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@Codeprogrammer Cheat Sheet Numpy.pdf
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This checklist covers the essentials of NumPy in one place, helping you:

- Create and initialize arrays
- Perform element-wise computations
- Stack and split arrays
- Apply linear algebra functions
- Efficiently index, slice, and manipulate arrays

…and much more!

Feel free to share if you found this useful, and let me know in the comments if I missed anything!

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#NumPy #Python #DataScience #MachineLearning #Automation #DeepLearning #Programming #Tech #DataAnalysis #SoftwareDevelopment #Coding #TechTips #PythonForDataScience
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Topic: Python Script to Convert a Shared ChatGPT Link to PDF – Step-by-Step Guide

---

### Objective

In this lesson, we’ll build a Python script that:

• Takes a ChatGPT share link (e.g., https://chat.openai.com/share/abc123)
• Downloads the HTML content of the chat
• Converts it to a PDF file using pdfkit and wkhtmltopdf

This is useful for archiving, sharing, or printing ChatGPT conversations in a clean format.

---

### 1. Prerequisites

Before starting, you need the following libraries and tools:

#### • Install pdfkit and requests

pip install pdfkit requests


#### • Install wkhtmltopdf

Download from:
https://wkhtmltopdf.org/downloads.html

Make sure to add the path of the installed binary to your system PATH.

---

### 2. Python Script: Convert Shared ChatGPT URL to PDF

import pdfkit
import requests
import os

# Define output filename
output_file = "chatgpt_conversation.pdf"

# ChatGPT shared URL (user input)
chat_url = input("Enter the ChatGPT share URL: ").strip()

# Verify the URL format
if not chat_url.startswith("https://chat.openai.com/share/"):
print("Invalid URL. Must start with https://chat.openai.com/share/")
exit()

try:
# Download HTML content
response = requests.get(chat_url)
if response.status_code != 200:
raise Exception(f"Failed to load the chat: {response.status_code}")

html_content = response.text

# Save HTML to temporary file
with open("temp_chat.html", "w", encoding="utf-8") as f:
f.write(html_content)

# Convert HTML to PDF
pdfkit.from_file("temp_chat.html", output_file)

print(f"\n PDF saved as: {output_file}")

# Optional: remove temp file
os.remove("temp_chat.html")

except Exception as e:
print(f" Error: {e}")


---

### 3. Notes

• This approach works only if the shared page is publicly accessible (which ChatGPT share links are).
• The PDF output will contain the web page version, including theme and layout.
• You can customize the PDF output using pdfkit options (like page size, margins, etc.).

---

### 4. Optional Enhancements

• Add GUI with Tkinter
• Accept multiple URLs
• Add PDF metadata (title, author, etc.)
• Add support for offline rendering using BeautifulSoup to clean content

---

### Exercise

• Try converting multiple ChatGPT share links to PDF
• Customize the styling with your own CSS
• Add a timestamp or watermark to the PDF

---

#Python #ChatGPT #PDF #WebScraping #Automation #pdfkit #tkinter

https://t.me/CodeProgrammer
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Python | Machine Learning | Coding | R
Photo
# 📚 Python Tutorial: Convert EPUB to PDF (Preserving Images)
#Python #EPUB #PDF #EbookConversion #Automation

This comprehensive guide will show you how to convert EPUB files (including those with images) to high-quality PDFs using Python.

---

## 🔹 Required Tools & Libraries
We'll use these Python packages:
- ebooklib - For EPUB parsing
- pdfkit (wrapper for wkhtmltopdf) - For PDF generation
- Pillow - For image handling (optional)

pip install ebooklib pdfkit pillow


Also install system dependencies:
# On Ubuntu/Debian
sudo apt-get install wkhtmltopdf

# On MacOS
brew install wkhtmltopdf

# On Windows (download from wkhtmltopdf.org)


---

## 🔹 Step 1: Extract EPUB Contents
First, we'll unpack the EPUB file to access its HTML and images.

from ebooklib import epub
from bs4 import BeautifulSoup
import os

def extract_epub(epub_path, output_dir):
book = epub.read_epub(epub_path)

# Create output directory
os.makedirs(output_dir, exist_ok=True)

# Extract all items (chapters, images, styles)
for item in book.get_items():
if item.get_type() == epub.ITEM_IMAGE:
# Save images
with open(os.path.join(output_dir, item.get_name()), 'wb') as f:
f.write(item.get_content())
elif item.get_type() == epub.ITEM_DOCUMENT:
# Save HTML chapters
with open(os.path.join(output_dir, item.get_name()), 'wb') as f:
f.write(item.get_content())

return [item.get_name() for item in book.get_items() if item.get_type() == epub.ITEM_DOCUMENT]


---

## 🔹 Step 2: Convert HTML to PDF
Now we'll convert the extracted HTML files to PDF while preserving images.

import pdfkit
from PIL import Image # For image validation (optional)

def html_to_pdf(html_files, output_pdf, base_dir):
options = {
'encoding': "UTF-8",
'quiet': '',
'enable-local-file-access': '', # Critical for local images
'no-outline': None,
'margin-top': '15mm',
'margin-right': '15mm',
'margin-bottom': '15mm',
'margin-left': '15mm',
}

# Validate images (optional)
for html_file in html_files:
soup = BeautifulSoup(open(os.path.join(base_dir, html_file)), 'html.parser')
for img in soup.find_all('img'):
img_path = os.path.join(base_dir, img['src'])
try:
Image.open(img_path) # Validate image
except Exception as e:
print(f"Image error in {html_file}: {e}")
img.decompose() # Remove broken images

# Convert to PDF
pdfkit.from_file(
[os.path.join(base_dir, f) for f in html_files],
output_pdf,
options=options
)


---

## 🔹 Step 3: Complete Conversion Function
Combine everything into a single workflow.

def epub_to_pdf(epub_path, output_pdf, temp_dir="temp_epub"):
try:
print(f"Converting {epub_path} to PDF...")

# Step 1: Extract EPUB
print("Extracting EPUB contents...")
html_files = extract_epub(epub_path, temp_dir)

# Step 2: Convert to PDF
print("Generating PDF...")
html_to_pdf(html_files, output_pdf, temp_dir)

print(f"Success! PDF saved to {output_pdf}")
return True

except Exception as e:
print(f"Conversion failed: {str(e)}")
return False
finally:
# Clean up temporary files
if os.path.exists(temp_dir):
import shutil
shutil.rmtree(temp_dir)


---

## 🔹 Advanced Options
### 1. Custom Styling
Add CSS to improve PDF appearance:

def html_to_pdf(html_files, output_pdf, base_dir):
options = {
# ... previous options ...
'user-style-sheet': 'styles.css', # Custom CSS
}

# Create CSS file if needed
css = """
body { font-family: "Times New Roman", serif; font-size: 12pt; }
img { max-width: 100%; height: auto; }
"""
with open(os.path.join(base_dir, 'styles.css'), 'w') as f:
f.write(css)

pdfkit.from_file(/* ... */)
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🚀 Comprehensive Tutorial: Build a Folder Monitoring & Intruder Detection System in Python

In this comprehensive, step-by-step tutorial, you will learn how to build a real-time folder monitoring and intruder detection system using Python.

🔐 Your Goal:
Create a background program that:
- Monitors a specific folder on your computer.
- Instantly captures a photo using the webcam whenever someone opens that folder.
- Saves the photo with a timestamp in a secure folder.
- Runs automatically when Windows starts.
- Keeps running until you manually stop it (e.g., via Task Manager or a hotkey).

Read and get code: https://hackmd.io/@husseinsheikho/Build-a-Folder-Monitoring

#Python #Security #FolderMonitoring #IntruderDetection #OpenCV #FaceCapture #Automation #Windows #TaskScheduler #ComputerVision


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🥇 This repo is like gold for every data scientist!

Just open your browser; a ton of interactive exercises and real experiences await you. Any question about statistics, probability, Python, or machine learning, you'll get the answer right there! With code, charts, even animations. This way, you don't waste time, and what you learn really sticks in your mind!

⬅️ Data science statistics and probability topics
⬅️ Clustering
⬅️ Principal Component Analysis (PCA)
⬅️ Bagging and Boosting techniques
⬅️ Linear regression
⬅️ Neural networks and more...


📂 Int Data Science Python Dash
🐱 GitHub-Repos

👉 @codeprogrammer

#Python #OpenCV #Automation #ML #AI #DEEPLEARNING #MACHINELEARNING #ComputerVision
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