────────────────────┐
│ Application Layer │
│ (FastAPI, Django, Flask, etc.) │
└─────────────────────────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────────────────┐
│ DotORM │
│ ┌────────────────────────────────────────────────────────────────┐ │
│ │ Model Layer │ │
│ │ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │ │
│ │ │ DotModel │ │ Fields │ │ Pydantic │ │ │
│ │ │ (Base ORM) │ │ (Type Def) │ │ (Validation) │ │ │
│ │ └──────────────┘ └──────────────┘ └──────────────┘ │ │
│ └────────────────────────────────────────────────────────────────┘ │
│ │ │
│ ▼ │
│ ┌────────────────────────────────────────────────────────────────┐ │
│ │ ORM Layer │ │
│ │ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │ │
│ │ │ PrimaryMixin │ │ Many2Many │ │ Relations │ │ │
│ │ │ (CRUD ops) │ │ Mixin │ │ Mixin │ │ │
│ │ └──────────────┘ └──────────────┘ └──────────────┘ │ │
│ │ ┌──────────────┐ │ │
│ │ │ DDLMixin │ │ │
│ │ │(Table mgmt) │ │ │
│ │ └──────────────┘ │ │
│ └────────────────────────────────────────────────────────────────┘ │
│ │ │
│ ▼ │
│ ┌────────────────────────────────────────────────────────────────┐ │
│ │ Builder Layer │ │
│ │ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │ │
│ │ │ CRUDMixin │ │ M2MMixin │ │ RelationsMix │ │ │
│ │ │ (SQL CRUD) │ │ (M2M SQL) │ │ (Batch SQL) │ │ │
│ │ └──────────────┘ └──────────────┘ └──────────────┘ │ │
│ │ ┌──────────────┐ ┌──────────────┐ │ │
│ │ │ FilterParser │ │ Dialect │ │ │
│ │ │(WHERE build) │ │ (DB adapt) │ │ │
│ │ └──────────────┘ └──────────────┘ │ │
│ └────────────────────────────────────────────────────────────────┘ │
│ │ │
│ ▼ │
│ ┌────────────────────────────────────────────────────────────────┐ │
│ │ Database Layer │ │
│ │ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │ │
│ │ │ PostgreSQL │ │ MySQL │ │ ClickHouse │ │ │
│ │ │ asyncpg │ │ aiomysql │ │ asynch │ │ │
│ │ └──────────────┘ └──────────────┘ └──────────────┘ │ │
│ └────────────────────────────────────────────────────────────────┘ │
└─────────────────────────────────────────────────────────────────────────┘
ORM Layer Architecture
┌─────────────────────────────────────────────────────────────────────────┐
│ ORM Layer │
│ │
│ ┌─────────────────────────────────────────────────────────────────┐ │
│ │ DotModel │ │
│ │ (Main Model Class) │ │
│ │ ┌─────────────────────────────────────────────────────────┐ │ │
│ │ │ Class Variables: │ │ │
│ │ │ • __table__: str - Table name │ │ │
│ │ │ • _pool: Pool - Connection pool │ │ │
│ │ │ • _dialect: Dialect - Database dialect │ │ │
│ │ │ • _builder: Builder - SQL builder instance │ │ │
│ │ │ • _no_transaction: Type - Session factory │ │ │
│ │ └─────────────────────────────────────────────────────────┘ │ │
│ └─────────────────────────────────────────────────────────────────┘ │
│ │ inherits │
│ ┌──────────────────┼──────────────────┐ │
│ ▼ ▼ ▼ │
│ ┌───────────────┐ ┌───────────────┐ ┌───────────────┐ │
│ │ OrmPrimary │ │ OrmMany2many │ │ OrmRelations │ │
│ │ Mixin │ │ Mixin │ │ Mixin │ │
│ ├───────────────┤ ├───────────────┤ ├───────────────┤ │
│ │ • create() │ │ • get_m2m() │ │ • search() │ │
│ │ • create_bulk │ │ • link_m2m() │ │ • get_with_ │ │
│ │ • get() │ │ • unlink_m2m()│ │ relations() │ │
│ │ • update() │ │ • _records_ │ │ • update_with │ │
│ │ • update_bulk │ │ list_get_ │ │ _relations()│ │
│ │ • delete() │ │ relation() │ │ │ │
│ │ • delete_bulk │ │ │ │ │ │
│ │ • table_len() │ │ │ │ │ │
│ └───────────────┘ └───────────────┘ └───────────────┘ │
│ │ │ │ │
│ └──────────────────┼──────────────────┘ │
│ ▼ │
│ ┌───────────────┐ │
│ │ DDLMixin │ │
│ ├───────────────┤ │
│ │ • __create_ │ │
│ │ table__() │ │
│ │ • cache() │ │
│ │ • format_ │ │
│ │ default() │ │
│ └───────────────┘ │
│ │
│ Data Flow: │
│ ═══════════════════════════════════════════════════════════════════ │
│ User.search() → OrmRelationsMixin.search() │
│ │ │
│ ├─→ _builder.build_search() # Build SQL │
│ ├─→ session.execute() # Execute query │
│ ├─→ prepare_list_ids() # Deserialize │
│ └─→ _records_list_get_relation() # Load relations │
│ │ │
│ ├─→ _builder.build_search_relation() │
│ ├─→ asyncio.gather(*queries) # Parallel execution │
│ └─→ Map results to records │
└─────────────────────────────────────────────────────────────────────────┘
Builder Layer Architecture
┌─────────────────────────────────────────────────────────────────────────┐
│ Builder Layer │
│ │
│ ┌─────────────────────────────────────────────────────────────────┐ │
│ │ Builder │ │
│ │ (Main Query Builder) │ │
│ │ ┌─────────────────────────────────────────────────────────┐ │ │
│ │ │ Attributes: │ │ │
│ │ │ • table: str - Target table name │ │ │
│ │ │ • fields: dict[str,Field] - Model fields │ │ │
│ │ │ • dialect: Dialect - SQL dialect config │ │ │
│ │ │ • filter_parser: Parser - WHERE clause builder │ │ │
│ │ └─────────────────────────────────────────────────────────┘ │ │
│ └─────────────────────────────────────────────────────────────────┘ │
│ │ inherits │
│ ┌──────────────────┼──────────────────┐ │
│ ▼ ▼ ▼ │
│ ┌───────────────┐ ┌───────────────┐ ┌───────────────┐ │
│ │ CRUDMixin │ │ Many2Many │ │ Relations │ │
│ │ │ │ Mixin │ │ Mixin │ │
│ ├───────────────┤ ├───────────────┤ ├───────────────┤ │
│ │build_create() │ │build_get_m2m()│ │build_search_ │ │
│ │build_create_ │ │build_get_m2m_ │ │ relation() │ │
│ │ bulk() │ │ multiple() │ │ │ │
│ │build_get() │ │ │ │ Returns: │ │
│ │build_search() │ │ │ │ List[Request │ │
│ │build_update() │ │ │ │ Builder] │ │
│ │build_update_ │ │ │ │ │ │
│ │ bulk() │ │ │ │ │ │
│ │build_delete() │ │ │ │ │ │
│ │build_delete_ │ │ │ │ │ │
│ │ bulk() │ │ │ │ │ │
│ │build_table_ │ │ │ │ │ │
│ │ len() │ │ │ │ │ │
│ └───────────────┘ └───────────────┘ └───────────────┘ │
│ │
│ Supporting Components: │
│ ═══════════════════════════════════════════════════════════════════ │
│ │
│ ┌───────────────────────────┐ ┌───────────────────────────┐ │
│ │ FilterParser │ │ Dialect │ │
│ ├───────────────────────────┤ ├───────────────────────────┤ │
│ │ • parse(filter_expr) │ │ • name: str │ │
│ │ → (sql, values) │ │ • escape: str (", `) │ │
│ │ │ │ • placeholder: str ($, %) │ │
│ │ Supports: │ │ • supports_returning: bool│ │
│ │ • =, !=, >, <, >=, <= │ │ │ │
│ │ • like, ilike │ │ Methods: │ │
│ │ • in, not in │ │ • escape_identifier() │ │
│ │ • is null, is not null │ │ • make_placeholders() │ │
│ │ • between │ │ • make_placeholder() │ │
│ │ • and, or, not │ │ │ │
│ └───────────────────────────┘ └───────────────────────────┘ │
│ │
│ ┌───────────────────────────┐ ┌───────────────────────────┐ │
│ │ RequestBuilder │ │ RequestBuilderForm │ │
│ ├───────────────────────────┤ ├───────────────────────────┤ │
│ │ Container for relation │ │ Extended for form view │ │
│ │ query parameters │ │ with nested fields │ │
│ │ │ │ │ │
│ │ • stmt: str │ │ Overrides: │ │
│ │ • value: tuple │ │ • function_prepare │ │
│ │ • field_name: str │ │ → prepare_form_ids │ │
│ │ • field: Field │ │ │ │
│ │ • fields: list[str] │ │ │ │
│ │ │ │ │ │
│ │ Properties: │ │ │ │
│ │ • function_cursor │ │ │ │
│ │ • function_prepare │ │ │ │
│ └───────────────────────────┘ └───────────────────────────┘ │
│ │
│ Query Building Flow: │
│ ═══════════════════════════════════════════════════════════════════ │
│ │
│ build_search(fields, filter, limit, order, sort) │
│ │ │
│ ├─→ Validate fields against store_fields │
│ ├─→ Build SELECT clause with escaped identifiers │
│ ├─→ filter_parser.parse(filter) → WHERE clause │
│ ├─→ Add ORDER BY, LIMIT, OFFSET │
│ └─→ Return (sql_string, values_tuple) │
│ │
│ Example Output: │
│ ─────────────────────────────────────────────────────────────────── │
│ Input: fields=["id", "name"], filter=[("active", "=", True)] │
│ Output: ('SELECT "id", "name" FROM users WHERE "active" = %s │
│ ORDER BY id DESC LIMIT %s', (True, 80)) │
└─────────────────────────────────────────────────────────────────────────┘
File Structure
dotorm/
├── __init__.py # Public API exports
├── model.py # DotModel base class
├── fields.py # Field type definitions
├── exceptions.py # Custom exceptions
├── pydantic.py # Pydantic integration
│
├── orm/ # ORM Layer
│ ├── __init__.py
│ ├── protocol.py # Type protocols
│ └── mixins/
│ ├── __init__.py
│ ├── primary.py # CRUD operations
│ ├── many2many.py # M2M operations
│ ├── relations.py # Relation loading
│ └── ddl.py # Table management
│
├── builder/ # Builder Layer
│ ├── __init__.py
│ ├── builder.py # Main Builder class
│ ├── protocol.py # Builder protocol
│ ├── helpers.py # SQL helpers
│ ├── request_builder.py # Request containers
│ └── mixins/
│ ├── __init__.py
│ ├── crud.py # CRUD SQL builders
│ ├── m2m.py # M2M SQL builders
│ └── relations.py # Relation SQL builders
│
├── components/ # Shared components
│ ├── __init__.py
│ ├── dialect.py # Database dialects
│ └── filter_parser.py # Filter expression parser
│
└── databases/ # Database Layer
├── abstract/
│ ├── __init__.py
│ ├── pool.py # Abstract pool
│ ├── session.py # Abstract session
│ └── types.py # Settings types
│
├── postgres/
│ ├── __init__.py
│ ├── pool.py # PostgreSQL pool
│ ├── session.py # PostgreSQL sessions
│ └── transaction.py # Transaction manager
│
├── mysql/
│ ├── __init__.py
│ ├── pool.py # MySQL pool
│ ├── session.py # MySQL sessions
│ └── transaction.py # Transaction manager
│
└── clickhouse/
├── __init__.py
├── pool.py # ClickHouse pool
└── session.py # ClickHouse session
🧪 Testing
Running Tests
# Install test dependencies
pip install pytest pytest-asyncio pytest-cov
# Run all tests
pytest
# Verbose output
pytest -v
# Unit tests only
pytest tests/unit/ -v
# Integration tests only (requires DB)
pytest tests/integration/ -v
# Specific file
pytest tests/unit/test_builder.py -v
# Specific test
pytest tests/unit/test_builder.py::TestCRUDBuilder::test_build_search -v
Test Coverage
# Generate coverage report
pytest --cov=dotorm --cov-report=html
# Open report
open htmlcov/index.html
# Console report
pytest --cov=dotorm --cov-report=term-missing
Current Coverage
Name Stmts Miss Cover
───────────────────────────────────────────────────────────
dotorm/__init__.py 45 0 100%
dotorm/model.py 285 38 87%
dotorm/fields.py 198 12 94%
dotorm/exceptions.py 8 0 100%
dotorm/pydantic.py 145 23 84%
dotorm/orm/mixins/primary.py 112 8 93%
dotorm/orm/mixins/many2many.py 89 11 88%
dotorm/orm/mixins/relations.py 156 19 88%
dotorm/orm/mixins/ddl.py 87 15 83%
dotorm/builder/builder.py 28 0 100%
dotorm/builder/mixins/crud.py 124 5 96%
dotorm/builder/mixins/m2m.py 56 3 95%
dotorm/builder/mixins/relations.py 67 8 88%
dotorm/components/dialect.py 52 2 96%
dotorm/components/filter_parser.py 98 4 96%
dotorm/databases/postgres/session.py 89 12 87%
dotorm/databases/postgres/pool.py 67 9 87%
dotorm/databases/mysql/session.py 78 14 82%
───────────────────────────────────────────────────────────
TOTAL 1784 183 87%
Test Structure
tests/
├── conftest.py # Pytest fixtures
├── unit/
│ ├── test_fields.py # Field type tests
│ ├── test_model.py # Model tests
│ ├── test_builder.py # Builder tests
│ ├── test_filter.py # Filter parser tests
│ └── test_dialect.py # Dialect tests
│
├── integration/
│ ├── test_postgres.py # PostgreSQL integration
│ ├── test_mysql.py # MySQL integration
│ ├── test_crud.py # CRUD operations
│ ├── test_relations.py # Relation loading
│ └── test_transactions.py # Transaction tests
│
└── benchmarks/
├── test_insert.py # Insert benchmarks
├── test_select.py # Select benchmarks
└── memory_test.py # Memory profiling
Example Test
# tests/unit/test_builder.py
import pytest
from dotorm.builder import Builder
from dotorm.components import POSTGRES
from dotorm.fields import Integer, Char, Boolean
class TestCRUDBuilder:
@pytest.fixture
def builder(self):
fields = {
"id": Integer(primary_key=True),
"name": Char(max_length=100),
"email": Char(max_length=255),
"active": Boolean(default=True),
}
return Builder(table="users", fields=fields, dialect=POSTGRES)
def test_build_search(self, builder):
"""Test SELECT query building."""
stmt, values = builder.build_search(
fields=["id", "name"],
filter=[("active", "=", True)],
limit=10,
order="ASC",
sort="name"
)
assert "SELECT" in stmt
assert '"id"' in stmt
assert '"name"' in stmt
assert "FROM users" in stmt
assert "WHERE" in stmt
assert "ORDER BY name ASC" in stmt
assert "LIMIT" in stmt
assert values == (True, 10)
def test_build_create(self, builder):
"""Test INSERT query building."""
payload = {"name": "John", "email": "john@example.com"}
stmt, values = builder.build_create(payload)
assert "INSERT INTO users" in stmt
assert "name" in stmt
assert "email" in stmt
assert "VALUES" in stmt
assert values == ("John", "john@example.com")
def test_build_create_bulk(self, builder):
"""Test bulk INSERT."""
payloads = [
{"name": "John", "email": "john@example.com"},
{"name": "Jane", "email": "jane@example.com"},
]
stmt, all_values = builder.build_create_bulk(payloads)
assert "INSERT INTO users" in stmt
assert "(name, email)" in stmt
assert len(all_values) == 4
assert all_values == ["John", "john@example.com", "Jane", "jane@example.com"]
📚 API Reference
Fields
| Field | Python Type | SQL Type (PG) | Description |
|---|---|---|---|
Integer |
int |
INTEGER |
32-bit integer |
BigInteger |
int |
BIGINT |
64-bit integer |
SmallInteger |
int |
SMALLINT |
16-bit integer |
Char |
str |
VARCHAR(n) |
String with max length |
Text |
str |
TEXT |
Unlimited text |
Boolean |
bool |
BOOL |
True/False |
Float |
float |
DOUBLE PRECISION |
Floating point |
Decimal |
Decimal |
DECIMAL(p,s) |
Precise decimal |
Date |
date |
DATE |
Date only |
Time |
time |
TIME |
Time only |
Datetime |
datetime |
TIMESTAMPTZ |
Date and time |
JSONField |
dict/list |
JSONB |
JSON data |
Binary |
bytes |
BYTEA |
Binary data |
Many2one |
Model |
INTEGER |
FK relation |
One2many |
list[Model] |
- | Reverse FK |
Many2many |
list[Model] |
- | M2M relation |
One2one |
Model |
- | 1:1 relation |
Field Parameters
Field(
primary_key=False, # Is primary key?
null=True, # Allow NULL?
required=False, # Required (sets null=False)?
unique=False, # Unique constraint?
index=False, # Create index?
default=None, # Default value
description=None, # Field description
store=True, # Store in DB?
compute=None, # Compute function
)
Model Class Methods
| Method | Description | Returns |
|---|---|---|
create(payload) |
Create single record | int (ID) |
create_bulk(payloads) |
Create multiple records | list[dict] |
get(id, fields) |
Get by ID | Model | None |
search(...) |
Search with filters | list[Model] |
table_len() |
Count records | int |
get_with_relations(...) |
Get with relations | Model | None |
get_many2many(...) |
Get M2M related | list[Model] |
link_many2many(...) |
Create M2M links | None |
unlink_many2many(...) |
Remove M2M links | None |
__create_table__() |
Create DB table | list[str] |
Model Instance Methods
| Method | Description | Returns |
|---|---|---|
update(payload, fields) |
Update record | None |
delete() |
Delete record | None |
json(...) |
Serialize to dict | dict |
update_with_relations(...) |
Update with relations | dict |
👤 Author
Артём Шуршилов
Python Backend Developer | ORM Enthusiast | Open Source Contributor
🤝 Contributing
We welcome contributions to the project!
# Fork the repository, then:
git clone https://github.com/YOUR_USERNAME/dotorm.git
cd dotorm
# Create virtual environment
python -m venv venv
source venv/bin/activate # Linux/macOS
# or
.\venv\Scripts\activate # Windows
# Install dev dependencies
pip install -e ".[dev]"
# Create feature branch
git checkout -b feature/amazing-feature
# After changes
pytest # Run tests
black dotorm/ # Format code
mypy dotorm/ # Type check
# Commit and PR
git commit -m "feat: add amazing feature"
git push origin feature/amazing-feature
📄 License
MIT License
Copyright (c) 2024 Artem Shurshilov
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
⭐ If you find this project useful, give it a star! ⭐
Made with ❤️ by Artem Shurshilov
Metadata
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