Hands on Lab Learning DynamoDB with Python Library PynamoDB¶
Tutorials¶
- Very Quick Overview on DynamoDB in 8 Minutes
- https://www.youtube.com/watch?v=kxAOskUGuw8
- Learn AWS DynamoDB in a easy Way in 55 Minutes | Indexes | Partition | Boto3
- https://www.youtube.com/watch?v=doocp3IMOWA
PynamoDB¶
PynamoDB is a Pythonic interface to Amazon’s DynamoDB. By using simple, yet powerful abstractions over the DynamoDB API, PynamoDB allows you to start developing immediately.
Python 3 support
- Support for Unicode, Binary, JSON, Number, Set, and UTC Datetime attributes
- Support for DynamoDB Local
- Support for all of the DynamoDB API
- Support for Global and Local Secondary Indexes
- Batch operations with automatic pagination
- Iterators for working with Query and Scan operations
- Fully tested
In [106]:
import os
import boto3
import json
from faker import Faker
import random
import pynamodb.attributes as at
import datetime
from datetime import datetime
from pynamodb.models import Model
from pynamodb.attributes import *
In [137]:
AWS_ACCESS_KEY = "XXX"
AWS_SECRET_KEY = "XXXXX"
AWS_REGION_NAME = "us-east-1"
Why PynamoDB?¶
It all started when author needed to use Global Secondary Indexes, a new and powerful feature of DynamoDB. I quickly realized that my go to library, dynamodb-mapper, didn’t support them. In fact, it won’t be supporting them anytime soon because dynamodb-mapper relies on another library, boto.dynamodb, which itself won’t support them. In fact, boto doesn’t support Python 3 either. If you want to know more, I blogged about it.
Installation¶
pip install pynamodb
In [108]:
!pip install pynamodb
In [109]:
faker = Faker()
Creating Model¶
In [124]:
class UserModel(Model):
class Meta:
table_name = 'youtube_tut'
aws_access_key_id = AWS_ACCESS_KEY
aws_secret_access_key = AWS_SECRET_KEY
email = UnicodeAttribute(null=True)
first_name = UnicodeAttribute(range_key=True)
last_name = UnicodeAttribute(hash_key=True)
Creating DynamoDB tables with pynamodb¶
- PROVISIONED
In [125]:
UserModel.create_table(
read_capacity_units=4,
write_capacity_units=4,
billing_mode='PROVISIONED')
- PAY_PER_REQUEST
In [ ]:
UserModel.create_table(billing_mode='PAY_PER_REQUEST')
Insert Item¶
In [126]:
UserModel(
email='test@gmail.com',
first_name='test',
last_name='test name'
).save()
Out[126]:
In [127]:
average = []
for i in range(1, 20):
starttime = datetime.now()
UserModel(email=faker.email(), first_name=faker.first_name(), last_name=faker.last_name()).save()
endtime = datetime.now()
delta = endtime-starttime
elapsed_time = int((delta.seconds * 1000) + (delta.microseconds / 1000))
average.append(elapsed_time)
print("Exection Time: {} MS ".format(elapsed_time))
averagetime = sum(average)/ len(average)
print("\nAverage Time in MS: {} ".format(averagetime))
Batch Inserts¶
In [46]:
bulk_items = [UserModel(
email=faker.email(),
first_name=faker.first_name(),
last_name=faker.last_name()
)
for i in range(1, 20)]
In [48]:
with UserModel.batch_write() as batch:
for item in bulk_items:
batch.save(item)
Query Partition Key¶
In [128]:
for user in UserModel.query("Cooper"):
print(user.email)
Querying Partition key and then by Sort Key¶
In [129]:
for user in UserModel.query("Cooper", UserModel.first_name.startswith("C")):
print(user.email)
Scan query¶
In [130]:
for item in UserModel.scan(UserModel.email.startswith('j'), limit=2):
print(item.email)
Update based on partition key¶
In [131]:
for user in UserModel.query("Cooper"):
user.email = "change email address"
user.save()
In [133]:
for user in UserModel.query("Cooper"):
print(user.email)
Deleting based on Partition key¶
In [134]:
for user in UserModel.query("Cooper"):
user.delete()
In [135]:
for user in UserModel.query("Cooper"):
print(user.email)
Delete table¶
In [136]:
UserModel.delete_table()
Out[136]:
