1 views collected around this technical thread.
This tutorial walks you through building a Python web‑scraper for Beike (Lianjia) second‑hand property listings, covering session spoofing, dynamic parameters, pagination, multithreaded detail fetching, data cleaning, and exporting results to Excel in a step‑by‑step manner.
This tutorial explains how to use Python to scrape product reviews from JD.com via its AJAX comment API, extract fields such as nickname, score, content, and image count, and save the collected data into a CSV file using the requests and csv modules.
This article explains why proxy IPs are essential for reliable web crawling, compares dynamic and static residential proxies, and provides step‑by‑step Python code to scrape product titles, prices and links from Snapdeal while demonstrating how to integrate proxies for improved efficiency and security.
This article outlines Python's advantages for web crawling, introduces core libraries such as Requests, BeautifulSoup, and Scrapy, details a step-by-step development workflow, provides practical code examples for extracting news titles, and highlights important considerations and advanced techniques for robust scraper implementation.
This article explains the PHP array_column() function introduced in version 5.5, detailing its syntax, parameters, return values, and provides multiple code examples showing how to extract specific keys from multidimensional arrays, including using an index key to create associative arrays.
This tutorial demonstrates how to use Apache Tika in a Java project to parse PDF, Word, and text documents, extract specific fields such as name and ID number, and shows the required Maven dependencies and sample code for performing the extraction.
This article introduces JSONPath as a query language for JSON, explains its core concepts and basic syntax with examples, demonstrates various practical use cases such as data extraction, API testing, and shows tool support across Python, Java, and JavaScript.
This guide shows how to use JSONPath within a Spring Boot 3.4.0 project to efficiently query, filter, and modify complex JSON structures, providing Maven setup, syntax overview, operator tables, and practical code examples for extracting authors, prices, books, and applying custom filters.
This tutorial explains e‑commerce web scraping fundamentals, covering definitions, tool types, data categories, step‑by‑step Python script creation with Requests, BeautifulSoup, and Selenium, provides sample code for Amazon, Walmart, and eBay, discusses challenges like dynamic pages and anti‑scraping measures, and recommends using specialized scraping APIs.
This article compares Python and PHP for web scraping, outlining each language's strengths, ecosystem, performance, learning curve, and community support to help readers decide which tool best fits their project requirements and experience level.
This article demonstrates how to create a reusable PHP function that searches a two‑dimensional array for a specific id and returns the value of a given key, such as the title, using a simple loop and conditional check.
This tutorial shows how to use the jq command‑line tool to extract each user's name from a JSON array, illustrating simple commands such as jq '.users[].name' data.json, describing the author's move from manual IDE methods, and emphasizing the importance of knowing jq exists and leveraging AI to generate scripts from plain‑language descriptions.
Camelot is a Python library that enables users to extract tables from PDF files into pandas DataFrames, offering simple installation via conda or pip, code examples for reading PDFs, exporting to CSV/JSON, and handling merged cells, making PDF data extraction straightforward.
Learn how to quickly scrape Amazon product details such as images, ASIN, name, price, rating, and image URLs by leveraging Google Sheets' ImportFromWeb function, requiring only a few clicks in a spreadsheet without writing any code, and see step‑by‑step instructions with screenshots.
This article walks through a Python web‑scraping project that fetches skin images, names, and prices from Honor of Kings, covering project background, required tools, site analysis, code implementation, data processing, and legal considerations.
This article provides a comprehensive Python tutorial for scraping second‑hand housing community data from Anjuke, covering city selection, URL collection, HTML parsing with lxml, data cleaning, CSV export, and full‑city crawling strategies, complete with runnable code examples.
This article demonstrates how regular expressions can be applied in API automation testing through ten practical Python examples that extract URLs, validate emails, parse JSON, match phone numbers, detect sensitive words, retrieve HTTP status codes, verify dates, parse query parameters, enforce password strength, and extract XML tag content.
This article presents a collection of useful Python scripts—including file sorting, empty‑folder removal, batch renaming, web‑scraping, bulk image downloading, form automation, and various text‑processing utilities—each accompanied by clear explanations and ready‑to‑run code examples.
This tutorial demonstrates how to use the tika-python library to extract textual content from PDF and Excel files, providing code examples and important notes about installation and potential formatting limitations, and suggestions for further processing to obtain readable or structured output.
This article introduces the Scrapeasy Python library, explains how to install it with a single pip command, and demonstrates step‑by‑step code examples for initializing websites, extracting links, images, videos, and other files, highlighting its ease of use for fast web data extraction.