pynamodb 3.3.1

A Pythonic Interface to DynamoDB

A Pythonic interface for Amazon’s DynamoDB that supports Python 2 and 3.

DynamoDB is a great NoSQL service provided by Amazon, but the API is verbose. PynamoDB presents you with a simple, elegant API.

Useful links:

• See the full documentation at https://pynamodb.readthedocs.io/

• Ask questions at Google group

• See release notes at https://pynamodb.readthedocs.io/en/latest/release_notes.html

Installation

From PyPi:

$ pip install pynamodb

From GitHub:

$ pip install git+https://github.com/pynamodb/PynamoDB#egg=pynamodb

Upgrading

Warning

The behavior of ‘UnicodeSetAttribute’ has changed in backwards-incompatible ways as of the 1.6.0 and 3.0.1 releases of PynamoDB.

The following steps can be used to safely update PynamoDB assuming that the data stored in the item’s UnicodeSetAttribute is not JSON. If JSON is being stored, these steps will not work and a custom migration plan is required. Be aware that values such as numeric strings (i.e. “123”) are valid JSON.

When upgrading services that use PynamoDB with tables that contain UnicodeSetAttributes with a version < 1.6.0, first deploy version 1.5.4 to prepare the read path for the new serialization format.

Once all services that read from the tables have been deployed, then deploy version 2.2.0 and migrate your data using the provided convenience methods on the Model. (Note: these methods are only available in version 2.2.0)

def get_save_kwargs(item):
    # any conditional args needed to ensure data does not get overwritten
    # for example if your item has a `version` attribute
    {'version__eq': item.version}

# Re-serialize all UnicodeSetAttributes in the table by scanning all items.
# See documentation of fix_unicode_set_attributes for rate limiting options
# to avoid exceeding provisioned capacity.
Model.fix_unicode_set_attributes(get_save_kwargs)

# Verify the migration is complete
print("Migration Complete? " + Model.needs_unicode_set_fix())

Once all data has been migrated then upgrade to a version >= 3.0.1.

Basic Usage

Create a model that describes your DynamoDB table.

from pynamodb.models import Model
from pynamodb.attributes import UnicodeAttribute

class UserModel(Model):
    """
    A DynamoDB User
    """
    class Meta:
        table_name = "dynamodb-user"
    email = UnicodeAttribute(null=True)
    first_name = UnicodeAttribute(range_key=True)
    last_name = UnicodeAttribute(hash_key=True)

PynamoDB allows you to create the table if needed (it must exist before you can use it!):

UserModel.create_table(read_capacity_units=1, write_capacity_units=1)

Create a new user:

user = UserModel("John", "Denver")
user.email = "[e-mail]"
user.save()

Now, search your table for all users with a last name of ‘John’ and whose first name begins with ‘D’:

for user in UserModel.query("John", first_name__begins_with="D"):
    print(user.first_name)

Examples of ways to query your table with filter conditions:

for user in UserModel.query("John", filter_condition= (UserModel.email=="[e-mail]")):
    print(user.first_name)

for user in UserModel.query("John", UserModel.email=="[e-mail]"):
    print(user.first_name)

# Deprecated, use UserModel.email=="[e-mail]" instead
for user in UserModel.query("John", email__eq="[e-mail]"):
    print(user.first_name)

Retrieve an existing user:

try:
    user = UserModel.get("John", "Denver")
    print(user)
except UserModel.DoesNotExist:
    print("User does not exist")

Advanced Usage

Want to use indexes? No problem:

from pynamodb.models import Model
from pynamodb.indexes import GlobalSecondaryIndex, AllProjection
from pynamodb.attributes import NumberAttribute, UnicodeAttribute

class ViewIndex(GlobalSecondaryIndex):
    class Meta:
        read_capacity_units = 2
        write_capacity_units = 1
        projection = AllProjection()
    view = NumberAttribute(default=0, hash_key=True)

class TestModel(Model):
    class Meta:
        table_name = "TestModel"
    forum = UnicodeAttribute(hash_key=True)
    thread = UnicodeAttribute(range_key=True)
    view = NumberAttribute(default=0)
    view_index = ViewIndex()

Now query the index for all items with 0 views:

for item in TestModel.view_index.query(0):
    print("Item queried from index: {0}".format(item))

It’s really that simple.

Want to use DynamoDB local? Just add a host name attribute and specify your local server.

from pynamodb.models import Model
from pynamodb.attributes import UnicodeAttribute

class UserModel(Model):
    """
    A DynamoDB User
    """
    class Meta:
        table_name = "dynamodb-user"
        host = "http://localhost:8000"
    email = UnicodeAttribute(null=True)
    first_name = UnicodeAttribute(range_key=True)
    last_name = UnicodeAttribute(hash_key=True)

Want to enable streams on a table? Just add a stream_view_type name attribute and specify the type of data you’d like to stream.

from pynamodb.models import Model
from pynamodb.attributes import UnicodeAttribute
from pynamodb.constants import STREAM_NEW_AND_OLD_IMAGE

class AnimalModel(Model):
    """
    A DynamoDB Animal
    """
    class Meta:
        table_name = "dynamodb-user"
        host = "http://localhost:8000"
        stream_view_type = STREAM_NEW_AND_OLD_IMAGE
    type = UnicodeAttribute(null=True)
    name = UnicodeAttribute(range_key=True)
    id = UnicodeAttribute(hash_key=True)

Want to backup and restore a table? No problem.

# Backup the table
UserModel.dump("usermodel_backup.json")

# Restore the table
UserModel.load("usermodel_backup.json")

Features

• Python 3.3, 3.4, 2.6, and 2.7 support

• An ORM-like interface with query and scan filters

• Compatible with DynamoDB Local

• Supports the entire DynamoDB API

• Full table backup/restore

• Support for Unicode, Binary, JSON, Number, Set, and UTC Datetime attributes

• Support for Global and Local Secondary Indexes

• Provides iterators for working with queries, scans, that are automatically paginated

• Automatic pagination for bulk operations

• Complex queries

• Support for Global and Local Secondary Indexes

• Batch operations with automatic pagination

• Iterators for working with Query and Scan operations