This document introduces APIs, API libraries, and REST APIs in Python covering concepts, request/response cycles, and practical examples using PyCoinGecko and pandas for time series and candlestick charting.
This document explains the HTTP protocol, URL structure, request and response cycles, status codes, and HTTP methods, focusing on REST APIs and their role in web communication and data transfer.
This document explains how to use the Python Requests library for HTTP communication, covering GET and POST requests, query strings, request/response objects, and practical examples for web APIs.
This document explains web scraping using Python, covering HTTP requests, HTML parsing, data extraction, and best practices with requests, BeautifulSoup, and pandas.
This document explores common file formats used in data science, including their structure, advantages, and typical use cases for data storage and exchange.
This document provides a concise overview of Python APIs, data manipulation with Pandas, web scraping, HTTP methods, and file formats, summarizing their practical applications and key concepts for effective Python data science development.