Code With Python
39K subscribers
841 photos
24 videos
22 files
746 links
This channel delivers clear, practical content for developers, covering Python, Django, Data Structures, Algorithms, and DSA – perfect for learning, coding, and mastering key programming skills.
Admin: @HusseinSheikho || @Hussein_Sheikho
Download Telegram
πŸ“• Think Python, 3rd Edition: Master Python Programming with Jupyter Notebooks! 🐍⭐️

#Python #LearnPython #Coding #JupyterNotebooks #OpenSource #FreeLearning #DataScience #Programming #TechEducation #AllenDowney #ThinkPython

β˜„οΈ Why This Book?
- Learn by Doing: Perfect for beginners and coders upgrading to Python 3! Hands-on examples, exercises, and projects.
- Jupyter Notebook Edition: Entire book redesigned as interactive notebooks! Run code, visualize results, and experiment live.
- Free & Open Source: Licensed under CC BY-NC-SAβ€”download, share, and contribute!
- From a Pro: Authored by Allen Downey, computer science professor and creator of the legendary *Think Series* (*Think Stats*, *Think Bayes*).
- Clear & Engaging: Simplifies complex concepts with humor and real-world analogies.

πŸ“ˆ New in the 3rd Edition:
- Updated for modern Python 3 practices.
- Fully integrated Jupyter notebooks for interactive learning.
- Expanded exercises and case studies.

πŸ‘©β€πŸ’» Perfect For:
- New programmers starting with Python.
- Educators teaching coding or data science.
- Data enthusiasts who want to code smarter.

πŸ”— Get It Now:
πŸ‘‰ Web Version: https://allendowney.github.io/ThinkPython/

πŸ§‘β€πŸ’» GitHub Repo: https://github.com/AllenDowney/ThinkPython3

#Python3 #CodeForFree #InteractiveLearning β€” Unlock Python’s power, one notebook at a time! β­οΈπŸ‘©β€πŸ’»

https://t.me/CodeProgrammer ⭐️

Use ⭐️ Emoji to support us ❀️
Please open Telegram to view this post
VIEW IN TELEGRAM
πŸ‘9❀1
# Interview Power Move: Parallel Merging
from concurrent.futures import ThreadPoolExecutor
from PyPDF2 import PdfMerger

def parallel_merge(pdf_list, output, max_workers=4):
chunks = [pdf_list[i::max_workers] for i in range(max_workers)]
temp_files = []

def merge_chunk(chunk, idx):
temp = f"temp_{idx}.pdf"
merger = PdfMerger()
for pdf in chunk:
merger.append(pdf)
merger.write(temp)
return temp

with ThreadPoolExecutor() as executor:
temp_files = list(executor.map(merge_chunk, chunks, range(max_workers)))

# Final merge of chunks
final_merger = PdfMerger()
for temp in temp_files:
final_merger.append(temp)
final_merger.write(output)

parallel_merge(["doc1.pdf", "doc2.pdf", ...], "parallel_merge.pdf")


# Pro Tip: Validate PDFs before merging
from PyPDF2 import PdfReader

def is_valid_pdf(path):
try:
with open(path, "rb") as f:
reader = PdfReader(f)
return len(reader.pages) > 0
except:
return False

valid_pdfs = [f for f in pdf_files if is_valid_pdf(f)]
merger.append(valid_pdfs) # Only merge valid files


# Real-World Case Study: Invoice Processing Pipeline
import glob
from PyPDF2 import PdfMerger

def process_monthly_invoices():
# 1. Download invoices from SFTP
download_invoices("sftp://vendor.com/invoices/*.pdf")

# 2. Validate and sort
invoices = sorted(
[f for f in glob.glob("invoices/*.pdf") if is_valid_pdf(f)],
key=lambda x: extract_invoice_date(x)
)

# 3. Merge with cover page
merger = PdfMerger()
merger.append("cover_template.pdf")
for inv in invoices:
merger.append(inv, outline_item=get_client_name(inv))

# 4. Add metadata and encrypt
merger.add_metadata({"/InvoiceCount": str(len(invoices))})
merger.encrypt(owner_pwd="finance_team_2023")
merger.write(f"Q3_Invoices_{datetime.now().strftime('%Y%m')}.pdf")

# 5. Upload to secure storage
upload_to_s3("secure-bucket/processed/", "Q3_Invoices.pdf")

process_monthly_invoices()


By: https://t.me/DataScience4

#Python #PDFProcessing #DocumentAutomation #PyPDF2 #CodingInterview #BackendDevelopment #FileHandling #DataEngineering #TechJobs #Programming #SystemDesign #DeveloperTips #CareerGrowth #CloudComputing #Docker #Microservices #Productivity #TechTips #Python3 #SoftwareEngineering
Forwarded from Machine Learning
In Python, building AI-powered Telegram bots unlocks massive potential for image generation, processing, and automationβ€”master this to create viral tools and ace full-stack interviews! πŸ€–

# Basic Bot Setup - The foundation (PTB v20+ Async)
from telegram.ext import Application, CommandHandler, MessageHandler, filters

async def start(update, context):
await update.message.reply_text(
"✨ AI Image Bot Active!\n"
"/generate - Create images from text\n"
"/enhance - Improve photo quality\n"
"/help - Full command list"
)

app = Application.builder().token("YOUR_BOT_TOKEN").build()
app.add_handler(CommandHandler("start", start))
app.run_polling()


# Image Generation - DALL-E Integration (OpenAI)
import openai
from telegram.ext import ContextTypes

openai.api_key = os.getenv("OPENAI_API_KEY")

async def generate(update: Update, context: ContextTypes.DEFAULT_TYPE):
if not context.args:
await update.message.reply_text("❌ Usage: /generate cute robot astronaut")
return

prompt = " ".join(context.args)
try:
response = openai.Image.create(
prompt=prompt,
n=1,
size="1024x1024"
)
await update.message.reply_photo(
photo=response['data'][0]['url'],
caption=f"🎨 Generated: *{prompt}*",
parse_mode="Markdown"
)
except Exception as e:
await update.message.reply_text(f"πŸ”₯ Error: {str(e)}")

app.add_handler(CommandHandler("generate", generate))


Learn more: https://hackmd.io/@husseinsheikho/building-AI-powered-Telegram-bots

#Python #TelegramBot #AI #ImageGeneration #StableDiffusion #OpenAI #MachineLearning #CodingInterview #FullStack #Chatbots #DeepLearning #ComputerVision #Programming #TechJobs #DeveloperTips #CareerGrowth #CloudComputing #Docker #APIs #Python3 #Productivity #TechTips


https://t.me/DataScienceM 🦾
Please open Telegram to view this post
VIEW IN TELEGRAM