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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...

How to Write ETL Logic in Python: Sample Code to Practice

Here's an example Python code that uses the mysql-connector library to connect to a MySQL database, extract data from a table, transform it, and load it as a JSON file. Here's an example:







Python ETL Sample Code


import mysql.connector

import json


# Connect to the MySQL database

cnx = mysql.connector.connect(user='username', password='password',

                              host='localhost',

                              database='database_name')


# Define a cursor to execute SQL queries

cursor = cnx.cursor()


# Define the SQL query to extract data

query = ("SELECT column1, column2, column3 FROM table_name")


# Execute the SQL query

cursor.execute(query)


# Fetch all rows from the result set

rows = cursor.fetchall()


# Transform the rows into a list of dictionaries

result = []

for row in rows:

    result.append({'column1': row[0], 'column2': row[1], 'column3': row[2]})


# Save the result as a JSON file

with open('output.json', 'w') as outfile:

    json.dump(result, outfile)


# Close the cursor and database connection

cursor.close()

cnx.close()

In this example, you will need to replace username, password, localhost, database_name, table_name, column1, column2, and column3 with the appropriate values for your MySQL database and table. 


The code will extract the data from the specified table, transform it into a list of dictionaries, and save it as a JSON file named output.json.

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