Learn Python Coding

⚠ Message was hidden by channel owner

⚠ Message was hidden by channel owner

Safe rounding of numbers with math.fsum

import math

# Initial list with fractions
values = [0.1] * 10

# 1. Regular summation via sum()
print(f"Standard sum(): {sum(values)}") # 0.9999999999999999

# 2. Exact summation via math.fsum()
print(f"Exact math.fsum(): {math.fsum(values)}") # 1.0

Eliminating errors when calculating arrays We've already discussed why float in Python loses accuracy and how Decimal deals with this. But what if you need to add a million ordinary real numbers from a database or matrix, and it's not possible to convert everything to heavy Decimal objects due to a performance hit? The math.fsum() function comes to the rescue. — Eliminating accumulated error: When sequentially adding elements via the standard sum(), the microscopic errors of float are rounded at each step and "accumulate" in the loop. The math.fsum() function tracks intermediate accuracy losses and compensates for them during the calculations. — High performance: Since the math module is written in C, this function works several times faster than manually iterating through the array or using alternative data types. You get the speed of basic float calculations with near-perfect accuracy. — Stability in Data Science: This tool is indispensable when working with weights in neural networks, calculating averages of large samples, or processing financial transactions, where speed is important but it's critical not to lose valuable cents and fractions during mass operations. 🐍 #Python #DataScience #Coding #Programming #MathFsum #TechTips ✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk ⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A 🚀 Level up your AI & Data Science skills with HelloEncyclo — a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more. ✅ 13 courses live + 40+ coming soon 🎯 One access, lifetime updates 🔑 Use code: PRESALE-BOOK-WAVE-2GFG 👉 https://helloencyclo.com/?ref=HUSSEINSHEIKHO

⚠ Message was hidden by channel owner

⚠ Message was hidden by channel owner

⚠ Message was hidden by channel owner

⚠ Message was hidden by channel owner

⚠ Message was hidden by channel owner

⚠ Message was hidden by channel owner

⚠ Message was hidden by channel owner

⚠ Message was hidden by channel owner

Convert PDF to structured JSON — in a couple of lines and without hassle! 📄✨ Today, we'll create a mini-service that takes a PDF document, extracts the text from it, and asks GPT to neatly organize the content into sections: title, author, date, and a list of sections. 🚀 First, let's connect the necessary libraries and API key:

import os
from PyPDF2 import PdfReader
from openai import OpenAI

client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))

Now, let's extract the text from the PDF. We'll loop through all the pages and combine them into a single string:

reader = PdfReader("document.pdf")
text = "
".join(page.extract_text() for page in reader.pages)

Next, we'll send the obtained text to GPT. We'll ask the model to return a structured JSON with the necessary fields:

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[
        {"role": "system", "content": (
            "You are a PDF parser. Return a JSON with the fields: title, author, date, sections. "
            "Each section is an object with name and summary."
        )},
        {"role": "user", "content": text}
    ]
)

Output the result:

structured = response.choices[0].message.content.strip()
print(structured)

🔥 Suitable for contracts, reports, methodologies, and any PDFs — we immediately get a JSON ready for use. #PDF #JSON #Python #GPT #Automation #DataScience ✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk ⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A 🚀 Level up your AI & Data Science skills with HelloEncyclo — a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more. ✅ 13 courses live + 40+ coming soon 🎯 One access, lifetime updates 🔑 Use code: PRESALE-BOOK-WAVE-2GFG 👉 https://helloencyclo.com/?ref=HUSSEINSHEIKHO

Shuffling without repetitions:

import random

# Initial list of candidates or prizes
participants = ["Alexey", "Maria", "Ivan", "Olga", "Dmitry"]

# 1. Selecting 3 unique winners (sample without replacement)
winners = random.sample(participants, k=3)
print(f"Winners: {winners}") 
# The result is different each time, but there will be no repetitions within the list of winners!

# 2. Shuffling an entire string (creating an anagram)
word = "python"
shuffled_word = "".join(random.sample(word, len(word)))
print(f"Anagram: {shuffled_word}")

# 3. Important difference: random.choices allows repetitions
print(f"With repetitions: {random.choices(participants, k=3)}")

✨ Honest selection and generation of unique sets When it's necessary to implement the logic of prize draws, random task distribution, or generating test questions, developers often use random.choice() in a loop. But this approach requires manually ensuring that the same element is not selected twice. The random.sample function takes on this routine. — Guarantee of uniqueness: The main property of random.sample is "without replacement". The extracted element no longer participates in the next selection cycle, which completely eliminates duplicates in the resulting list. — Safety of the original: The function does not modify the original list (unlike random.shuffle()), but creates a completely new array with the results. This allows the structure of the original data to remain intact. — Strict control of size: If you pass a parameter k (the number of elements) that exceeds the length of the original list, Python will not start duplicating elements and will immediately throw an ValueError error. This protects the program logic from incorrect data. #Python #Random #Coding #NoRepetition #DataScience #UniqueSets ✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk ⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A 🚀 Level up your AI & Data Science skills with HelloEncyclo — a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more. ✅ 13 courses live + 40+ coming soon 🎯 One access, lifetime updates 🔑 Use code: PRESALE-BOOK-WAVE-2GFG 👉 https://helloencyclo.com/?ref=HUSSEINSHEIKHO

⚠ Message was hidden by channel owner

Join our livestream with Marina Wyss, Senior Applied Scientist at Twitch, as we discuss how to break into AI Engineering in 2026. Sign up for FREE and save your seat here: luma.com/qgz4g4r7 Why should you join? Many people interested in AI Engineering are asking the same questions: ❓ Where do I start? 🤔 Do I need deep math first? 🧠 Should I focus on ML, LLMs, RAG, or AI agents? 🧭 How do I avoid wasting time learning the wrong things? 🚀 How do I go from learning to becoming hireable? If you’re interested in AI Engineering but unsure how to approach it, this livestream is for you. What you’ll learn ✦ What AI Engineering really is ✦ Where beginners should start ✦ What skills and topics actually matter ✦ Common mistakes to avoid ✦ Self-study vs bootcamp vs MSc ✦ How to think about becoming hireable in AI ✦ Practical advice from someone already working in the field Sign up for FREE and save your seat: luma.com/qgz4g4r7

A 14-day tutorial where you build a Python code-agent CLI in the style of Claude Code from scratch and simultaneously understand how the Agent Harness actually works. 🛠️🤖 In the end, you don't just call a ready-made agent via the API, but you understand the components that make up a Claude Code-like tool. 🧠⚙️ https://github.com/bozhouDev/14days-build-claude-code-cli/blob/main/README.en.md #Python #AI #ClaudeCode #CLI #CodingTutorial #Tech ✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk ⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A 🚀 Level up your AI & Data Science skills with HelloEncyclo — a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more. ✅ 13 courses live + 40+ coming soon 🎯 One access, lifetime updates 🔑 Use code: PRESALE-BOOK-WAVE-2GFG 👉 https://helloencyclo.com/?ref=HUSSEINSHEIKHO

🎰 Welcome Bonus 1200% — Maczo Crypto Casino 🎮 Crypto exchange · Sports · Live casino — all in one place 💳 USDT instant deposit & withdrawal →https://tglink.io/10ac0a48667b40 → Affiliate 60%