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How to Read a CSV File from Amazon S3 Using Python (With Headers and Rows Displayed)

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  Introduction If you’re working with cloud data, especially on AWS, chances are you’ll encounter data stored in CSV files inside an Amazon S3 bucket . Whether you're building a data pipeline or a quick analysis tool, reading data directly from S3 in Python is a fast, reliable, and scalable way to get started. In this blog post, we’ll walk through: Setting up access to S3 Reading a CSV file using Python and Boto3 Displaying headers and rows Tips to handle larger datasets Let’s jump in! What You’ll Need An AWS account An S3 bucket with a CSV file uploaded AWS credentials (access key and secret key) Python 3.x installed boto3 and pandas libraries installed (you can install them via pip) pip install boto3 pandas Step-by-Step: Read CSV from S3 Let’s say your S3 bucket is named my-data-bucket , and your CSV file is sample-data/employees.csv . ✅ Step 1: Import Required Libraries import boto3 import pandas as pd from io import StringIO boto3 is...
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A Quick guide to Amazon RDS

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Amazon Aurora is a MySQL-compatible relational database management system (RDBMS) that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases.

It provides up to 5X the performance of MySQL at one tenth the cost of a commercial database. Amazon Aurora allows you to encrypt data at rest as well as in transit for your mission-critical workloads.

Key points on Amazon Aurora


  1. Amazon Aurora is a relational database engine that combines the speed and reliability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. It delivers up to five times the throughput of standard MySQL running on the same hardware.
  2. Amazon Aurora is designed to be compatible with MySQL 5.6, so that existing MySQL applications and tools can run without requiring modification. 
  3. Amazon Aurora joins MySQL, Oracle, Microsoft SQL Server, and PostgreSQL as the fifth database engine available to customers through Amazon RDS. 
  4. Amazon RDS handles time-consuming tasks such as provisioning, patching, backup, recovery, failure detection, and repair. You pay a simple monthly charge for each Amazon Aurora database instance you use. There are no upfront costs or long-term commitments.

What is RDS on Amazon Aurora

Amazon RDS makes it easy to manage your Amazon Aurora database by automating most of the common administrative tasks associated with running a database. 

With a few clicks in the AWS Management Console, you can quickly launch an Amazon Aurora database instance. Amazon Aurora scales storage automatically, growing storage and rebalancing I/Os to provide consistent performance without the need for over-provisioning.

For example, you can start with a database of 10GB and have it automatically grow up to 64TB without requiring availability disruptions to resize or restripe data.

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