This article will show you how to store rows of a Pandas DataFrame in DynamoDB using the batch write operations.
First, we have to create a DynamoDB client:
import boto3
dynamodb = boto3.resource('dynamodb', aws_access_key_id='', aws_secret_access_key='')
table = dynamodb.Table('table_name')
When the connection handler is ready, we must create a batch writer using the with statement:
with table.batch_writer() as batch:
pass # we will change that
Now, we can create an iterator over the Pandas DataFrame inside the with block:
with table.batch_writer() as batch:
for index, row in df.iterrows():
pass # to be changed
We will extract the fields we want to store in DynamoDB and put them in a dictionary in the loop:
with table.batch_writer() as batch:
for index, row in df.iterrows():
content = {
'field_A', row['A'],
'field_B', row['B']
}
# there is still something missing
In the end, we use the put_item function to add the item to the batch:
with table.batch_writer() as batch:
for index, row in df.iterrows():
content = {
'field_A', row['A'],
'field_B', row['B']
}
batch.put_item(Item=content)
When our code exits the with block, the batch writer will send the data to DynamoDB.