pydynox 🐍⚙️

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A fast, async-first DynamoDB ORM for Python with a Rust core.

🎉 v1.0 is here! The API is stable and fully async. Production-ready with a Rust core for speed.

Why pydynox?

Py(thon) + Dyn(amoDB) + Ox(ide/Rust)

Key features

  • Async-first - Async by default, sync with sync_ prefix. True non-blocking I/O with Rust's tokio
  • Fast - Rust core for serialization, compression, and encryption. Zero Python runtime dependencies
  • Simple API - Class-based models like PynamoDB. Define once, use everywhere
  • Type-safe - Full type hints for IDE autocomplete and type checkers
  • Pydantic support - Use your existing Pydantic models with DynamoDB
  • Batteries included - TTL, hooks, auto-generate, optimistic locking, rate limiting, encryption, compression, S3 attributes, PartiQL, observability

Installation

pip install pydynox

Optional extras:

pip install pydynox[pydantic]       # Pydantic integration
pip install pydynox[opentelemetry]  # OpenTelemetry tracing

Quick start

Define a model

from pydynox import Model, ModelConfig
from pydynox.attributes import StringAttribute, NumberAttribute

class User(Model):
    model_config = ModelConfig(table="users")
    
    pk = StringAttribute(partition_key=True)
    sk = StringAttribute(sort_key=True)
    name = StringAttribute()
    age = NumberAttribute(default=0)

Async operations (default)

Async methods have no prefix. This is the default.

import asyncio

async def main():
    # Create
    user = User(pk="USER#123", sk="PROFILE", name="John")
    await user.save()

    # Read
    user = await User.get(pk="USER#123", sk="PROFILE")

    # Update
    await user.update(name="Jane", age=30)

    # Query
    async for user in User.query(partition_key="USER#123"):
        print(user.name)

    # Delete
    await user.delete()

asyncio.run(main())

Sync operations (use sync_ prefix)

For scripts, CLI tools, or code that doesn't need async.

# Create
user = User(pk="USER#123", sk="PROFILE", name="John")
user.sync_save()

# Read
user = User.sync_get(pk="USER#123", sk="PROFILE")

# Update
user.sync_update(name="Jane", age=30)

# Query
for user in User.sync_query(partition_key="USER#123"):
    print(user.name)

# Delete
user.sync_delete()

Async-first API

pydynox is async-first. Methods without prefix are async, methods with sync_ prefix are sync.

Async (default) Sync
await model.save() model.sync_save()
await model.delete() model.sync_delete()
await model.update() model.sync_update()
await Model.get() Model.sync_get()
async for x in Model.query() for x in Model.sync_query()
async for x in Model.scan() for x in Model.sync_scan()
await Model.batch_get() Model.sync_batch_get()
async with BatchWriter() with SyncBatchWriter()

Why async? Python's GIL blocks threads during I/O. With async, your app can handle other work while waiting for DynamoDB. pydynox releases the GIL during network calls, so async operations are truly non-blocking.

Conditions

# Save only if item doesn't exist
await user.save(condition=User.pk.not_exists())

# Delete with condition
await user.delete(condition=User.version == 5)

# Combine with & (AND) and | (OR)
await user.save(condition=User.pk.not_exists() | (User.version == 1))

Atomic updates

# Increment
await user.update(atomic=[User.age.add(1)])

# Append to list
await user.update(atomic=[User.tags.append(["verified"])])

# Multiple operations
await user.update(atomic=[
    User.age.add(1),
    User.tags.append(["premium"]),
])

Batch operations

from pydynox import BatchWriter, SyncBatchWriter, DynamoDBClient

client = DynamoDBClient()

# Async (default)
async with BatchWriter(client, "users") as batch:
    for i in range(100):
        batch.put({"pk": f"USER#{i}", "sk": "PROFILE", "name": f"User {i}"})

# Sync
with SyncBatchWriter(client, "users") as batch:
    batch.put({"pk": "USER#1", "sk": "PROFILE", "name": "John"})

Global Secondary Index

from pydynox.indexes import GlobalSecondaryIndex

class User(Model):
    model_config = ModelConfig(table="users")
    
    pk = StringAttribute(partition_key=True)
    email = StringAttribute()
    
    email_index = GlobalSecondaryIndex(
        index_name="email-index",
        partition_key="email",
    )

# Async
async for user in User.email_index.query(partition_key="john@test.com"):
    print(user.name)

# Sync
for user in User.email_index.sync_query(partition_key="john@test.com"):
    print(user.name)

Transactions

from pydynox import DynamoDBClient, Transaction

client = DynamoDBClient()

async with Transaction(client) as tx:
    tx.put("users", {"pk": "USER#1", "sk": "PROFILE", "name": "John"})
    tx.put("orders", {"pk": "ORDER#1", "sk": "DETAILS", "user": "USER#1"})

Pydantic integration

from pydantic import BaseModel, EmailStr
from pydynox import DynamoDBClient
from pydynox.integrations.pydantic import dynamodb_model

client = DynamoDBClient()

@dynamodb_model(table="users", partition_key="pk", sort_key="sk", client=client)
class User(BaseModel):
    pk: str
    sk: str
    name: str
    email: EmailStr

# Async (default)
user = User(pk="USER#123", sk="PROFILE", name="John", email="john@test.com")
await user.save()
user = await User.get(pk="USER#123", sk="PROFILE")

# Sync
user.sync_save()
user = User.sync_get(pk="USER#123", sk="PROFILE")

S3 attribute (large files)

DynamoDB has a 400KB item limit. S3Attribute stores files in S3 and keeps metadata in DynamoDB.

from pydynox.attributes import S3Attribute, S3File

class Document(Model):
    model_config = ModelConfig(table="documents")
    
    pk = StringAttribute(partition_key=True)
    content = S3Attribute(bucket="my-bucket", prefix="docs/")

# Upload
doc = Document(pk="DOC#1")
doc.content = S3File(b"...", name="report.pdf", content_type="application/pdf")
await doc.save()

# Download (async)
data = await doc.content.get_bytes()
await doc.content.save_to("/path/to/file.pdf")
url = await doc.content.presigned_url(3600)

# Download (sync)
data = doc.content.sync_get_bytes()
doc.content.sync_save_to("/path/to/file.pdf")

Table management

# Async (default)
await User.create_table(wait=True)
if await User.table_exists():
    print("Table exists")

# Sync
User.sync_create_table(wait=True)
if User.sync_table_exists():
    print("Table exists")

GenAI contributions 🤖

I believe GenAI is transforming how we build software. It's a powerful tool that accelerates development when used by developers who understand what they're doing.

To support both humans and AI agents, I created:

  • .ai/ folder - Guidelines for agentic IDEs (Cursor, Windsurf, Kiro, etc.)
  • ADR/ folder - Architecture Decision Records for humans to understand the "why" behind decisions

If you're contributing with AI help:

  • Understand what the AI generated before submitting
  • Make sure the code follows the project patterns
  • Test your changes

I reserve the right to reject low-quality PRs where project patterns are not followed and it's clear that GenAI was driving instead of the developer.

Documentation

Full documentation: https://ferrumio.github.io/pydynox

License

Apache 2.0 License

Inspirations

  • PynamoDB - The ORM-style API and model design
  • Pydantic - Data validation patterns
  • dynarust - Rust DynamoDB client patterns
  • dyntastic - Pydantic + DynamoDB integration ideas

Building from source

# Clone
git clone https://github.com/ferrumio/pydynox.git
cd pydynox

# Build (requires Python 3.11+, Rust 1.70+)
pip install maturin
maturin develop

# Test
pip install -e ".[dev]"
pytest

Project links

Data verified by PyPI on Aug 7, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (1.4.0)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for leandro.damascena from gravatar.com leandro.damascena

Credits

Author: Leandro Cavalcante Damascena

GitHub Statistics

Data verified by PyPI on Aug 7, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License

Apache Software License (Apache-2.0)

Requires

Python >=3.11

Provides Extra

opentelemetry pydantic

Tags

dynamodb orm aws rust python

Classifiers

Report project as malware

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1.4.0

17 files

This release

1.3.1 This release

17 files

1.3.0

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1.2.0

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1.1.1

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1.1.0

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1.0.0

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0.27.0

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0.26.0

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0.25.0

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0.24.0

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0.23.0

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0.18.0

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0.16.0

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0.15.0

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0.14.0

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0.13.0

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0.12.0

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0.11.0

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0.10.0

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0.9.0

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0.6.0

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0.5.0

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0.4.0

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0.3.0

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0.2.0

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0.1.1

1 file

0.1.0

1 file

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