Do you know that Python can shift sequences without slicing and creating new lists?

When you need to cyclically shift data, many use slicing:

data = data[-1:] + data[:-1]

But deque.rotate() does this at the level of the data structure and usually works more efficiently for cyclical operations.

q.rotate(1)

A negative value rotates the queue in the other direction.

q.rotate(-2)

This is useful for ring buffers, task schedulers, cyclical queues, and round-robin algorithms.

workers.rotate(-1)

🔥 deque.rotate() allows you to implement cyclical data structures without manual index logic and without creating new lists.

#Python #DataStructures #CodingTips #Programming #Deque #Tech

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Join our livestream with Marina Wyss, Senior Applied Scientist at Twitch, as we discuss how to break into AI Engineering in 2026.

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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?
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🧭 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

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✦ Where beginners should start
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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

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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

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How to create your own context manager in Python for opening and closing a connection to the SQLite database

The enter() method is used when opening a connection, and the exit() method is used when closing it:

import sqlite3

class DatabaseConnection:
    def __init__(self, db_name):
        self.db_name = db_name
        self.connection = None

    def __enter__(self):
        self.connection = sqlite3.connect(self.db_name)
        return self.connection

    def __exit__(self, exc_type, exc_val, exc_tb):
        if self.connection:
            self.connection.close()

# Usage
with DatabaseConnection("example.db") as conn:
    cursor = conn.cursor()
    cursor.execute("SELECT * FROM users")

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#Python #SQLite #ContextManager #Programming #Coding #Tech