typedmongo

Typed Mongo

A production-ready modern Python MongoDB ODM

In addition to synchronous mode, you can use asynchronous mode, just export from typedmongo.asyncio.

Install

pip install typedmongo

Usage

Usage examples trump all usage documentation. So please look at the Example below first.

Example

import datetime
from typing import Literal

from motor.motor_asyncio import AsyncIOMotorClient as MongoClient

import typedmongo.asyncio as mongo


class Wallet(mongo.Document):
    balance: mongo.DecimalField


class User(mongo.MongoDocument):
    name: mongo.StringField
    gender: mongo.LiteralField[Literal["m", "f"]]
    age: mongo.IntegerField
    tags: mongo.ListField[str]
    wallet: mongo.EmbeddedField[Wallet]
    created_at: mongo.DateTimeField = mongo.DateTimeField(
        default=lambda: datetime.datetime.now(datetime.timezone.utc)
    )
    children: mongo.ListField[User]
    extra: mongo.DictField = mongo.DictField(default=dict)


async def main():
    await mongo.initial_collections(
        MongoClient().mongo,
        User,
    )

    # Insert one document
    document_id = await User.objects.insert_one(
        User.load(
            {
                "name": "Aber",
                "gender": "m",
                "age": 18,
                "tags": ["a", "b"],
                "wallet": {"balance": 100},
                "children": [],
            },
        )
    )

    # Find one document
    user = await User.objects.find_one(User._id == document_id, sort=[+User.age])

    # Update one document
    update_result = await User.objects.update_one(
        User._id == document_id, {"$set": {"tags": ["a", "b", "e", "r"]}}
    )

    # Delete one document
    delete_result = await User.objects.delete_one(User._id == document_id)

    # Find one and update
    user = await User.objects.find_one_and_update(
        User._id == document_id, {"$set": {"tags": ["a", "b", "e"]}}
    )

    # Find one and replace
    user = await User.objects.find_one_and_replace(
        User._id == document_id,
        User.load({"name": "Aber", "age": 0}),
        after_document=True,
    )

    # Find one and delete
    user = await User.objects.find_one_and_delete(User._id == document_id)

    # Find many documents and sort
    users = [user async for user in User.objects.find(User.age == 18, sort=[-User.age])]

    # Update many documents
    update_result = await User.objects.update_many(
        User.wallet._.balance == Decimal("100"), {"$inc": {"wallet.balance": 10}}
    )

    # Count documents
    await User.objects.count_documents(User.age >= 0)

    # Bulk write operations
    await User.objects.bulk_write(
        mongo.DeleteOne(User._id == 0),
        mongo.DeleteMany(User.age < 18),
        mongo.InsertOne(User.load({"name": "InsertOne"}, partial=True)),
        mongo.ReplaceOne(User.name == "Aber", User.load({}, partial=True)),
        mongo.UpdateMany({}, {"$set": {"age": 25}}),
        mongo.UpdateMany(User.name == "Yue", {"$set": {"name": "yue"}}),
    )

Document

Note: The Document must be initialized with initial_collections before it can be used.

• Document.load: Load data from dict to instance, and validate the data.
• Document.dump: Dump the instance to jsonable dict.

Collection Name

Document.__collection_name__: Normally, subclasses of Document will generate a collection_name based on the Class Name, but if you want to customize it, you can set __collection_name__ when defining it.

class APIKey(mongo.Document):
    __collection_name__ = "api_key"

Raw Collection

If you want to use functions such as aggregate, you can access pymongo's original collection object through Document.objects.collection.

Document.objects.collection.aggregate([
    {"$group": {"_id": "$field", "count": {"$sum": 1}}}
])

Field

• ObjectIdField
• StringField
• IntegerField
• DecimalField
• DateTimeField
• DictField
• EmbeddedField
• ListField
• LiteralField
• UnionField
• EnumField

Conditional expressions

If you want to use conditional expressions with methods like aggregate, you can call expression.compile() to get a mongo expression.

Document.objects.collection.aggregate([
    {"$match": (Document.age >= 18).compile()},
    {"$group": {"_id": "$field", "count": {"$sum": 1}}},
])

Comparison expressions

• Document.field == value
• Document.field != value
• Document.field > value
• Document.field >= value
• Document.field < value
• Document.field <= value

Logical expressions

• (Document.field == value) & (Document.field == value)
• (Document.field == value) | (Document.field == value)
• ~(Document.field == value)
• ~((Document.field == value) & (Document.field == value))
• ~((Document.field == value) | (Document.field == value))

RawExpression

Sometime, you maybe need use raw query, you can use RawExpression to do that.

from typedmongo.asyncio import RawExpression
# Or `from typedmongo import RawExpression`

User.objects.find(RawExpression({"field_name": {"$mongo_command": value}}) & User.age > 18)

Sort expressions

• +Document.field: Ascending
• -Document.field: Descending

User.objects.find(..., sort=[+User.age, -User.name])

Objects

• Document.objects: The object manager of the Document.
  • collection: The collection of the Document.
  • use_session: Use session for the operations. (Use contextvars, so you don't need to pass the session to the function parameters)
  • use_transaction: Use transaction for the operations.
  • insert_one: Insert one document.
  • insert_many: Insert many documents.
  • find: Find many documents.
  • find_one: Find one document.
  • find_one_and_update: Find one and update.
  • find_one_and_replace: Find one and replace.
  • find_one_and_delete: Find one and delete.
  • delete_one: Delete one document.
  • delete_many: Delete many documents.
  • update_one: Update one document.
  • update_many: Update many documents.
  • count_documents: Count documents.
  • bulk_write: Bulk write operations.