👩‍💻 heapq.merge(): Combining sorted data!

If you have multiple sources of data that are already sorted, you don't need to collect them into a single collection and sort them again. heapq.merge() combines such sources into a single, ordered iterator.

In this guide:
• We will combine multiple sorted sequences;
• We will explore lazy processing of large data sources;
• We will configure comparison using the key argument;
• We will combine data sorted in reverse order.

This is especially useful when working with logs, files, and query results, where each source already provides data in the correct order.

#Python #heapq #DataProcessing #CodingTips #Programming #Algorithms

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Hands On Python Data Science - Data Science Bootcamp

Master Python for Data Science with Real-World Applications: Dive Deep into Data Analysis, Machine Learning

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#Programming #Coding #Development #Tech #Python #DataScience

📱 270 tools for Python developers

The repository contains:
🫡 Linters and formatters;
🫡 Type checkers;
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🫡 Debugging and profiling tools;
🫡 Package managers;
🫡 Logging tools;
🫡 Security tools;
🫡 Documentation and package building tools.

Save this to your favorites, as the list is updated regularly.

⛓️ Link to the repository

#Python #DevTools #Programming #Coding #SoftwareDevelopment #GitHub

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Python Lists: A Quick Reference 🐍

*   Definition: Lists are ordered, mutable collections that can contain various data types and duplicates.
*   Creating Lists: Creating empty, numerical, mixed, nested lists, and lists with duplicates.
*   Accessing List Elements: Accessing elements using positive and negative indexing, as well as slicing with

start:end:step

.
*   Common Operations: Adding, inserting, concatenating, deleting, clearing, searching, sorting, and reversing lists.
*   List Methods:

append()

,

insert()

,

extend()

,

remove()

,

pop()

,

clear()

,

index()

,

count()

,

sort()

, and

reverse()

.
*   List Comprehension: Quickly creating lists using expressions and conditions.
*   List vs. Tuple: Differences between mutable lists and immutable tuples.
*   Important Points: Specifics of indexing, slicing, data types, and working with lists.

#Python #Coding #Programming #DataStructures #PythonTips #LearnPython

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📚 Download 10 Python books for FREE:

1. Think Python — O’Reilly
https://t.co/X7y3pX68IW

2. The Big Book of Small Python Projects
https://inventwithpython.com/bigbookpython/

3. Data Structures
https://opendatastructures.org/ods-python.pdf

4. Data Science Handbook
https://t.co/9aOLdiAbim

5. Data Analysis
https://wesmckinney.com/book/

6. Data Science
https://t.co/TusyBWGfrx

7. Machine Learning
https://t.co/7veOwESe8q

8. Statistics
https://t.co/waWDQylQpY

9. Think Bayes
https://allendowney.github.io/ThinkBayes2/

10. Clean Code in Python — Packt
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Python is the #1 language in AI. 🐍

But you don’t need to learn all of it. (save this) 📌

#Python #AI #Programming #DataScience #MachineLearning #Tech

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In Python 3.15, a single asterisk replaces nested loops. 🐍✨

Previously, to flatten a list, you would write:

rows = [[1, 2], [3], [4, 5]]

flat = [x for row in rows for x in row]

Now, you can simply use:

flat = [*row for row in rows]
# [1, 2, 3, 4, 5]

A double asterisk merges dictionaries: 📦

configs = [
    {"debug": False, "timeout": 10},
    {"timeout": 30},
]

config = {**part for part in configs}
# {'debug': False, 'timeout': 30}

When keys overlap, the last value wins – this is convenient for combining settings from multiple sources. ⚙️

Unpacking removes one level of nesting. In Python 3.14, this syntax within comprehensions will raise a SyntaxError. 🚫

https://peps.python.org/pep-0798/

#Python #Python315 #Programming #CodingTips #TechNews #Developer

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📝 Cheat sheet for Python:

Higher-order functions:

🔹 map() - applies a function to each element
🔹 filter() - selects elements based on a condition
🔹 reduce() - sequentially combines elements into a single value

These functions help to process collections concisely and perform data transformations.

#Python #Programming #Coding #HigherOrderFunctions #DataProcessing #TechTips

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🚀 asyncio.Queue.shutdown() — shutting down handlers without special markers

Starting with Python 3.13, the asyncio.Queue can be closed using shutdown(), without the need to use None or other special values.

import asyncio

async def worker(queue):
    while True:
        try:
            task = await queue.get()
        except asyncio.QueueShutDown:
            break

        print(task)
        queue.task_done()

async def main():
    queue = asyncio.Queue()
    task = asyncio.create_task(worker(queue))

    await queue.put("task-1")
    await queue.put("task-2")

    queue.shutdown()
    await queue.join()
    await task

asyncio.run(main())

After shutdown(), no new items are added, and existing items are processed. When the queue is empty, get() will raise asyncio.QueueShutDown.

For a forced shutdown, there is shutdown(immediate=True), which clears the queue but may disrupt the normal behavior of join().

#Python #Asyncio #Programming #DevTips #Coding #Tech

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Extracting named entities (NER) from contract texts using spaCy. 📝

Manually parsing legal documents to find organizations, dates, and amounts is too time-consuming. The spaCy library allows you to automatically find and classify named entities in unstructured text. We will write a Python script that loads a language model and recognizes key entities in a contract excerpt. 🚀

We will install the spaCy library and download a pre-trained language model for working with the Russian language. 🇷🇺

pip install spacy && python3 -m spacy download ru_core_news_sm

The spaCy library and the Russian language model have been successfully loaded into the environment. ✅

We will create a Python script called extract_ner.py that processes the contract text through a language pipeline and prints the identified entities. 🐍

import spacy

nlp = spacy.load("ru_core_news_sm")
text = "OOO 'Vector' undertakes to pay 500,000 rubles by October 15, 2026, in Moscow."
doc = nlp(text)

for ent in doc.ents:
    print(f"{ent.text}

#spacy #python #nlp #dataScience #programming #automation

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