from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
element = WebDriverWait(driver, 10).until(
EC.presence_of_element_located((By.ID, "myDynamicElement"))
)
• Get the page source after JavaScript has executed.
dynamic_html = driver.page_source
• Close the browser window.
driver.quit()
VII. Common Tasks & Best Practices
• Handle pagination by finding the "Next" link.
next_page_url = soup.find('a', text='Next')['href']• Save data to a CSV file.
import csv
with open('data.csv', 'w', newline='', encoding='utf-8') as f:
writer = csv.writer(f)
writer.writerow(['Title', 'Link'])
# writer.writerow([title, url]) in a loop
• Save data to CSV using
pandas.import pandas as pd
df = pd.DataFrame(data, columns=['Title', 'Link'])
df.to_csv('data.csv', index=False)
• Use a proxy with
requests.proxies = {'http': 'http://10.10.1.10:3128', 'https': 'http://10.10.1.10:1080'}
requests.get('http://example.com', proxies=proxies)• Pause between requests to be polite.
import time
time.sleep(2) # Pause for 2 seconds
• Handle JSON data from an API.
json_response = requests.get('https://api.example.com/data').json()• Download a file (like an image).
img_url = 'http://example.com/image.jpg'
img_data = requests.get(img_url).content
with open('image.jpg', 'wb') as handler:
handler.write(img_data)
• Parse a
sitemap.xml to find all URLs.# Get the sitemap.xml file and parse it like any other XML/HTML to extract <loc> tags.
VIII. Advanced Frameworks (
Scrapy)• Create a Scrapy spider (conceptual command).
scrapy genspider example example.com
• Define a
parse method to process the response.# In your spider class:
def parse(self, response):
# parsing logic here
pass
• Extract data using Scrapy's CSS selectors.
titles = response.css('h1::text').getall()• Extract data using Scrapy's XPath selectors.
links = response.xpath('//a/@href').getall()• Yield a dictionary of scraped data.
yield {'title': response.css('title::text').get()}• Follow a link to parse the next page.
next_page = response.css('li.next a::attr(href)').get()
if next_page is not None:
yield response.follow(next_page, callback=self.parse)• Run a spider from the command line.
scrapy crawl example -o output.json
• Pass arguments to a spider.
scrapy crawl example -a category=books
• Create a Scrapy Item for structured data.
import scrapy
class ProductItem(scrapy.Item):
name = scrapy.Field()
price = scrapy.Field()
• Use an Item Loader to populate Items.
from scrapy.loader import ItemLoader
loader = ItemLoader(item=ProductItem(), response=response)
loader.add_css('name', 'h1.product-name::text')
#Python #WebScraping #BeautifulSoup #Selenium #Requests
━━━━━━━━━━━━━━━
By: @DataScienceN ✨
❤3
🔥 Trending Repository: localstack
📝 Description: 💻 A fully functional local AWS cloud stack. Develop and test your cloud & Serverless apps offline
🔗 Repository URL: https://github.com/localstack/localstack
🌐 Website: https://localstack.cloud
📖 Readme: https://github.com/localstack/localstack#readme
📊 Statistics:
🌟 Stars: 61.1K stars
👀 Watchers: 514
🍴 Forks: 4.3K forks
💻 Programming Languages: Python - Shell - Makefile - ANTLR - JavaScript - Java
🏷️ Related Topics:
==================================
🧠 By: https://t.me/DataScienceM
📝 Description: 💻 A fully functional local AWS cloud stack. Develop and test your cloud & Serverless apps offline
🔗 Repository URL: https://github.com/localstack/localstack
🌐 Website: https://localstack.cloud
📖 Readme: https://github.com/localstack/localstack#readme
📊 Statistics:
🌟 Stars: 61.1K stars
👀 Watchers: 514
🍴 Forks: 4.3K forks
💻 Programming Languages: Python - Shell - Makefile - ANTLR - JavaScript - Java
🏷️ Related Topics:
#python #testing #aws #cloud #continuous_integration #developer_tools #localstack
==================================
🧠 By: https://t.me/DataScienceM
🔥 Trending Repository: TrendRadar
📝 Description: 🎯 告别信息过载,AI 助你看懂新闻资讯热点,简单的舆情监控分析 - 多平台热点聚合+基于 MCP 的AI分析工具。监控35个平台(抖音、知乎、B站、华尔街见闻、财联社等),智能筛选+自动推送+AI对话分析(用自然语言深度挖掘新闻:趋势追踪、情感分析、相似检索等13种工具)。支持企业微信/飞书/钉钉/Telegram/邮件/ntfy推送,30秒网页部署,1分钟手机通知,无需编程。支持Docker部署⭐ 让算法为你服务,用AI理解热点
🔗 Repository URL: https://github.com/sansan0/TrendRadar
🌐 Website: https://github.com/sansan0
📖 Readme: https://github.com/sansan0/TrendRadar#readme
📊 Statistics:
🌟 Stars: 6K stars
👀 Watchers: 21
🍴 Forks: 4.5K forks
💻 Programming Languages: Python - HTML - Batchfile - Shell - Dockerfile
🏷️ Related Topics:
==================================
🧠 By: https://t.me/DataScienceM
📝 Description: 🎯 告别信息过载,AI 助你看懂新闻资讯热点,简单的舆情监控分析 - 多平台热点聚合+基于 MCP 的AI分析工具。监控35个平台(抖音、知乎、B站、华尔街见闻、财联社等),智能筛选+自动推送+AI对话分析(用自然语言深度挖掘新闻:趋势追踪、情感分析、相似检索等13种工具)。支持企业微信/飞书/钉钉/Telegram/邮件/ntfy推送,30秒网页部署,1分钟手机通知,无需编程。支持Docker部署⭐ 让算法为你服务,用AI理解热点
🔗 Repository URL: https://github.com/sansan0/TrendRadar
🌐 Website: https://github.com/sansan0
📖 Readme: https://github.com/sansan0/TrendRadar#readme
📊 Statistics:
🌟 Stars: 6K stars
👀 Watchers: 21
🍴 Forks: 4.5K forks
💻 Programming Languages: Python - HTML - Batchfile - Shell - Dockerfile
🏷️ Related Topics:
#python #docker #mail #news #telegram_bot #mcp #data_analysis #trending_topics #wechat_robot #dingtalk_robot #ntfy #hot_news #feishu_robot #mcp_server
==================================
🧠 By: https://t.me/DataScienceM
🔥 Trending Repository: LEANN
📝 Description: RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private RAG application on your personal device.
🔗 Repository URL: https://github.com/yichuan-w/LEANN
📖 Readme: https://github.com/yichuan-w/LEANN#readme
📊 Statistics:
🌟 Stars: 3.9K stars
👀 Watchers: 34
🍴 Forks: 403 forks
💻 Programming Languages: Python
🏷️ Related Topics:
==================================
🧠 By: https://t.me/DataScienceM
📝 Description: RAG on Everything with LEANN. Enjoy 97% storage savings while running a fast, accurate, and 100% private RAG application on your personal device.
🔗 Repository URL: https://github.com/yichuan-w/LEANN
📖 Readme: https://github.com/yichuan-w/LEANN#readme
📊 Statistics:
🌟 Stars: 3.9K stars
👀 Watchers: 34
🍴 Forks: 403 forks
💻 Programming Languages: Python
🏷️ Related Topics:
#python #privacy #ai #offline_first #localstorage #vectors #faiss #rag #vector_search #vector_database #llm #langchain #llama_index #retrieval_augmented_generation #ollama #gpt_oss
==================================
🧠 By: https://t.me/DataScienceM
🔥 Trending Repository: PythonRobotics
📝 Description: Python sample codes and textbook for robotics algorithms.
🔗 Repository URL: https://github.com/AtsushiSakai/PythonRobotics
🌐 Website: https://atsushisakai.github.io/PythonRobotics/
📖 Readme: https://github.com/AtsushiSakai/PythonRobotics#readme
📊 Statistics:
🌟 Stars: 26.3K stars
👀 Watchers: 509
🍴 Forks: 7K forks
💻 Programming Languages: Python
🏷️ Related Topics:
==================================
🧠 By: https://t.me/DataScienceM
📝 Description: Python sample codes and textbook for robotics algorithms.
🔗 Repository URL: https://github.com/AtsushiSakai/PythonRobotics
🌐 Website: https://atsushisakai.github.io/PythonRobotics/
📖 Readme: https://github.com/AtsushiSakai/PythonRobotics#readme
📊 Statistics:
🌟 Stars: 26.3K stars
👀 Watchers: 509
🍴 Forks: 7K forks
💻 Programming Languages: Python
🏷️ Related Topics:
#python #algorithm #control #robot #localization #robotics #mapping #animation #path_planning #slam #autonomous_driving #autonomous_vehicles #ekf #hacktoberfest #cvxpy #autonomous_navigation
==================================
🧠 By: https://t.me/DataScienceM
• Error Handling: Always wrap dispatch logic in
• Security: Never hardcode credentials directly in scripts. Use environment variables (
• Rate Limits: SMTP servers impose limits on the number of messages one can send per hour or day. Implement pauses (
• Opt-Outs: For promotional dispatches, ensure compliance with regulations (like GDPR, CAN-SPAM) by including clear unsubscribe options.
Concluding Thoughts
Automating electronic message dispatch empowers users to scale their communication efforts with remarkable efficiency. By leveraging Python's native capabilities, anyone can construct a powerful, flexible system for broadcasting anything from routine updates to extensive promotional campaigns. The journey into programmatic dispatch unveils a world of streamlined operations and enhanced communicative reach.
#python #automation #email #smtplib #emailautomation #programming #scripting #communication #developer #efficiency
━━━━━━━━━━━━━━━
By: @DataScienceN ✨
try-except blocks to gracefully handle network issues, authentication failures, or incorrect receiver addresses.• Security: Never hardcode credentials directly in scripts. Use environment variables (
os.environ.get()) or a secure configuration management system. Ensure starttls() is called for encrypted communication.• Rate Limits: SMTP servers impose limits on the number of messages one can send per hour or day. Implement pauses (
time.sleep()) between dispatches to respect these limits and avoid being flagged as a spammer.• Opt-Outs: For promotional dispatches, ensure compliance with regulations (like GDPR, CAN-SPAM) by including clear unsubscribe options.
Concluding Thoughts
Automating electronic message dispatch empowers users to scale their communication efforts with remarkable efficiency. By leveraging Python's native capabilities, anyone can construct a powerful, flexible system for broadcasting anything from routine updates to extensive promotional campaigns. The journey into programmatic dispatch unveils a world of streamlined operations and enhanced communicative reach.
#python #automation #email #smtplib #emailautomation #programming #scripting #communication #developer #efficiency
━━━━━━━━━━━━━━━
By: @DataScienceN ✨
🔥 Trending Repository: Memori
📝 Description: Open-Source Memory Engine for LLMs, AI Agents & Multi-Agent Systems
🔗 Repository URL: https://github.com/GibsonAI/Memori
🌐 Website: https://memorilabs.ai
📖 Readme: https://github.com/GibsonAI/Memori#readme
📊 Statistics:
🌟 Stars: 2.3K stars
👀 Watchers: 18
🍴 Forks: 216 forks
💻 Programming Languages: Python - PLpgSQL
🏷️ Related Topics:
==================================
🧠 By: https://t.me/DataScienceM
📝 Description: Open-Source Memory Engine for LLMs, AI Agents & Multi-Agent Systems
🔗 Repository URL: https://github.com/GibsonAI/Memori
🌐 Website: https://memorilabs.ai
📖 Readme: https://github.com/GibsonAI/Memori#readme
📊 Statistics:
🌟 Stars: 2.3K stars
👀 Watchers: 18
🍴 Forks: 216 forks
💻 Programming Languages: Python - PLpgSQL
🏷️ Related Topics:
#python #agent #awesome #state_management #ai #memory #memory_management #hacktoberfest #long_short_term_memory #rag #llm #memori_ai #hacktoberfest2025 #chatgpt #aiagent
==================================
🧠 By: https://t.me/DataScienceM
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If you love tools that save time, money, and nerves — this is 100% for you.
This is an open-source panel on Python + Streamlit, packed with a whole arsenal of useful automations.
You open it — and it’s like gaining a superpower: doing everything faster.
What it can do:
🗞 News Reader — reads out current news.
And that’s just part of the list.
Why do you need this?
git clone https://github.com/Ai-Quill/automated.git
cd automated
pip install -r requirements.txt
streamlit run app.py
http://localhost:8501And enjoy the panel where all tools are just one click away.
#python #soft #github
https://t.me/DataScienceN
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