Get All Items from DynamoDB in Python (boto3)

There is no "select all" in DynamoDB — reading a whole table means a scan you paginate to the end. Each response carries at most 1 MB; boto3's built-in scan paginator follows LastEvaluatedKey across every page for you.

Code

import boto3

client = boto3.client("dynamodb")

paginator = client.get_paginator("scan")

items = []
for page in paginator.paginate(TableName="Music"):
    items.extend(page["Items"])

print(f"Table holds {len(items)} items")

Explanation

• The paginator is the point — a single scan call does NOT return the table; it returns up to 1 MB. client.get_paginator("scan") issues follow-up requests (feeding LastEvaluatedKey back as ExclusiveStartKey) until the table is exhausted — the loop people forget when they wonder why items are "missing". (Doing it by hand? Keep calling while the response contains a LastEvaluatedKey.)
• Memory — items holds the entire table. For big tables, process each page inside the loop (write to a file, stream, aggregate) instead of accumulating.
• Faster on big tables: parallel scan — pass Segment=i, TotalSegments=N and run N workers (threads/processes), each paginating its own segment. Same total cost, much lower wall-clock time.
• Cost — a full scan reads (and bills) every byte of every item, every time you run it. ProjectionExpression shrinks the response, not the bill; don't put a scan on a hot path — that's what query and access-pattern design are for.
• Items return in DynamoDB JSON ({"S": ...}). Prefer native Python types? Use the resource API (table.scan + a manual LastEvaluatedKey loop — the resource API has no paginator).

Do it visually

Eyeballing a table doesn't need a script: download DynoTable to browse any table in a paginated grid — it pages through scans for you, no loop to get wrong. And before you scan-and-pay, the DynamoDB pricing calculator shows what a full read of your table actually costs.

Related examples

• Get all items in Node.js — the same full read with an explicit loop.
• Get all items with the AWS CLI — the CLI pages for you.
• DynamoDB Scan in Python — scanning with a FilterExpression.
• Parallel scans — Segment/TotalSegments, worker counts, and when to bother.
• Why is my DynamoDB Scan slow and expensive? — the cost model and how to avoid it.
• DynamoDB ProvisionedThroughputExceededException — reading the whole table is the classic way to hit it.
• "The provided starting key is invalid" — a mangled resume key in the pagination loop.

References

• Scan — Amazon DynamoDB API Reference
• DynamoDB.Paginator.Scan — Boto3 documentation
• Scanning tables in DynamoDB — Amazon DynamoDB Developer Guide
• DynamoDB read and write operations (capacity unit consumption) — Amazon DynamoDB Developer Guide

Last verified 2026-07-13 against the official AWS documentation linked above.