pydynamodb

PyDynamoDB

PyDynamoDB is a Python DB API 2.0 (PEP 249) client for Amazon DynamoDB. SQLAlchemy dialect supported as well.

Objectives

PyDynamoDB implement the DB API 2.0 interfaces based on PartiQL supported by AWS DynamoDB. Although PartiQL can only support DML operations (INSERT, UPDATE, DELETE, SELECT), PyDynamoDB extended the capabilities to support DDL as well. Now you are able to use MySQL-like statements to CREATE/ALTER/DROP tables. Besides DDL statements, some of utility statements are allowed to execute (Such as, List and Describe Table). PyDynamodb provide parameters and result_set converter to make you easily manipulate operations with Python built-in types. Transaction is also partially supported with DB standard operations, like begin() and commit().

Features

Compatible with DB API 2.0 Specification
PartiQL for DML operations (INSERT, UPDATE, DELETE, SELECT)
Limit supported in SELECT statement
Extra type conversion and string functions supported in SELECT statement
Column alias supported in SELECT statement
MySQL-Like statements for DDL operations (CREATE TABLE, ALTER TABLE, DROP TABLE)
MySQL-Like statements for Utility operations (LIST/SHOW TABLES, DESC TABLE)
Auto data type conversion for parameters and result set (Including date and datetime)
Transaction and Batch operations
SQLAlchemy dialect provided
Compatible for Superset SQL Lab and graphing

Requirements

Python
- CPython 3.9 3.10 3.11 3.12 3.13 3.14

Dependencies

Boto3 (Python SDK for AWS Services)
- boto3 >= 1.21.0
- botocore >= 1.24.7
Tenacity (Retry Utility for API calling)
- tenacity >= 4.1.0
SQLAlchemy (The ORM Toolkit for Python, only required if using PyDynamoDB Dialect)
- SQLAlchemy >= 1.0.0
Pyparsing (The approach to creating and executing simple grammars)
- pyparsing >= 3.0.0

Installation

pip install pydynamodb

Guidances

To get more documentation, please visit: PyDynamoDB WIKI.

Basic usage

from pydynamodb import connect

cursor = connect(aws_access_key_id="aws_access_key_id",
                aws_secret_access_key="aws_secret_access_key",
                region_name="region_name").cursor()
cursor.execute('SELECT * FROM "ddb_table_name"')
print(cursor.fetchall())

Cursor iteration

from pydynamodb import connect

cursor = connect(aws_access_key_id="aws_access_key_id",
                aws_secret_access_key="aws_secret_access_key",
                region_name="region_name").cursor()
cursor.execute('SELECT * FROM "ddb_table_name"')
rows = cursor.fetchall()
for row in rows:
    print(row)

Query with parameters

PyDynamoDB is able to serialize the parameters which passed to DDB and deserialize the response to Python built-in types.

from pydynamodb import connect
from datetime import date, datetime
cursor = connect(aws_access_key_id="aws_access_key_id",
                aws_secret_access_key="aws_secret_access_key",
                region_name="region_name").cursor()
cursor.execute("""INSERT INTO "ddb_table_name" VALUE {
                    'partition_key' = ?, 'sort_key' = ?, 'col_str' = ?,
                    'col_num' = ?, 'col_byte' = ?, 'col_ss' = ?,
                    'col_ns' = ?, 'col_bs' = ?, 'col_list' = ?,
                    'col_map' = ?, 'col_nested' = ?,
                    'col_date' = ?, 'col_datetime' = ?
                }""", ["pkey_value", "skey_value", "str", 100, b"ABC", # String, Number, Bytes
                        {"str", "str"}, {100, 100}, {b"A", b"B"}, # String/Numnber/Bytes Set
                        ["str", 100, b"ABC"],  # List
                        {"key1": "val", "key2": "val"}, # Map
                        ["str", 100, {"key1": "val"}], # Nested Structure
                        date(2022, 10, 18), datetime(2022, 10, 18, 13, 55, 34), # Date and Datetime Type
                    ])

cursor.execute('SELECT * FROM "ddb_table_name" WHERE partition_key = ?', ["key_value"])
print(cursor.fetchall())

License

PyDynamoDB is distributed under the MIT license.

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