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Showing posts with the label File Formats

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Step-by-Step Guide to Creating an AWS RDS Database Instance

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 Amazon Relational Database Service (AWS RDS) makes it easy to set up, operate, and scale a relational database in the cloud. Instead of managing servers, patching OS, and handling backups manually, AWS RDS takes care of the heavy lifting so you can focus on building applications and data pipelines. In this blog, we’ll walk through how to create an AWS RDS instance , key configuration choices, and best practices you should follow in real-world projects. What is AWS RDS? AWS RDS is a managed database service that supports popular relational engines such as: Amazon Aurora (MySQL / PostgreSQL compatible) MySQL PostgreSQL MariaDB Oracle SQL Server With RDS, AWS manages: Database provisioning Automated backups Software patching High availability (Multi-AZ) Monitoring and scaling Prerequisites Before creating an RDS instance, make sure you have: An active AWS account Proper IAM permissions (RDS, EC2, VPC) A basic understanding of: ...
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Python: How to Work With Various File Formats

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Here is Python logic that shows Parse and Read Different Files in Python. The formats are XML, JSON, CSV, Excel, Text, PDF, Zip files, Images, SQLlite, and Yaml. Python Reading Files import pandas as pd import json import xml.etree.ElementTree as ET from PIL import Image import pytesseract import PyPDF2 from zipfile import ZipFile import sqlite3 import yaml Reading Text Files # Read text file (.txt) def read_text_file(file_path):     with open(file_path, 'r') as file:         text = file.read()     return text Reading CSV Files # Read CSV file (.csv) def read_csv_file(file_path):     df = pd.read_csv(file_path)     return df Reading JSON Files # Read JSON file (.json) def read_json_file(file_path):     with open(file_path, 'r') as file:         json_data = json.load(file)     return json_data Reading Excel Files # Read Excel file (.xlsx, .xls) def read_excel_file(file_path):    ...
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