TGTGInsighttelegram intelligenceLIVE / telegram public index
← Python Заметки

TGINSIGHT SIMILAR POSTS

Најди сличен содржај

Изворен канал @pythonotes · Post #61 · 2 апр.

Ранее я уже упоминал о другой фишке из ˍˍfutureˍˍ , это оператор деления. from __future__ import division Суть проста. Раньше сложность типа данных результата поределялась типом самого сложного операнда. Например: int/int => int int/float => float В первом случае оба операнда int, значит и результат будет int. Во втором float более сложный тип, поэтому результат будет float. Если нам требуется получить дробное значение при делении двух int то приходилось форсированно один из операндов конверировать в float. 12/float(5) => float Но с новой "философией" это не требуется. В Python3 "floor division" заменили на "true division" а старый способ теперь работает через оператор "//". >>> 3/2 1.5 >>> 3//2 1 То есть теперь деление int на int даёт float если результат не целое число. В классах теперь доступны методы __floordiv__() и __truediv__() для определения поведения с этими операторами. Данный переход описан в PEP238. #pep#2to3#basic

Резултати

Пронајдени 3 слични објави

Пребарај: #crawling

当前筛选 #crawling清除筛选
GitHub Trends

@githubtrending · Post #14786 · 04.06.2025 г., 12:00

#python#crawler#crawling#framework#hacktoberfest#python#scraping#web_scraping#web_scraping_python Scrapy is a powerful tool for extracting data from websites. It works on many platforms and requires Python 3.9 or higher. Scrapy is free, stable, and can handle complex tasks efficiently. It allows you to manage multiple requests at once, making it fast and efficient for large-scale data extraction. Scrapy also supports various formats for storing data and has features like auto-throttling to prevent overwhelming websites. This makes it a great choice for users who need to collect data from many websites quickly and reliably. https://github.com/scrapy/scrapy

Repositorio data science

@repo_science · Post #3180 · 12.05.2023 г., 19:53

#webScraping#Python#Scrapy 🐍 Scrapy course - Python web scraping for beginners The Scrapy #Beginners Course will teach you everything you need to learn to start scraping websites at scale using #Python Scrapy. Topics - Creating your first #Scrapy spider - #Crawling through websites & scraping data from each page - Cleaning data with Items & Item Pipelines - Saving data to CSV files, #MySQL & #Postgres#databases - Using fake #user-agents & headers to avoid getting blocked - Using #proxies to scale up your web scraping without getting banned - Deploying your #scraper to the cloud & scheduling it to run periodically 🗣️ Joe Kearney. 🔗Link 📢#youtube ⭐️ Resources ⭐️ Course Resources - Scrapy Docs - Course Guide - Course Github - The Python Scrapy Playbook ----- Main channel: @repo_science Coupons: @freecoupons_reposcience -----

GitHub Trends

@githubtrending · Post #15520 · 24.02.2026 г., 14:30

#python#ai#ai_scraping#automation#crawler#crawling#crawling_python#data#data_extraction#mcp#mcp_server#playwright#python#scraping#selectors#stealth#web_scraper#web_scraping#web_scraping_python#webscraping#xpath Scrapling is a fast Python web scraping tool that fetches pages, bypasses anti-bot blocks like Cloudflare, and adapts to site changes by auto-finding elements. Use simple CSS/XPath selectors, spiders for big crawls with pause/resume, proxy rotation, and CLI—no code needed sometimes. Install via pip; it's memory-light and beats others in speed. You save time fixing broken scrapers, scrape reliably at scale, cut costs with AI tools, and focus on using data for leads, prices, or research. https://github.com/D4Vinci/Scrapling