This channels is for Programmers, Coders, Software Engineers.

0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
6️⃣ Statistics
7️⃣ Deep Learning
8️⃣ programming Languages

✅ https://news.1rj.ru/str/addlist/8_rRW2scgfRhOTc0

✅ https://news.1rj.ru/str/Codeprogrammer

Clean code advice for Python:

Do not add redundant context.
Avoid adding unnecessary data to variable names, especially when working with classes.

Example:

This is bad:

class Person:
    def __init__(self, person_first_name, person_last_name, person_age):
        self.person_first_name = person_first_name
        self.person_last_name = person_last_name
        self.person_age = person_age

This is good:

class Person:
    def __init__(self, first_name, last_name, age):
        self.first_name = first_name
        self.last_name = last_name
        self.age = age

👉 @DataScience4

python-docx: Create and Modify Word Documents #python

python-docx is a Python library for reading, creating, and updating Microsoft Word 2007+ (.docx) files.

Installation

pip install python-docx

Example

from docx import Document

document = Document()
document.add_paragraph("It was a dark and stormy night.")
<docx.text.paragraph.Paragraph object at 0x10f19e760>
document.save("dark-and-stormy.docx")

document = Document("dark-and-stormy.docx")
document.paragraphs[0].text
'It was a dark and stormy night.'

https://news.1rj.ru/str/DataScienceN 🚗

Get a weather forecast without API and complex settings in Python

We use the wttr.in: https://github.com/chubin/wttr.in

service — a simple and powerful tool that shows the weather right in the console.

To work with the HTTP request, you only need one library - requests. Installing it is very easy:

pip install requests

Here is the minimal and clear code to get the forecast:

import requests

city = input("Enter the city name: ")
url = f"https://wttr.in/{city}"

try:
    response = requests.get(url)
    print(response.text)
except Exception:
    print("Oops! Something went wrong. Please try again later.")

Just enter the desired city and get a detailed forecast with temperature, precipitation

Try it yourself 😏

https://news.1rj.ru/str/DataScience4 🌟

Django REST Framework and Vue versus Django and HTMX

https://testdriven.io/blog/drf-vue-vs-django-htmx/

Learn how the development process varies between working with Django REST Framework and Vue versus #Django and #HTMX.

https://news.1rj.ru/str/DataScience4 🌟

Building a Real-time Dashboard with FastAPI and Svelte

In this tutorial, you'll learn how to build a real-time analytics dashboard using FastAPI and Svelte. We'll use server-sent events (SSE) to stream live data updates from FastAPI to our Svelte frontend, creating an interactive dashboard that updates in real-time.

Start: https://testdriven.io/blog/fastapi-svelte/

https://news.1rj.ru/str/DataScience4 😡

🐍📰 What Are Mixin Classes in Python?

Learn how to use Python mixin classes to write modular, reusable, and flexible code with practical examples and design tips

https://realpython.com/python-mixin/

https://news.1rj.ru/str/DataScience4 🍏

marimo: A Reactive, Reproducible Notebook

marimo notebooks redefine the notebook experience by offering a reactive environment that addresses the limitations of traditional linear notebooks. With marimo, you can seamlessly reproduce and share content while benefiting from automatic cell updates and a correct execution order. Discover how marimo’s features make it an ideal tool for documenting research and learning activities.

Link: https://realpython.com/marimo-notebook/

https://news.1rj.ru/str/DataScience4 🫰

https://news.1rj.ru/str/DataScience4 📁

This channels is for Programmers, Coders, Software Engineers.

0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
6️⃣ Statistics
7️⃣ Deep Learning
8️⃣ programming Languages

✅ https://news.1rj.ru/str/addlist/8_rRW2scgfRhOTc0

✅ https://news.1rj.ru/str/Codeprogrammer

Cheat sheet for Python interview

1. Swap variables without a temporary one

a, b = 5, 10
a, b = b, a

2. One-line if-else (ternary)

result = "Even" if x % 2 == 0 else "Odd"

3. List Comprehension

squares = [x**2 for x in range(10)]
evens = [x for x in range(10) if x % 2 == 0]

4. Set and Dict Comprehension

unique = {x for x in [1,2,2,3]}        # remove duplicates
squares = {x: x**2 for x in range(5)}  # dict comprehension

5. Most common element in a list

from collections import Counter
most_common = Counter(['a','b','a','c']).most_common(1)[0][0]

6. Merging dictionaries (Python 3.9+)

a = {'x': 1}
b = {'y': 2}
merged = a | b

7. Returning multiple values

def stats(x):
    return max(x), min(x), sum(x)

high, low, total = stats([1, 2, 3])

8. Using zip to iterate over two lists

names = ['a', 'b']
scores = [90, 85]

for n, s in zip(names, scores):
    print(f"{n}: {s}")

9. Flattening nested lists

nested = [[1,2], [3,4]]
flat = [item for sublist in nested for item in sublist]

10. Default values in a dictionary

from collections import defaultdict
d = defaultdict(int)
d['apple'] += 1   # no KeyError

11. Lambda in one line

square = lambda x: x**2
print(square(4))

12. enumerate with index

for i, v in enumerate(['a', 'b', 'c']):
    print(i, v)

13. Sorting by key or value

d = {'a': 3, 'b': 1, 'c': 2}
sorted_by_val = sorted(d.items(), key=lambda x: x[1])

14. Reading file lines into a list

with open('file.txt') as f:
    lines = f.read().splitlines()

15. Type Hints

def add(x: int, y: int) -> int:
    return x + y

👉 @DataScience4